Wagstaff, Kiri; Mazzoni, Dominic
An improved active learning method has been devised for training data classifiers. One example of a data classifier is the algorithm used by the United States Postal Service since the 1960s to recognize scans of handwritten digits for processing zip codes. Active learning algorithms enable rapid training with minimal investment of time on the part of human experts to provide training examples consisting of correctly classified (labeled) input data. They function by identifying which examples would be most profitable for a human expert to label. The goal is to maximize classifier accuracy while minimizing the number of examples the expert must label. Although there are several well-established methods for active learning, they may not operate well when irrelevant examples are present in the data set. That is, they may select an item for labeling that the expert simply cannot assign to any of the valid classes. In the context of classifying handwritten digits, the irrelevant items may include stray marks, smudges, and mis-scans. Querying the expert about these items results in wasted time or erroneous labels, if the expert is forced to assign the item to one of the valid classes. In contrast, the new algorithm provides a specific mechanism for avoiding querying the irrelevant items. This algorithm has two components: an active learner (which could be a conventional active learning algorithm) and a relevance classifier. The combination of these components yields a method, denoted Relevance Bias, that enables the active learner to avoid querying irrelevant data so as to increase its learning rate and efficiency when irrelevant items are present. The algorithm collects irrelevant data in a set of rejected examples, then trains the relevance classifier to distinguish between labeled (relevant) training examples and the rejected ones. The active learner combines its ranking of the items with the probability that they are relevant to yield a final decision about which item
Faillie, Jean-Luc; Suissa, Samy
Among the observational studies of drug effects in chronic diseases, many of them have found effects that were exaggerated or wrong. Among bias responsible for these errors, the immortal time bias, concerning the definition of exposure and exposure periods, is relevantly important as it usually tends to wrongly attribute a significant benefit to the study drug (or exaggerate a real benefit). In this article, we define the mechanism of immortal time bias, we present possible solutions and illustrate its consequences through examples of pharmacoepidemiological studies of drug effects. © 2014 Société Française de Pharmacologie et de Thérapeutique.
This textbook introduces and explains the basic concepts on which statics is based utilizing real engineering examples. The authors emphasize the learning process by showing a real problem, analyzing it, simplifying it, and developing a way to solve it. This feature teaches students intuitive thinking in solving real engineering problems using the fundamentals of Newton’s laws. This book also: · Stresses representation of physical reality in ways that allow students to solve problems and obtain meaningful results · Emphasizes identification of important features of the structure that should be included in a model and which features may be omitted · Facilitates students' understanding and mastery of the "flow of thinking" practiced by professional engineers.
Højen, Anders; Nazzi, Thierry
The present study explored whether the phonological bias favoring consonants found in French-learning infants and children when learning new words (Havy & Nazzi, 2009; Nazzi, 2005) is language-general, as proposed by Nespor, Peña and Mehler (2003), or varies across languages, perhaps as a functio...
This talk will present the different Machine Learning tools that the INSPIRE is developing and integrating in order to automatize as much as possible content selection and curation in a subject based repository.
Lange, Karin E.; Booth, Julie L.; Newton, Kristie J.
For students to be successful in algebra, they must have a truly conceptual understanding of key algebraic features as well as the procedural skills to complete a problem. One strategy to correct students' misconceptions combines the use of worked example problems in the classroom with student self-explanation. "Self-explanation" is the…
Van Gog, Tamara; Kester, Liesbeth; Paas, Fred
Van Gog, T., Kester, L., & Paas, F. (2011). Effects of worked examples, example-problem, and problem-example pairs on novices’ learning. Contemporary Educational Psychology, 36(3), 212-218. doi:10.1016/j.cedpsych.2010.10.004
Taniguchi, Hidetaka; Sato, Hiroshi; Shirakawa, Tomohiro
Human learners can generalize a new concept from a small number of samples. In contrast, conventional machine learning methods require large amounts of data to address the same types of problems. Humans have cognitive biases that promote fast learning. Here, we developed a method to reduce the gap between human beings and machines in this type of inference by utilizing cognitive biases. We implemented a human cognitive model into machine learning algorithms and compared their performance with the currently most popular methods, naïve Bayes, support vector machine, neural networks, logistic regression and random forests. We focused on the task of spam classification, which has been studied for a long time in the field of machine learning and often requires a large amount of data to obtain high accuracy. Our models achieved superior performance with small and biased samples in comparison with other representative machine learning methods.
Grechanuk, Pavel Aleksandrovi [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)
For many real-world applications in radiation transport where simulations are compared to experimental measurements, like in nuclear criticality safety, the bias (simulated - experimental keff) in the calculation is an extremely important quantity used for code validation. The objective of this project is to accurately predict the bias of MCNP6  criticality calculations using machine learning (ML) algorithms, with the intention of creating a tool that can complement the current nuclear criticality safety methods. In the latest release of MCNP6, the Whisper tool is available for criticality safety analysts and includes a large catalogue of experimental benchmarks, sensitivity profiles, and nuclear data covariance matrices. This data, coming from 1100+ benchmark cases, is used in this study of ML algorithms for criticality safety bias predictions.
1 déc. 2010 ... Couverture du livre Collaborative Learning in Practice: Examples from Natural Resource Management in Asia ... Collaborative Learning in Practice saura intéresser les universitaires, les chercheurs et les étudiants des cycles supérieurs en études du développement, ... Strategic leverage on value chains.
Chen, Jianzhong; Muggleton, Stephen; Santos, José
We revisit an application developed originally using abductive Inductive Logic Programming (ILP) for modeling inhibition in metabolic networks. The example data was derived from studies of the effects of toxins on rats using Nuclear Magnetic Resonance (NMR) time-trace analysis of their biofluids together with background knowledge representing a subset of the Kyoto Encyclopedia of Genes and Genomes (KEGG). We now apply two Probabilistic ILP (PILP) approaches - abductive Stochastic Logic Programs (SLPs) and PRogramming In Statistical modeling (PRISM) to the application. Both approaches support abductive learning and probability predictions. Abductive SLPs are a PILP framework that provides possible worlds semantics to SLPs through abduction. Instead of learning logic models from non-probabilistic examples as done in ILP, the PILP approach applied in this paper is based on a general technique for introducing probability labels within a standard scientific experimental setting involving control and treated data. Our results demonstrate that the PILP approach provides a way of learning probabilistic logic models from probabilistic examples, and the PILP models learned from probabilistic examples lead to a significant decrease in error accompanied by improved insight from the learned results compared with the PILP models learned from non-probabilistic examples.
de Bruin, Angela; Treccani, Barbara; Della Sala, Sergio
It is a widely held belief that bilinguals have an advantage over monolinguals in executive-control tasks, but is this what all studies actually demonstrate? The idea of a bilingual advantage may result from a publication bias favoring studies with positive results over studies with null or negative effects. To test this hypothesis, we looked at conference abstracts from 1999 to 2012 on the topic of bilingualism and executive control. We then determined which of the studies they reported were subsequently published. Studies with results fully supporting the bilingual-advantage theory were most likely to be published, followed by studies with mixed results. Studies challenging the bilingual advantage were published the least. This discrepancy was not due to differences in sample size, tests used, or statistical power. A test for funnel-plot asymmetry provided further evidence for the existence of a publication bias. © The Author(s) 2014.
Culbertson, Jennifer; Smolensky, Paul; Legendre, Géraldine
How recurrent typological patterns, or universals, emerge from the extensive diversity found across the world's languages constitutes a central question for linguistics and cognitive science. Recent challenges to a fundamental assumption of generative linguistics-that universal properties of the human language acquisition faculty constrain the types of grammatical systems which can occur-suggest the need for new types of empirical evidence connecting typology to biases of learners. Using an artificial language learning paradigm in which adult subjects are exposed to a mix of grammatical systems (similar to a period of linguistic change), we show that learners' biases mirror a word-order universal, first proposed by Joseph Greenberg, which constrains typological patterns of adjective, numeral, and noun ordering. We briefly summarize the results of a probabilistic model of the hypothesized biases and their effect on learning, and discuss the broader implications of the results for current theories of the origins of cross-linguistic word-order preferences. Copyright © 2011 Elsevier B.V. All rights reserved.
Abdelraheem, Mohamed Ahmed; Beelen, Peter; Leander, Gregor
, we often tend to embed a security margin - from an efficiency perspective nothing else than wasted performance. The aim of this paper is to stimulate research on these foundations of block ciphers. We do this by presenting three examples of ciphers that behave differently to what is normally assumed...
A practical work outlining the theory and practice of using active learning techniques in library settings. It explains the theory of active learning and argues for its importance in our teaching and is illustrated using a large number of examples of techniques that can be easily transferred and used in teaching library and information skills to a range of learners within all library sectors. These practical examples recognise that for most of us involved in teaching library and information skills the one off session is the norm, so we need techniques that allow us to quickly grab and hold our
Tribello, Gareth A.; Ceriotti, Michele; Parrinello, Michele
A new self-learning algorithm for accelerated dynamics, reconnaissance metadynamics, is proposed that is able to work with a very large number of collective coordinates. Acceleration of the dynamics is achieved by constructing a bias potential in terms of a patchwork of one-dimensional, locally valid collective coordinates. These collective coordinates are obtained from trajectory analyses so that they adapt to any new features encountered during the simulation. We show how this methodology can be used to enhance sampling in real chemical systems citing examples both from the physics of clusters and from the biological sciences. PMID:20876135
This thesis addresses the problem of machine learning from biased datasets in the context of astronomical applications. In astronomy there are many cases in which the training sample does not follow the true distribution. The thesis examines different types of biases and proposes algorithms...... set. Against this background, the thesis begins with a survey of active learning algorithms for the support vector machine. If the cost of additional labeling is prohibitive, unlabeled data can often be utilized instead and the sample selection bias can be overcome through domain adaptation, that is...... to handle them. During learning and when applying the predictive model, active learning enables algorithms to select training examples from a pool of unlabeled data and to request the labels. This allows for selecting examples that maximize the algorithm's accuracy despite an initial bias in the training...
Fischer, Anja; Igel, Christian
Optimization based on k-step contrastive divergence (CD) has become a common way to train restricted Boltzmann machines (RBMs). The k-step CD is a biased estimator of the log-likelihood gradient relying on Gibbs sampling. We derive a new upper bound for this bias. Its magnitude depends on k...
Kendal, Jeremy; Giraldeau, Luc-Alain; Laland, Kevin
Humans and other animals do not use social learning indiscriminately, rather, natural selection has favoured the evolution of social learning rules that make selective use of social learning to acquire relevant information in a changing environment. We present a gene-culture coevolutionary analysis of a small selection of such rules (unbiased social learning, payoff-biased social learning and frequency-dependent biased social learning, including conformism and anti-conformism) in a population of asocial learners where the environment is subject to a constant probability of change to a novel state. We define conditions under which each rule evolves to a genetically polymorphic equilibrium. We find that payoff-biased social learning may evolve under high levels of environmental variation if the fitness benefit associated with the acquired behaviour is either high or low but not of intermediate value. In contrast, both conformist and anti-conformist biases can become fixed when environment variation is low, whereupon the mean fitness in the population is higher than for a population of asocial learners. Our examination of the population dynamics reveals stable limit cycles under conformist and anti-conformist biases and some highly complex dynamics including chaos. Anti-conformists can out-compete conformists when conditions favour a low equilibrium frequency of the learned behaviour. We conclude that evolution, punctuated by the repeated successful invasion of different social learning rules, should continuously favour a reduction in the equilibrium frequency of asocial learning, and propose that, among competing social learning rules, the dominant rule will be the one that can persist with the lowest frequency of asocial learning.
Learning from examples is a very effective means of initial cognitive skill acquisition. There is an enormous body of research on the specifics of this learning method. This article presents an instructionally oriented theory of example-based learning that integrates theoretical assumptions and findings from three research areas: learning from…
A Monte Carlo learning and biasing technique is described that does its learning and biasing in the random number space rather than the physical phase-space. The technique is probably applicable to all linear Monte Carlo problems, but no proof is provided here. Instead, the technique is illustrated with a simple Monte Carlo transport problem. Problems encountered, problems solved, and speculations about future progress are discussed. 12 refs
In many applications the histories of a normal Monte Carlo game rarely reach the target region. An approximate knowledge of the importance (with respect to the target) may be used to guide the particles more frequently into the target region. A Monte Carlo method is presented in which each history contributes to update the importance field such that eventually most target histories are sampled. It is a self-learning method in the sense that the procedure itself: (a) learns which histories are important (reach the target) and increases their probability; (b) reduces the probabilities of unimportant histories; (c) concentrates gradually on the more important target histories. (U.K.)
1 déc. 2010 ... Parmi ses publications récentes, citons Learning from the Field: Innovating China's Higher Education System (Foundation Books et CRDI, 2008) et Social and Gender Analysis in Natural Resource Management: Learning Studies and Lessons from Asia (Sage India, CAP et CRDI, 2006). Edición español: ...
Tombak, Busra; Altun, Sertel
Problem Statement: Motivation is a significant component of success in education, and it is best achieved by constructivist learning methods, especially cooperative Learning (CL). CL is a popular method among primary and secondary schools, but it is rarely used in higher education due to the large numbers of students and time restrictions. The…
Hansen, Toke Jansen; Mahoney, Michael W.
In many applications, one has side information, e.g., labels that are provided in a semi-supervised manner, about a specific target region of a large data set, and one wants to perform machine learning and data analysis tasks "nearby" that pre-specified target region. Locally-biased problems of t...
Caro, Daniel H.; Kyriakides, Leonidas; Televantou, Ioulia
Omitted prior achievement bias is pervasive in international assessment studies and precludes causal inference. For example, reported negative associations between student-oriented teaching strategies and student performance are against expectations and might actually reflect omitted prior achievement bias. Namely, that these teaching strategies…
Hu, Fang-Tzu; Ginns, Paul; Bobis, Janette
Cognitive load theory seeks to generate novel instructional designs through a focus on human cognitive architecture including a limited working memory; however, the potential for enhancing learning through non-visual or non-auditory working memory channels is yet to be evaluated. This exploratory experiment tested whether explicit instructions to…
Fischer, Paul; Hoeffgen, K.- U.; Lefmann, H.
dimension of a target class with respect to a sample class, which replaces the Vapnik-Chervonenkis dimension (V.N. Vapnik and A.Y. Chervonenkis, 1971). The investigation of structural aspects of the relative dimension is followed by its applications to learning environments. It turns out that computing...
Pedrini, Bonnie C.; Pedrini, D. T.
The purpose of this paper is to relate psychology to teaching generally, and to relate behavior shaping to curriculum, specifically. Focusing on operant conditioning and learning, many studies are cited which illustrate some of the work being done toward effectively shaping or modifying student behavior whether in terms of subject matter or…
Slobodyan, Sergey; Bogomolova, A.; Kolyuzhnov, Dmitri
Roč. 20, č. 3 (2016), s. 777-790 ISSN 1365-1005 R&D Projects: GA ČR(CZ) GCP402/11/J018 Institutional support: PRVOUK-P23 Keywords : constant gain * adaptive learning * e-stability Subject RIV: AH - Economics Impact factor: 0.718, year: 2016
Hansen, Toke Jansen; Mahoney, Michael W.
improved scaling properties. We provide several empirical examples demonstrating how these semi-supervised eigenvectors can be used to perform locally-biased learning; and we discuss the relationship between our results and recent machine learning algorithms that use global eigenvectors of the graph......In many applications, one has side information, e.g., labels that are provided in a semi-supervised manner, about a specific target region of a large data set, and one wants to perform machine learning and data analysis tasks nearby that prespecified target region. For example, one might......-based machine learning and data analysis tools. At root, the reason is that eigenvectors are inherently global quantities, thus limiting the applicability of eigenvector-based methods in situations where one is interested in very local properties of the data. In this paper, we address this issue by providing...
Voon, V; Derbyshire, K; Rück, C; Irvine, M A; Worbe, Y; Enander, J; Schreiber, L R N; Gillan, C; Fineberg, N A; Sahakian, B J; Robbins, T W; Harrison, N A; Wood, J; Daw, N D; Dayan, P; Grant, J E; Bullmore, E T
Why do we repeat choices that we know are bad for us? Decision making is characterized by the parallel engagement of two distinct systems, goal-directed and habitual, thought to arise from two computational learning mechanisms, model-based and model-free. The habitual system is a candidate source of pathological fixedness. Using a decision task that measures the contribution to learning of either mechanism, we show a bias towards model-free (habit) acquisition in disorders involving both natural (binge eating) and artificial (methamphetamine) rewards, and obsessive-compulsive disorder. This favoring of model-free learning may underlie the repetitive behaviors that ultimately dominate in these disorders. Further, we show that the habit formation bias is associated with lower gray matter volumes in caudate and medial orbitofrontal cortex. Our findings suggest that the dysfunction in a common neurocomputational mechanism may underlie diverse disorders involving compulsion.
Moul, Caroline; Dadds, Mark R
In accordance with a recently proposed account of amygdala function in psychopathy, it is hypothesized that people with high levels of psychopathic personality traits have a bias in learning style to encode the general valence, and neglect the specific-features, of an outcome. We present a novel learning task designed to operationalize these biases in learning style. The results from pilot samples of healthy adults and children and from a clinical sample of children with conduct problems provide support for the validity of the learning task as a measure of learning style and demonstrate a significant relationship between general-valence style learning and psychopathic personality traits. It is suggested that this relationship may be important for the aetiology of the social-cognitive deficits exhibited by psychopaths. These preliminary results suggest that this measure of learning style has the potential to be utilized as a research tool and may assist with the early identification, and treatment, of children with conduct problems and high levels of callous-unemotional traits.
An action learning approach to help managers enhance learning capacity involved a performance management seminar, work by action learning sets, implementation of a new performance management instrument with mentoring by action learning facilitators, and evaluation. Survey responses from 392 participants revealed satisfaction with managerial…
Rawson, Katherine A.; Dunlosky, John
Declarative concepts (i.e., key terms and corresponding definitions for abstract concepts) represent foundational knowledge that students learn in many content domains. Thus, investigating techniques to enhance concept learning is of critical importance. Various theoretical accounts support the expectation that example generation will serve this…
Warnick, Bryan R.
"Imitation and Education" provides an in-depth reassessment of learning by example that places imitation in a larger social context. It is the first book to bring together ancient educational thought and startling breakthroughs in the fields of cognitive science, psychology, and philosophy to reconsider how we learn from the lives of…
Hoogerheide, V.; Loyens, S.M.M.; van Gog, T.
Online learning from video modeling examples, in which a human model demonstrates and explains how to perform a learning task, is an effective instructional method that is increasingly used nowadays. However, model characteristics such as gender tend to differ across videos, and the model-observer
Hoogerheide, Vincent; Loyens, Sofie M. M.; van Gog, Tamara
Online learning from video modeling examples, in which a human model demonstrates and explains how to perform a learning task, is an effective instructional method that is increasingly used nowadays. However, model characteristics such as gender tend to differ across videos, and the model-observer similarity hypothesis suggests that such…
V. Hoogerheide (Vincent); S.M.M. Loyens (Sofie); T.A.J.M. van Gog (Tamara)
textabstractOnline learning from video modeling examples, in which a human model demonstrates and explains how to perform a learning task, is an effective instructional method that is increasingly used nowadays. However, model characteristics such as gender tend to differ across videos, and the
Song, Yang; Han, Dawei; Rico-Ramirez, Miguel A.
Radar rainfall measurement errors can be considerably attributed to various sources including intricate synoptic regimes. Temperature, humidity and wind are typically acknowledged as critical meteorological factors in inducing the precipitation discrepancies aloft and on the ground. The conventional practices mainly use the radar-gauge or geostatistical techniques by direct weighted interpolation algorithms as bias correction schemes whereas rarely consider the atmospheric effects. This study aims to comprehensively quantify those meteorological elements' impacts on radar-gauge rainfall bias correction based on a deep learning approach. The deep learning approach employs deep convolutional neural networks to automatically extract three-dimensional meteorological features for target recognition based on high range resolution profiles. The complex nonlinear relationships between input and target variables can be implicitly detected by such a scheme, which is validated on the test dataset. The proposed bias correction scheme is expected to be a promising improvement in systematically minimizing the synthesized atmospheric effects on rainfall discrepancies between radar and rain gauges, which can be useful in many meteorological and hydrological applications (e.g., real-time flood forecasting) especially for regions with complex atmospheric conditions.
Mazzoni, Dominic; Wagstaff, Kiri
We propose a new active learning framework where the expert labeler is allowed to decline to label any example. This may be necessary because the true label is unknown or because the example belongs to a class that is not part of the real training problem. We show that within this framework, popular active learning algorithms (such as Simple) may perform worse than random selection because they make so many queries to the unlabelable class. We present a method by which any active learning algorithm can be modified to avoid unlabelable examples by training a second classifier to distinguish between the labelable and unlabelable classes. We also demonstrate the effectiveness of the method on two benchmark data sets and a real-world problem.
Liu, Huaping; Xiao, Wei; Zhao, Hongyan; Sun, Fuchun
System stability is a basic concept in courses on dynamic system analysis and control for undergraduate students with computer science backgrounds. Typically, this was taught using a simple simulation example of an inverted pendulum. Unfortunately, many difficult issues arise in the learning and understanding of the concepts of stability,…
Riegler, Peter; Biehl, Michael; Solla, Sara A.; Marangi, Carmela; Marinaro, Maria; Tagliaferri, Roberto
We analyse on-line learning of a linearly separable rule with a simple perceptron. Example inputs are taken from two overlapping clusters of data and the rule is defined through a teacher vector which is in general not aligned with the connection line of the cluster centers. We find that the Hebb
Full Text Available This paper proposes a novel approach for recommending social resources using learning from positive and unlabeled examples. Bookmarks submitted on social bookmarking system delicious1 and artists on online music system last.fm2 are considered as social resources. The foremost feature of this problem is that there are no labeled negative resources/examples available for learning a recommender/classifier. The memory based collaborative filtering has served as the most widely used algorithm for social resource recommendation. However, its predictions are based on some ad hoc heuristic rules and its success depends on the availability of a critical mass of users. This paper proposes model based two-step techniques to learn a classifier using positive and unlabeled examples to address personalized resource recommendations. In the first step of these techniques, naïve Bayes classifier is employed to identify reliable negative resources. In the second step, to generate effective resource recommender, classification and regression tree and least square support vector machine (LS-SVM are exercised. A direct method based on LS-SVM is also put forward to realize the recommendation task. LS-SVM is customized for learning from positive and unlabeled data. Furthermore, the impact of feature selection on our proposed techniques is also studied. Memory based collaborative filtering as well as our proposed techniques exploit usage data to generate personalized recommendations. Experimental results show that the proposed techniques outperform existing method appreciably.
Full Text Available Comparisons of the DNA sequences of metazoa show an excess of transitional over transversional substitutions. Part of this bias is due to the relatively high rate of mutation of methylated cytosines to thymine. Postmutation processes also introduce a bias, particularly selection for codon-usage bias in coding regions. It is generally assumed, however, that there is a universal bias in favour of transitions over transversions, possibly as a result of the underlying chemistry of mutation. Surprisingly, this underlying trend has been evaluated only in two types of metazoan, namely Drosophila and the Mammalia. Here, we investigate a third group, and find no such bias. We characterize the point substitution spectrum in Podisma pedestris, a grasshopper species with a very large genome. The accumulation of mutations was surveyed in two pseudogene families, nuclear mitochondrial and ribosomal DNA sequences. The cytosine-guanine (CpG dinucleotides exhibit the high transition frequencies expected of methylated sites. The transition rate at other cytosine residues is significantly lower. After accounting for this methylation effect, there is no significant difference between transition and transversion rates. These results contrast with reports from other taxa and lead us to reject the hypothesis of a universal transition/transversion bias. Instead we suggest fundamental interspecific differences in point substitution processes.
Luque, D., Vadillo, M, A., Gutiérrez-Cobo, M, J., Le Pelley, M, E. (2018). The blocking effect in associative learning involves learned biases in rapid attentional capture. Quarterly Journal of Experimental Psychology, 71, 522-544. doi: 10.1080/17470218.2016.1262435. The above article is part of the Special Issue on Associative Learning (in honour of Nick Mackintosh) and was inadvertently published in the February 2018 issue of Quarterly Journal of Experimental Psychology. After publication of the Special Issue, an online collection on Associative Learning will be created on SAGE Journals and this paper will be included in that collection. The Publisher apologises for this error.
Thorson, James T.; Kristensen, Kasper
Statistical models play an important role in fisheries science when reconciling ecological theory with available data for wild populations or experimental studies. Ecological models increasingly include both fixed and random effects, and are often estimated using maximum likelihood techniques...... configurations of an age-structured population dynamics model. This simulation experiment shows that the epsilon-method and the existing bias-correction method perform equally well in data-rich contexts, but the epsilon-method is slightly less biased in data-poor contexts. We then apply the epsilon......-method to a spatial regression model when estimating an index of population abundance, and compare results with an alternative bias-correction algorithm that involves Markov-chain Monte Carlo sampling. This example shows that the epsilon-method leads to a biologically significant difference in estimates of average...
Cheng, Zhanzhan; Zhou, Shuigeng; Wang, Yang; Liu, Hui; Guan, Jihong; Chen, Yi-Ping Phoebe
Prediction of compound-protein interactions (CPIs) is to find new compound-protein pairs where a protein is targeted by at least a compound, which is a crucial step in new drug design. Currently, a number of machine learning based methods have been developed to predict new CPIs in the literature. However, as there is not yet any publicly available set of validated negative CPIs, most existing machine learning based approaches use the unknown interactions (not validated CPIs) selected randomly as the negative examples to train classifiers for predicting new CPIs. Obviously, this is not quite reasonable and unavoidably impacts the CPI prediction performance. In this paper, we simply take the unknown CPIs as unlabeled examples, and propose a new method called PUCPI (the abbreviation of PU learning for Compound-Protein Interaction identification) that employs biased-SVM (Support Vector Machine) to predict CPIs using only positive and unlabeled examples. PU learning is a class of learning methods that leans from positive and unlabeled (PU) samples. To the best of our knowledge, this is the first work that identifies CPIs using only positive and unlabeled examples. We first collect known CPIs as positive examples and then randomly select compound-protein pairs not in the positive set as unlabeled examples. For each CPI/compound-protein pair, we extract protein domains as protein features and compound substructures as chemical features, then take the tensor product of the corresponding compound features and protein features as the feature vector of the CPI/compound-protein pair. After that, biased-SVM is employed to train classifiers on different datasets of CPIs and compound-protein pairs. Experiments over various datasets show that our method outperforms six typical classifiers, including random forest, L1- and L2-regularized logistic regression, naive Bayes, SVM and k-nearest neighbor (kNN), and three types of existing CPI prediction models. Source code, datasets and
Dijkstra, A.F.; Verdonk, P.; Lagro-Janssen, A.L.M.
OBJECTIVES: This study aimed to review the availability and accessibility of gender-specific knowledge in current medical textbooks used in Dutch medical schools. Medicine has been criticised as being gender-biased by assuming male and female bodies to be generally the same. The authors wondered
Dijkstra, A.F.; Verdonk, P.; Lagro-Janssen, A.L.M.
OBJECTIVES: This study aimed to review the availability and accessibility of gender-specific knowledge in current medical textbooks used in Dutch medical schools. Medicine has been criticised as being gender-biased by assuming male and female bodies to be generally the same. The authors wondered
Mouratidou, Katerina; Barkoukis, Vassilis
Gender biases have often been observed in physical education (PE) classes, as many teachers adopt a male-biased perspective in teaching and learning. This might affect their evaluation of students' behavior and may lead students to accept and reproduce gender biases in other social contexts. The aim of this study was to examine whether PE teachers…
Guo, Jian-Peng; Yang, Ling-Yan; Ding, Yi
Researchers have consistently demonstrated that multiple examples are better than one example in facilitating learning because the comparison evoked by multiple examples supports learning and transfer. However, research outcomes are unclear regarding the effects of example variability and prior knowledge on learning from comparing multiple…
Brinson, Jesse A.
This article encourages supervisors, in general, and counsellor supervisors, in particular, to engage in reflective learning as a way to identify their cultural biases. Awareness of counsellor bias has been addressed by ethical standards outlined for professional helpers. This article presents reflective learning as a potentially useful strategy…
Broeck, C. van den
The problem of how one can learn from examples is illustrated on the case of a student perception trained by the Hebb rule on examples generated by a teacher perception. Two basic quantities are calculated: the training error and the generalization error. The obtained results are found to be typical. Other training rules are discussed. For the case of an Ising student with an Ising teacher, the existence of a first order phase transition is shown. Special effects such as dilution, queries, rejection, etc. are discussed and some results for multilayer networks are reviewed. In particular, the properties of a self-similar committee machine are derived. Finally, we discuss the statistic of generalization, with a review of the Hoeffding inequality, the Dvoretzky Kiefer Wolfowitz theorem and the Vapnik Chervonenkis theorem. (author). 29 refs, 6 figs
Hanson, Catherine; Caglar, Leyla Roskan; Hanson, Stephen José
Category learning performance is influenced by both the nature of the category's structure and the way category features are processed during learning. Shepard (1964, 1987) showed that stimuli can have structures with features that are statistically uncorrelated (separable) or statistically correlated (integral) within categories. Humans find it much easier to learn categories having separable features, especially when attention to only a subset of relevant features is required, and harder to learn categories having integral features, which require consideration of all of the available features and integration of all the relevant category features satisfying the category rule (Garner, 1974). In contrast to humans, a single hidden layer backpropagation (BP) neural network has been shown to learn both separable and integral categories equally easily, independent of the category rule (Kruschke, 1993). This "failure" to replicate human category performance appeared to be strong evidence that connectionist networks were incapable of modeling human attentional bias. We tested the presumed limitations of attentional bias in networks in two ways: (1) by having networks learn categories with exemplars that have high feature complexity in contrast to the low dimensional stimuli previously used, and (2) by investigating whether a Deep Learning (DL) network, which has demonstrated humanlike performance in many different kinds of tasks (language translation, autonomous driving, etc.), would display human-like attentional bias during category learning. We were able to show a number of interesting results. First, we replicated the failure of BP to differentially process integral and separable category structures when low dimensional stimuli are used (Garner, 1974; Kruschke, 1993). Second, we show that using the same low dimensional stimuli, Deep Learning (DL), unlike BP but similar to humans, learns separable category structures more quickly than integral category structures
Full Text Available Category learning performance is influenced by both the nature of the category's structure and the way category features are processed during learning. Shepard (1964, 1987 showed that stimuli can have structures with features that are statistically uncorrelated (separable or statistically correlated (integral within categories. Humans find it much easier to learn categories having separable features, especially when attention to only a subset of relevant features is required, and harder to learn categories having integral features, which require consideration of all of the available features and integration of all the relevant category features satisfying the category rule (Garner, 1974. In contrast to humans, a single hidden layer backpropagation (BP neural network has been shown to learn both separable and integral categories equally easily, independent of the category rule (Kruschke, 1993. This “failure” to replicate human category performance appeared to be strong evidence that connectionist networks were incapable of modeling human attentional bias. We tested the presumed limitations of attentional bias in networks in two ways: (1 by having networks learn categories with exemplars that have high feature complexity in contrast to the low dimensional stimuli previously used, and (2 by investigating whether a Deep Learning (DL network, which has demonstrated humanlike performance in many different kinds of tasks (language translation, autonomous driving, etc., would display human-like attentional bias during category learning. We were able to show a number of interesting results. First, we replicated the failure of BP to differentially process integral and separable category structures when low dimensional stimuli are used (Garner, 1974; Kruschke, 1993. Second, we show that using the same low dimensional stimuli, Deep Learning (DL, unlike BP but similar to humans, learns separable category structures more quickly than integral category
The biases of individual language learners act to determine the learnability and cultural stability of languages: learners come to the language learning task with biases which make certain linguistic systems easier to acquire than others. These biases are repeatedly applied during the process of language transmission, and consequently should effect the types of languages we see in human populations. Understanding the cultural evolutionary consequences of particular learning biases is therefore central to understanding the link between language learning in individuals and language universals, common structural properties shared by all the world’s languages. This paper reviews a range of models and experimental studies which show that weak biases in individual learners can have strong effects on the structure of socially learned systems such as language, suggesting that strong universal tendencies in language structure do not require us to postulate strong underlying biases or constraints on language learning. Furthermore, understanding the relationship between learner biases and language design has implications for theories of the evolution of those learning biases: models of gene-culture coevolution suggest that, in situations where a cultural dynamic mediates between properties of individual learners and properties of language in this way, biological evolution is unlikely to lead to the emergence of strong constraints on learning.
Retnowati, Endah; Ayres, Paul; Sweller, John
Worked examples and collaborative learning have both been shown to facilitate learning. However, the testing of both strategies almost exclusively has been conducted independently of each other. The main aim of the current study was to examine interactions between these 2 strategies. Two experiments (N = 182 and N = 122) were conducted with…
Swann, Ellen T; Fernandez, Michael; Coote, Michelle L; Barnard, Amanda S
Current benchmarking methods in quantum chemistry rely on databases that are built using a chemist's intuition. It is not fully understood how diverse or representative these databases truly are. Multivariate statistical techniques like archetypal analysis and K-means clustering have previously been used to summarize large sets of nanoparticles however molecules are more diverse and not as easily characterized by descriptors. In this work, we compare three sets of descriptors based on the one-, two-, and three-dimensional structure of a molecule. Using data from the NIST Computational Chemistry Comparison and Benchmark Database and machine learning techniques, we demonstrate the functional relationship between these structural descriptors and the electronic energy of molecules. Archetypes and prototypes found with topological or Coulomb matrix descriptors can be used to identify smaller, statistically significant test sets that better capture the diversity of chemical space. We apply this same method to find a diverse subset of organic molecules to demonstrate how the methods can easily be reapplied to individual research projects. Finally, we use our bias-free test sets to assess the performance of density functional theory and quantum Monte Carlo methods.
Lefebvre, Germain; Blakemore, Sarah-Jayne
Previous studies suggest that factual learning, that is, learning from obtained outcomes, is biased, such that participants preferentially take into account positive, as compared to negative, prediction errors. However, whether or not the prediction error valence also affects counterfactual learning, that is, learning from forgone outcomes, is unknown. To address this question, we analysed the performance of two groups of participants on reinforcement learning tasks using a computational model that was adapted to test if prediction error valence influences learning. We carried out two experiments: in the factual learning experiment, participants learned from partial feedback (i.e., the outcome of the chosen option only); in the counterfactual learning experiment, participants learned from complete feedback information (i.e., the outcomes of both the chosen and unchosen option were displayed). In the factual learning experiment, we replicated previous findings of a valence-induced bias, whereby participants learned preferentially from positive, relative to negative, prediction errors. In contrast, for counterfactual learning, we found the opposite valence-induced bias: negative prediction errors were preferentially taken into account, relative to positive ones. When considering valence-induced bias in the context of both factual and counterfactual learning, it appears that people tend to preferentially take into account information that confirms their current choice. PMID:28800597
Palminteri, Stefano; Lefebvre, Germain; Kilford, Emma J; Blakemore, Sarah-Jayne
Previous studies suggest that factual learning, that is, learning from obtained outcomes, is biased, such that participants preferentially take into account positive, as compared to negative, prediction errors. However, whether or not the prediction error valence also affects counterfactual learning, that is, learning from forgone outcomes, is unknown. To address this question, we analysed the performance of two groups of participants on reinforcement learning tasks using a computational model that was adapted to test if prediction error valence influences learning. We carried out two experiments: in the factual learning experiment, participants learned from partial feedback (i.e., the outcome of the chosen option only); in the counterfactual learning experiment, participants learned from complete feedback information (i.e., the outcomes of both the chosen and unchosen option were displayed). In the factual learning experiment, we replicated previous findings of a valence-induced bias, whereby participants learned preferentially from positive, relative to negative, prediction errors. In contrast, for counterfactual learning, we found the opposite valence-induced bias: negative prediction errors were preferentially taken into account, relative to positive ones. When considering valence-induced bias in the context of both factual and counterfactual learning, it appears that people tend to preferentially take into account information that confirms their current choice.
Houssami, Nehmat; Ciatto, Stefano
This work highlights concepts on the potential for design-related factors to bias estimates of test accuracy in comparative imaging research. We chose two design factors, selection of eligible subjects and the reference standard, to examine the effect of design limitations on estimates of accuracy. Estimates of sensitivity in a study of the comparative accuracy of mammography and ultrasound differed according to how subjects were selected. Comparison of a new imaging test with an existing test should distinguish whether the new test is to be used as a replacement for, or as an adjunct to, the conventional test, to guide the method for subject selection. Quality of the reference standard, examined in a meta-analysis of preoperative breast MRI, varied across studies and was associated with estimates of incremental accuracy. Potential solutions to deal with the reference standard are outlined where an ideal reference standard may not be available in all subjects. These examples of breast imaging research demonstrate that design-related bias, when comparing a new imaging test with a conventional imaging test, may bias accuracy in a direction that favours the new test by overestimating the accuracy of the new test or by underestimating that of the conventional test. (orig.)
Reynolds, Gemma; Field, Andy P; Askew, Chris
Research with children has shown that vicarious learning can result in changes to 2 of Lang's (1968) 3 anxiety response systems: subjective report and behavioral avoidance. The current study extended this research by exploring the effect of vicarious learning on physiological responses (Lang's final response system) and attentional bias. The study used Askew and Field's (2007) vicarious learning procedure and demonstrated fear-related increases in children's cognitive, behavioral, and physiological responses. Cognitive and behavioral changes were retested 1 week and 1 month later, and remained elevated. In addition, a visual search task demonstrated that fear-related vicarious learning creates an attentional bias for novel animals, which is moderated by increases in fear beliefs during learning. The findings demonstrate that vicarious learning leads to lasting changes in all 3 of Lang's anxiety response systems and is sufficient to create attentional bias to threat in children. PsycINFO Database Record (c) 2014 APA, all rights reserved.
J.-O. Dyer (Joseph-Omer); A. Hudon (Anne); K. Montpetit-Tourangeau (Katherine); B. Charlin (Bernard); S. Mamede (Silvia); T.A.J.M. van Gog (Tamara)
textabstractBACKGROUND: Example-based learning using worked examples can foster clinical reasoning. Worked examples are instructional tools that learners can use to study the steps needed to solve a problem. Studying worked examples paired with completion examples promotes acquisition of
Ariel, Robert; Hines, Jarrod C.; Hertzog, Christopher
People estimate minimal changes in learning when making predictions of learning (POLs) for future study opportunities despite later showing increased performance and an awareness of that increase (Kornell & Bjork, 2009). This phenomenon is conceptualized as a stability bias in judgments about learning. We investigated the malleability of this effect, and whether it reflected people’s underlying beliefs about learning. We manipulated prediction framing to emphasize the role of testing vs. studying on memory and directly measured beliefs about multi-trial study effects on learning by having participants construct predicted learning curves before and after the experiment. Mean POLs were more sensitive to the number of study-test opportunities when performance was framed in terms of study benefits rather than testing benefits and POLs reflected pre-existing beliefs about learning. The stability bias is partially due to framing and reflects discounted beliefs about learning benefits rather than inherent belief in the stability of performance. PMID:25067885
Anderson, Lorin W.
The purpose of the study was to examine test bias and the "non-effects" of schooling. Teachers were given a list of words selected from standardized vocabulary tests and asked to indicate the words they had taught. The words were classified by the grade level at which they were first introduced. Ninety-five third-grade students in four schools…
Koban, Leonie; Schneider, Rebecca; Ashar, Yoni K; Andrews-Hanna, Jessica R; Landy, Lauren; Moscovitch, David A; Wager, Tor D; Arch, Joanna J
People learn about their self from social information, and recent work suggests that healthy adults show a positive bias for learning self-related information. In contrast, social anxiety disorder (SAD) is characterized by a negative view of the self, yet what causes and maintains this negative self-view is not well understood. Here the authors use a novel experimental paradigm and computational model to test the hypothesis that biased social learning regarding self-evaluation and self-feelings represents a core feature that distinguishes adults with SAD from healthy controls. Twenty-one adults with SAD and 35 healthy controls (HCs) performed a speech in front of 3 judges. They subsequently evaluated themselves and received performance feedback from the judges and then rated how they felt about themselves and the judges. Affective updating (i.e., change in feelings about the self over time, in response to feedback from the judges) was modeled using an adapted Rescorla-Wagner learning model. HCs demonstrated a positivity bias in affective updating, which was absent in SAD. Further, self-performance ratings revealed group differences in learning from positive feedback-a difference that endured at an average of 1 year follow up. These findings demonstrate the presence and long-term endurance of positively biased social learning about the self among healthy adults, a bias that is absent or reversed among socially anxious adults. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
According to constructivist theory of learning, new knowledge is learned on the basis of what is already known by learners. Thus for an emerging and transformative technology such as Linked Data to be learned, the technology must be made relevant for learners and must be compatible with their skillset. Designing and developing Linked Data…
Gisabella, Barbara; Farah, Shadia; Peng, Xiaoyu; Burgos-Robles, Anthony Noel; Lim, Seh Hong; Goosens, Ki Ann
Prolonged stress exposure is a risk factor for developing posttraumatic stress disorder, a disorder characterized by the ?over-encoding' of a traumatic experience. A potential mechanism by which this occurs is through upregulation of growth hormone (GH) in the amygdala. Here we test the hypotheses that GH promotes the over-encoding of fearful memories by increasing the number of neurons activated during memory encoding and biasing the allocation of neuronal activation, one aspect of the proce...
Reynolds, G; Field, AP; Askew, C
Research with children has shown that vicarious learning can result in changes to 2 of Lang's (1968) 3 anxiety response systems: subjective report and behavioral avoidance. The current study extended this research by exploring the effect of vicarious learning on physiological responses (Lang's final response system) and attentional bias. The study used Askew and Field's (2007) vicarious learning procedure and demonstrated fear-related increases in children's cognitive, behavioral, and physiol...
Booth, Julie L.; Lange, Karin E.; Koedinger, Kenneth R.; Newton, Kristie J.
In a series of two "in vivo" experiments, we examine whether correct and incorrect examples with prompts for self-explanation can be effective for improving students' conceptual understanding and procedural skill in Algebra when combined with guided practice. In Experiment 1, students working with the Algebra I Cognitive Tutor were randomly…
Zamary, Amanda; Rawson, Katherine A.
Students in many courses are commonly expected to learn declarative concepts, which are abstract concepts denoted by key terms with short definitions that can be applied to a variety of scenarios as reported by Rawson et al. ("Educational Psychology Review" 27:483-504, 2015). Given that declarative concepts are common and foundational in…
Gisabella, B; Farah, S; Peng, X; Burgos-Robles, A; Lim, S H; Goosens, K A
Prolonged stress exposure is a risk factor for developing posttraumatic stress disorder, a disorder characterized by the 'over-encoding' of a traumatic experience. A potential mechanism by which this occurs is through upregulation of growth hormone (GH) in the amygdala. Here we test the hypotheses that GH promotes the over-encoding of fearful memories by increasing the number of neurons activated during memory encoding and biasing the allocation of neuronal activation, one aspect of the process by which neurons compete to encode memories, to favor neurons that have stronger inputs. Viral overexpression of GH in the amygdala increased the number of amygdala cells activated by fear memory formation. GH-overexpressing cells were especially biased to express the immediate early gene c-Fos after fear conditioning, revealing strong autocrine actions of GH in the amygdala. In addition, we observed dramatically enhanced dendritic spine density in GH-overexpressing neurons. These data elucidate a previously unrecognized autocrine role for GH in the regulation of amygdala neuron function and identify specific mechanisms by which chronic stress, by enhancing GH in the amygdala, may predispose an individual to excessive fear memory formation.
Marangi, Carmela; Solla, Sara A.; Biehl, Michael; Riegler, Peter; Marinaro, Maria; Tagliaferri, Roberto
We analyze the generalization ability of a simple perceptron acting on a structured input distribution for the simple case of two clusters of input data and a linearly separable rule. The generalization ability computed for three learning scenarios: maximal stability, Gibbs, and optimal learning, is
McLaren, Bruce M.; van Gog, Tamara; Ganoe, Craig; Yaron, David; Karabinos, Michael
The ‘assistance dilemma’, an important issue in the Learning Sciences, is concerned with how much guidance or assistance should be provided to help students learn. A recent study comparing three high-assistance approaches (worked examples, tutored problems, and erroneous examples) and one
Field, Zoë C; Field, Andy P
Cognitive models of vulnerability to anxiety propose that information processing biases such as interpretation bias play a part in the etiology and maintenance of anxiety disorders. However, at present little is known about the role of memory in information processing accounts of child anxiety. The current study investigates the relationships between interpretation biases, memory and fear responses when learning about new stimuli. Children (aged 8-11 years) were presented with ambiguous information regarding a novel animal, and their fear, interpretation bias, and memory for the information was measured. The main findings were: (1) trait anxiety and interpretation bias significantly predicted acquired fear; (2) interpretation bias did not significantly mediate the relationship between trait anxiety and acquired fear; (3) interpretation bias appeared to be a more important predictor of acquired fear than trait anxiety per se; and (4) the relationship between interpretation bias and acquired fear was not mediated by the number of negative memories but was mediated by the number of positive and false-positive memories. The findings suggest that information processing models of child anxiety need to explain the role of positive memory in the formation of fear responses.
Huang, Sheng-Jun; Jin, Rong; Zhou, Zhi-Hua
Active learning reduces the labeling cost by iteratively selecting the most valuable data to query their labels. It has attracted a lot of interests given the abundance of unlabeled data and the high cost of labeling. Most active learning approaches select either informative or representative unlabeled instances to query their labels, which could significantly limit their performance. Although several active learning algorithms were proposed to combine the two query selection criteria, they are usually ad hoc in finding unlabeled instances that are both informative and representative. We address this limitation by developing a principled approach, termed QUIRE, based on the min-max view of active learning. The proposed approach provides a systematic way for measuring and combining the informativeness and representativeness of an unlabeled instance. Further, by incorporating the correlation among labels, we extend the QUIRE approach to multi-label learning by actively querying instance-label pairs. Extensive experimental results show that the proposed QUIRE approach outperforms several state-of-the-art active learning approaches in both single-label and multi-label learning.
Dec 1, 2010 ... Case studies show how, through joint efforts with researchers and other actors, local ... address and learn from challenges in managing natural resources. ... health, and health systems research relevant to the emerging crisis.
Full Text Available In health care institutions aiming healthy society by the way protecting and promoting human health, reaching information has a vital importance. This descriptive research purposed an evaluation of organizational learning capability of 396 employees working in Gülhane Military Medical Academy Hospital. A questionnaire including socio-demographic characteristics was used along with Organizational Learning Capability scale designed by Ricardo CHIVA and His Friends. Data acquired was analyzed with SPSS 15.0 program. Participants’ Organizational Learning Capability and its subscales means were assessed in terms of their sociodemographic characteristics. Assessing participants’ answers in terms of 5 subscales which are experimentation, risk taking, interaction with the external environment, dialogue and participatory decision-making; for education level and professional groups, statistical significant differences was found between Organizational Learning Capability and its subscales means.
Atkisson, Curtis; O'Brien, Michael J; Mesoudi, Alex
Social learning (learning from others) is evolutionarily adaptive under a wide range of conditions and is a long-standing area of interest across the social and biological sciences. One social-learning mechanism derived from cultural evolutionary theory is prestige bias, which allows a learner in a novel environment to quickly and inexpensively gather information as to the potentially best teachers, thus maximizing his or her chances of acquiring adaptive behavior. Learners provide deference to high-status individuals in order to ingratiate themselves with, and gain extended exposure to, that individual. We examined prestige-biased social transmission in a laboratory experiment in which participants designed arrowheads and attempted to maximize hunting success, measured in caloric return. Our main findings are that (1) participants preferentially learned from prestigious models (defined as those models at whom others spent longer times looking), and (2) prestige information and success-related information were used to the same degree, even though the former was less useful in this experiment than the latter. We also found that (3) participants were most likely to use social learning over individual (asocial) learning when they were performing poorly, in line with previous experiments, and (4) prestige information was not used more often following environmental shifts, contrary to predictions. These results support previous discussions of the key role that prestige-biased transmission plays in social learning.
Dyer, Joseph-Omer; Hudon, Anne; Montpetit-Tourangeau, Katherine; Charlin, Bernard; Mamede, Sílvia; van Gog, Tamara
Example-based learning using worked examples can foster clinical reasoning. Worked examples are instructional tools that learners can use to study the steps needed to solve a problem. Studying worked examples paired with completion examples promotes acquisition of problem-solving skills more than studying worked examples alone. Completion examples are worked examples in which some of the solution steps remain unsolved for learners to complete. Providing learners engaged in example-based learning with self-explanation prompts has been shown to foster increased meaningful learning compared to providing no self-explanation prompts. Concept mapping and concept map study are other instructional activities known to promote meaningful learning. This study compares the effects of self-explaining, completing a concept map and studying a concept map on conceptual knowledge and problem-solving skills among novice learners engaged in example-based learning. Ninety-one physiotherapy students were randomized into three conditions. They performed a pre-test and a post-test to evaluate their gains in conceptual knowledge and problem-solving skills (transfer performance) in intervention selection. They studied three pairs of worked/completion examples in a digital learning environment. Worked examples consisted of a written reasoning process for selecting an optimal physiotherapy intervention for a patient. The completion examples were partially worked out, with the last few problem-solving steps left blank for students to complete. The students then had to engage in additional self-explanation, concept map completion or model concept map study in order to synthesize and deepen their knowledge of the key concepts and problem-solving steps. Pre-test performance did not differ among conditions. Post-test conceptual knowledge was higher (P example and completion example strategies to foster intervention selection.
J.-O. Dyer (Joseph-Omer); A. Hudon (Anne); K. Montpetit-Tourangeau (Katherine); B. Charlin (Bernard); S. Mamede (Silvia); T.A.J.M. van Gog (Tamara)
textabstractBackground: Example-based learning using worked examples can foster clinical reasoning. Worked examples are instructional tools that learners can use to study the steps needed to solve a problem. Studying worked examples paired with completion examples promotes acquisition of
Burgos, Daniel; Hummel, Hans; Tattersall, Colin; Brouns, Francis; Koper, Rob
Burgos, D., Hummel, H. G. K., Tattersall, C., Brouns, F., & Koper, R. (2009). Design Guidelines for Collaboration and Participation with Examples from the LN4LD (Learning Network for Learning Design). In L. Lockyer, S. Bennett, S. Agostinho & B. Harper (Eds.), Handbook of Research on Learning Design
Ajideh, Parviz; Yaghoubi-Notash, Massoud; Khalili, Abdolreza
The present study investigated the contribution of the EFL students' learning strategies to the explanation of the variance in their results on language tests. More specifically, it examined the role of these strategies as bias factors in the results of English cloze tests. Based on this aim, first, 158 intermediate EFL learners were selected from…
Bouma, H.; Eendebak, P.T.; Schutte, K.; Azzopardi, G.; Burghouts, G.J.
Object recognition and localization are important to automatically interpret video and allow better querying on its content. We propose a method for object localization that learns incrementally and addresses four key aspects. Firstly, we show that for certain applications, recognition is feasible
Brugemann, V.P.; Brummelen, van E.H.; Melkert, J.A.; Kamp, A.; Saunders-Smits, G.N.; Reith, B.A.; Zandbergen, B.T.C.; Graaf, de E.; Saunders-Smits, G.N.; Nieweg, M.R.
This paper is a showcase for an on-going active learning capstone design project in the BSe. programme at the Faculty of Aerospace Engineering at Delft University of Technology. In multi-disciplinary teams supervised by tutors from different backgrounds students work towards an Aerospace (related)
Full Text Available Point of entry to the Ecole Polytechnique Fédérale de Lausanne (EPFL, the Learning Center will be a place to learn, to obtain information, and to live. Replacing and improving the old main library, this new building will gradually assimilate all EPFL department libraries collections and services, as they are integrated into a global information system. Conceived as the place for those who are learning, mainly students, who have no personal working area on the campus, it is designed to adapt itself to the ‘seasons’ of academic life throughout the year (flexibility and modularity of rooms, extended opening hours during exam periods. It will take into account group working habits (silence vs. noise, changes in the rhythm of student life (meals, working alone, discussions, etc., and other environmental factors. Of course the needs of EPFL staff and alumni, local industry and citizens have also been carefully considered in the design. By offering a multitude of community functions, such as a bookshop, cafeteria and restaurant services, and rooms for relaxation and discussion, the Learning Center will link the campus to the city. Areas devoted to exhibition and debate will also be included, enforcing its role as an interactive science showcase, in particular for those technologies related to the research and teaching of the EPFL. The presentation described the process and steps towards the actual realisation of such a vital public space: from the programme definition to the collaboration with the bureau of architects (SAANA, Tokyo who won the project competition, the speakers showed what are the challenges and lessons already taken when working on this major piece of architecture, indeed the heart of the transformation of the technical school build in the 1970s into a real 2000s campus.
The very suitable topic for independent student activities is the investigation of factors influencing an oscillation period of the mathematic pendulum. The article describes the experience from particular lessons. Students themselves were discovering new facts. They learned about the physics practice of acquiring new knowledge. The knowledge quality and retention was compared between the experimental classes and classes with a traditional instruction one year after the experiment.
Sabine van der Ham
Full Text Available When learning language, humans have a tendency to produce more extreme distributions of speech sounds than those observed most frequently: In rapid, casual speech, vowel sounds are centralized, yet cross-linguistically, peripheral vowels occur almost universally. We investigate whether adults’ generalization behavior reveals selective pressure for communication when they learn skewed distributions of speech-like sounds from a continuous signal space. The domain-specific hypothesis predicts that the emergence of sound categories is driven by a cognitive bias to make these categories maximally distinct, resulting in more skewed distributions in participants’ reproductions. However, our participants showed more centered distributions, which goes against this hypothesis, indicating that there are no strong innate linguistic biases that affect learning these speech-like sounds. The centralization behavior can be explained by a lack of communicative pressure to maintain categories.
Woud, Marcella L; Blackwell, Simon E; Steudte-Schmiedgen, Susann; Browning, Michael; Holmes, Emily A; Harmer, Catherine J; Margraf, Jürgen; Reinecke, Andrea
The partial N-methyl-D-aspartate receptor agonist d-cycloserine may enhance psychological therapies. However, its exact mechanism of action is still being investigated. Cognitive bias modification techniques allow isolation of cognitive processes and thus investigation of how they may be affected by d-cycloserine. We used a cognitive bias modification paradigm targeting appraisals of a stressful event, Cognitive Bias Modification-Appraisal, to investigate whether d-cycloserine enhanced the modification of appraisal, and whether it caused greater reduction in indices of psychopathology. Participants received either 250 mg of d-cycloserine ( n=19) or placebo ( n=19). As a stressor task, participants recalled a negative life event, followed by positive Cognitive Bias Modification-Appraisal training. Before and after Cognitive Bias Modification-Appraisal, appraisals and indices of psychopathology related to the stressor were assessed. Cognitive Bias Modification-Appraisal successfully modified appraisals, but d-cycloserine did not affect appraisals post-training. There were no post-training group differences in frequency of intrusions. Interestingly, d-cycloserine led to a greater reduction in distress and impact on state mood from recalling the event, and lower distress post-training was associated with fewer intrusions. Therefore, d-cycloserine may affect emotional reactivity to recalling a negative event when combined with induction of a positive appraisal style, but via a mechanism other than enhanced learning of the appraisal style.
The ID3 algorithm for inductive learning was tested using preclassified material for patients suspected to have a thyroid illness. Classification followed a rule-based expert system for the diagnosis of thyroid function. Thus, the knowledge to be learned was limited to the rules existing in the knowledge base of that expert system. The learning capability of the ID3 algorithm was tested with an unselected learning material (with some inherent missing data) and with a selected learning material (no missing data). The selected learning material was a subgroup which formed a part of the unselected learning material. When the number of learning cases was increased, the accuracy of the program improved. When the learning material was large enough, an increase in the learning material did not improve the results further. A better learning result was achieved with the selected learning material not including missing data as compared to unselected learning material. With this material we demonstrate a weakness in the ID3 algorithm: it can not find available information from good example cases if we add poor examples to the data.
T.A.J.M. van Gog (Tamara); N. Rummel (Nikol)
textabstractExample-based learning has been studied from different perspectives. Cognitive research has mainly focused on worked examples, which typically provide students with a written worked-out didactical solution to a problem to study. Social-cognitive research has mostly focused on modeling
Schworm, Silke; Renkl, Alexander
Learning with self-explaining examples is an effective method in well-structured domains. The authors analyzed this method in teaching the complex skill of argumentation, experimentally comparing 4 conditions (N = 71 student teachers) that differed with respect to whether and how the processing of the examples was supported by self-explanation…
Renkl, Alexander; Hilbert, Tatjana; Schworm, Silke
One classical instructional effect of cognitive load theory (CLT) is the worked-example effect. Although the vast majority of studies have focused on well-structured and algorithmic sub-domains of mathematics or physics, more recent studies have also analyzed learning with examples from complex domains in which only heuristic solution strategies…
Van Gog, Tamara; Verveer, Ilse; Verveer, Lise
Video modeling examples in which a human(-like) model shows learners how to perform a task are increasingly used in education, as they have become very easy to create and distribute in e-learning environments. However, little is known about design guidelines to optimize learning from video modeling
Mashhood Ahmed Sheikh
Full Text Available The mechanisms by which childhood socioeconomic status (CSES affects adult mental health, general health, and well-being are not clear. Moreover, the analytical assumptions employed when assessing mediation in social and psychiatric epidemiology are rarely explained. The aim of this paper was to explain the intermediate confounding assumption, and to quantify differential recall bias in the association between CSES, childhood abuse, and mental health (SCL-10, general health (EQ-5D, and subjective well-being (SWLS. Furthermore, we assessed the mediating role of psychological and physical abuse in the association between CSES and mental health, general health, and well-being; and the influence of differential recall bias in the estimation of total effects, direct effects, and proportion of mediated effects. The assumptions employed when assessing mediation are explained with reference to a causal diagram. Poisson regression models (relative risk, RR and 99% CI were used to assess the association between CSES and psychological and physical abuse in childhood. Mediation analysis (difference method was used to assess the indirect effect of CSES (through psychological and physical abuse in childhood on mental health, general health, and well-being. Psychological abuse and physical abuse mediated the association between CSES and adult mental health, general health, and well-being (6-16% among men and 7-14% among women, p<0.001. The results suggest that up to 27% of the association between CSES and childhood abuse, 23% of the association between childhood abuse, and mental health, general health, and well-being, and 44% of the association between CSES and mental health, general health, and well-being is driven by differential recall bias. Assessing mediation with cross-sectional data (exposure, mediator, and outcome measured at the same time showed that the total effects and direct effects were vastly overestimated (biased upwards. Consequently, the
Guo, Jian-Peng; Yang, Ling-Yan; Ding, Yi
Researchers have consistently demonstrated that studying multiple examples is more effective than studying one example because comparing multiple examples can promote schema construction and facilitate discernment of critical aspects. Teachers, however, are usually absent from those self-led text-based studies. In this experimental study, a learning study approach based on variation theory was adopted to examine the effectiveness of teachers' different ways of designing multiple examples in helping students learn a physics principle. Three hundred and fifty-one tenth-grade students learned to distinguish action-reaction from equilibrium (a) by comparing examples that varied critical aspects first separately and then simultaneously, or (b) by comparing examples that separately varied critical aspects only. Results showed that students with average academic attainment benefited more from comparing examples in the first condition. Students with higher academic attainment learned equally within both conditions. This finding supports the advantage of simultaneous variation. The characteristics of students and instructional support should be taken into account when considering the effectiveness of patterns of variation.
Full Text Available The article is devoted to the contribution of foreign language learning to stimulating students’ life skills at non-linguistic higher institutions. In the article, the author considers the possibilities of motivating students to exercise life skills in the process of foreign language instruction. The author analyses the cooperative learning technology as a means that enables students to be involved into interaction with one another as well as it develops their team-building skills to successfully cooperate and communicate with each other. The author describes different forms of cooperative leaning, which give students an opportunity to mutually enrich and complement each other’s skills in foreign language learning. The author argues that cooperative learning technology stimulates the students’ existent life skills and makes them work in the process of professionally-biased instruction of a foreign language.
Touzet, C.; Santos, J.M.
The main paradigm in sub-symbolic learning robot domain is the reinforcement learning method. Various techniques have been developed to deal with the memorization/generalization problem, demonstrating the superior ability of artificial neural network implementations. In this paper, the authors address the issue of designing the reinforcement so as to optimize the exploration part of the learning. They also present and summarize works relative to the use of bias intended to achieve the effective synthesis of the desired behavior. Demonstrative experiments involving a self-organizing map implementation of the Q-learning and real mobile robots (Nomad 200 and Khepera) in a task of obstacle avoidance behavior synthesis are described. 3 figs., 5 tabs
Research with children has shown that vicarious learning can result in changes to 2 of Lang’s (1968) 3 anxiety response systems: subjective report and behavioral avoidance. The current study extended this research by exploring the effect of vicarious learning on physiological responses (Lang’s final response system) and attentional bias. The study used Askew and Field’s (2007) vicarious learning procedure and demonstrated fear-related increases in children’s cognitive, behavioral, and physiological responses. Cognitive and behavioral changes were retested 1 week and 1 month later, and remained elevated. In addition, a visual search task demonstrated that fear-related vicarious learning creates an attentional bias for novel animals, which is moderated by increases in fear beliefs during learning. The findings demonstrate that vicarious learning leads to lasting changes in all 3 of Lang’s anxiety response systems and is sufficient to create attentional bias to threat in children. PMID:25151521
Ding, Ying; Tang, Shaowu; Liao, Serena G; Jia, Jia; Oesterreich, Steffi; Lin, Yan; Tseng, George C
Supervised machine learning is commonly applied in genomic research to construct a classifier from the training data that is generalizable to predict independent testing data. When test datasets are not available, cross-validation is commonly used to estimate the error rate. Many machine learning methods are available, and it is well known that no universally best method exists in general. It has been a common practice to apply many machine learning methods and report the method that produces the smallest cross-validation error rate. Theoretically, such a procedure produces a selection bias. Consequently, many clinical studies with moderate sample sizes (e.g. n = 30-60) risk reporting a falsely small cross-validation error rate that could not be validated later in independent cohorts. In this article, we illustrated the probabilistic framework of the problem and explored the statistical and asymptotic properties. We proposed a new bias correction method based on learning curve fitting by inverse power law (IPL) and compared it with three existing methods: nested cross-validation, weighted mean correction and Tibshirani-Tibshirani procedure. All methods were compared in simulation datasets, five moderate size real datasets and two large breast cancer datasets. The result showed that IPL outperforms the other methods in bias correction with smaller variance, and it has an additional advantage to extrapolate error estimates for larger sample sizes, a practical feature to recommend whether more samples should be recruited to improve the classifier and accuracy. An R package 'MLbias' and all source files are publicly available. tsenglab.biostat.pitt.edu/software.htm. email@example.com Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: firstname.lastname@example.org.
Our aim is to ensure individualized learning that is fun, inspiring and innovative. We believe that when you enjoy, your brain will open up and learning will be easier and more effective. The methods use a non-linear learning environment based on self-contained learning objects which are pieced t...
Button, Katherine S; Browning, Michael; Munafò, Marcus R; Lewis, Glyn
Fears of negative evaluation characterise social anxiety, and preferential processing of fear-relevant information is implicated in maintaining symptoms. Little is known, however, about the relationship between social anxiety and the process of inferring negative evaluation. The ability to use social information to learn what others think about one, referred to here as self-referential learning, is fundamental for effective social interaction. The aim of this research was to examine whether social anxiety is associated with self-referential learning. 102 Females with either high (n = 52) or low (n = 50) self-reported social anxiety completed a novel probabilistic social learning task. Using trial and error, the task required participants to learn two self-referential rules, 'I am liked' and 'I am disliked'. Participants across the sample were better at learning the positive rule 'I am liked' than the negative rule 'I am disliked', β = -6.4, 95% CI [-8.0, -4.7], p learning positive self-referential information was strongest in the lowest socially anxious and was abolished in the most symptomatic participants. Relative to the low group, the high anxiety group were better at learning they were disliked and worse at learning they were liked, social anxiety by rule interaction β = 3.6; 95% CI [+0.3, +7.0], p = 0.03. The specificity of the results to self-referential processing requires further research. Healthy individuals show a robust preference for learning that they are liked relative to disliked. This positive self-referential bias is reduced in social anxiety in a way that would be expected to exacerbate anxiety symptoms. Copyright © 2012 Elsevier Ltd. All rights reserved.
Jurtz, Vanessa Isabell; Johansen, Alexander Rosenberg; Nielsen, Morten
Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms for training deep models and easy to use....... Here, we aim to further the development of deep learning methods within biology by providing application examples and ready to apply and adapt code templates. Given such examples, we illustrate how architectures consisting of convolutional and long short-term memory neural networks can relatively...
Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J. [Astronomy Department, University of California, Berkeley, CA 94720-7450 (United States); Brink, Henrik [Dark Cosmology Centre, Juliane Maries Vej 30, 2100 Copenhagen O (Denmark); Long, James P.; Rice, John, E-mail: email@example.com [Statistics Department, University of California, Berkeley, CA 94720-7450 (United States)
Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL-where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up-is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.
Richards, Joseph W.; Starr, Dan L.; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; Berian James, J.; Brink, Henrik; Long, James P.; Rice, John
Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.
Richards, Joseph W.; Starr, Dan L.; Brink, Henrik; Miller, Adam A.; Bloom, Joshua S.; Butler, Nathaniel R.; James, J. Berian; Long, James P.; Rice, John
Despite the great promise of machine-learning algorithms to classify and predict astrophysical parameters for the vast numbers of astrophysical sources and transients observed in large-scale surveys, the peculiarities of the training data often manifest as strongly biased predictions on the data of interest. Typically, training sets are derived from historical surveys of brighter, more nearby objects than those from more extensive, deeper surveys (testing data). This sample selection bias can cause catastrophic errors in predictions on the testing data because (1) standard assumptions for machine-learned model selection procedures break down and (2) dense regions of testing space might be completely devoid of training data. We explore possible remedies to sample selection bias, including importance weighting, co-training, and active learning (AL). We argue that AL—where the data whose inclusion in the training set would most improve predictions on the testing set are queried for manual follow-up—is an effective approach and is appropriate for many astronomical applications. For a variable star classification problem on a well-studied set of stars from Hipparcos and Optical Gravitational Lensing Experiment, AL is the optimal method in terms of error rate on the testing data, beating the off-the-shelf classifier by 3.4% and the other proposed methods by at least 3.0%. To aid with manual labeling of variable stars, we developed a Web interface which allows for easy light curve visualization and querying of external databases. Finally, we apply AL to classify variable stars in the All Sky Automated Survey, finding dramatic improvement in our agreement with the ASAS Catalog of Variable Stars, from 65.5% to 79.5%, and a significant increase in the classifier's average confidence for the testing set, from 14.6% to 42.9%, after a few AL iterations.
Tempelaar, Dirk; Rienties, Bart; Nguyen, Quan
This study aims to contribute to recent developments in empirical studies on students’ learning strategies, whereby the use of trace data is combined with self-report data to distinguish profiles of learning strategy use [3–5]. We do so in the context of an application of dispositional learning
van Marlen, Tim; van Wermeskerken, Margot; Jarodzka, Halszka; van Gog, Tamara
Eye movement modeling examples (EMME) are demonstrations of a computer-based task by a human model (e.g., a teacher), with the model's eye movements superimposed on the task to guide learners' attention. EMME have been shown to enhance learning of perceptual classification tasks; however, it is an
Panda, Priyadarshini; Srinivasa, Narayan
A fundamental challenge in machine learning today is to build a model that can learn from few examples. Here, we describe a reservoir based spiking neural model for learning to recognize actions with a limited number of labeled videos. First, we propose a novel encoding, inspired by how microsaccades influence visual perception, to extract spike information from raw video data while preserving the temporal correlation across different frames. Using this encoding, we show that the reservoir generalizes its rich dynamical activity toward signature action/movements enabling it to learn from few training examples. We evaluate our approach on the UCF-101 dataset. Our experiments demonstrate that our proposed reservoir achieves 81.3/87% Top-1/Top-5 accuracy, respectively, on the 101-class data while requiring just 8 video examples per class for training. Our results establish a new benchmark for action recognition from limited video examples for spiking neural models while yielding competitive accuracy with respect to state-of-the-art non-spiking neural models. PMID:29551962
Judd, Thomas P.; Pondish, Christopher; Secolsky, Charles
Benchmarking is a process that can take place at both the inter-institutional and intra-institutional level. This paper focuses on benchmarking intra-institutional student learning outcomes using case examples. The findings of the study illustrate the point that when the outcomes statements associated with the mission of the institution are…
Scherr, Rachel E.; Hammer, David
The concept of framing from anthropology and sociolinguistics is useful for understanding student reasoning. For example, a student may frame a learning activity as an opportunity for sensemaking or as an assignment to fill out a worksheet. The student's framing affects what she notices, what knowledge she accesses, and how she thinks to act. We…
Wong, Darren; Poo, Sng Peng; Hock, Ng Eng; Kang, Wee Loo
We describe an example of learning with multiple representations in an A-level revision lesson on mechanics. The context of the problem involved the motion of a ball thrown vertically upwards in air and studying how the associated physical quantities changed during its flight. Different groups of students were assigned to look at the ball's motion…
Hoogerheide, Vincent; Loyens, Sofie M M; van Gog, Tamara
Two experiments investigated whether acting as a peer model for a video-based modeling example, which entails studying a text with the intention to explain it to others and then actually explaining it on video, would foster learning and transfer. In both experiments, novices were instructed to study
Jarodzka, Halszka; Balslev, Thomas; Holmqvist, Kenneth; Nyström, Marcus; Scheiter, Katharina; Gerjets, Peter; Eika, Berit
Jarodzka, H., Balslev, T., Holmqvist, K., Nyström, M., Scheiter, K., Gerjets, P., & Eika, B. (2010). Learning perceptual aspects of diagnosis in medicine via eye movement modeling examples on patient video cases. In S. Ohlsson & R. Catrambone (Eds.), Proceedings of the 32nd Annual Conference of the
Jarodzka, Halszka; Balslev, Thomas; Holmqvist, Kenneth; Nyström, Marcus; Scheiter, Katharina; Gerjets, Peter; Eika, Berit
Jarodzka, H., Balslev, T., Holmqvist, K., Nyström, M., Scheiter, K., Gerjets, P., & Eika, B. (2010, August). Learning perceptual aspects of diagnosis in medicine via eye movement modeling examples on patient video cases. Poster presented at the 32nd Annual Conference of the Cognitive Science
Raaijmakers, Steven F.; Baars, Martine; Schaap, Lydia; Paas, Fred; van Merriënboer, Jeroen; van Gog, Tamara
Self-assessment and task-selection skills are crucial in self-regulated learning situations in which students can choose their own tasks. Prior research suggested that training with video modeling examples, in which another person (the model) demonstrates and explains the cyclical process of problem-solving task performance, self-assessment, and…
McCabe, Jennifer A.
The goal of this research was to determine whether there is a generation effect for learner-created keyword mnemonics and real-life examples, compared to instructor-provided materials, when learning neurophysiological terms and definitions in introductory psychology. Students participated in an individual (Study 1) or small-group (Study 2)…
Zaman, Jonas; Madden, Victoria J; Iven, Julie; Wiech, Katja; Weltens, Nathalie; Ly, Huynh Giao; Vlaeyen, Johan W S; Van Oudenhove, Lukas; Van Diest, Ilse
A growing body of research has identified fear of visceral sensations as a potential mechanism in the development and maintenance of visceral pain disorders. However, the extent to which such learned fear affects visceroception remains unclear. To address this question, we used a differential fear conditioning paradigm with nonpainful esophageal balloon distensions of 2 different intensities as conditioning stimuli (CSs). The experiment comprised of preacquisition, acquisition, and postacquisition phases during which participants categorized the CSs with respect to their intensity. The CS+ was always followed by a painful electrical stimulus (unconditioned stimulus) during the acquisition phase and in 60% of the trials during postacquisition. The second stimulus (CS-) was never associated with pain. Analyses of galvanic skin and startle eyeblink responses as physiological markers of successful conditioning showed increased fear responses to the CS+ compared with the CS-, but only in the group with the low-intensity stimulus as CS+. Computational modeling of response times and response accuracies revealed that differential fear learning affected perceptual decision-making about the intensities of visceral sensations such that sensations were more likely to be categorized as more intense. These results suggest that associative learning might indeed contribute to visceral hypersensitivity in functional gastrointestinal disorders. This study shows that associative fear learning biases intensity judgements of visceral sensations toward perceiving such sensations as more intense. Learning-induced alterations in visceroception might therefore contribute to the development or maintenance of visceral pain. Copyright © 2017 American Pain Society. Published by Elsevier Inc. All rights reserved.
Rinsky, Jessica L; Richardson, David B; Wing, Steve; Beard, John D; Alavanja, Michael; Beane Freeman, Laura E; Chen, Honglei; Henneberger, Paul K; Kamel, Freya; Sandler, Dale P; Hoppin, Jane A
Prospective cohort studies are important tools for identifying causes of disease. However, these studies are susceptible to attrition. When information collected after enrollment is through interview or exam, attrition leads to missing information for nonrespondents. The Agricultural Health Study enrolled 52,394 farmers in 1993-1997 and collected additional information during subsequent interviews. Forty-six percent of enrolled farmers responded to the 2005-2010 interview; 7% of farmers died prior to the interview. We examined whether response was related to attributes measured at enrollment. To characterize potential bias from attrition, we evaluated differences in associations between smoking and incidence of 3 cancer types between the enrolled cohort and the subcohort of 2005-2010 respondents, using cancer registry information. In the subcohort we evaluated the ability of inverse probability weighting (IPW) to reduce bias. Response was related to age, state, race/ethnicity, education, marital status, smoking, and alcohol consumption. When exposure and outcome were associated and case response was differential by exposure, some bias was observed; IPW conditional on exposure and covariates failed to correct estimates. When response was nondifferential, subcohort and full-cohort estimates were similar, making IPW unnecessary. This example provides a demonstration of investigating the influence of attrition in cohort studies using information that has been self-reported after enrollment. © The Author(s) 2017. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: firstname.lastname@example.org.
White, Peter; Cheung, Alice K.Y.
Purpose: To demonstrate how e-learning can be integrated into an undergraduate radiography programme, using an academic subject dealing with ethico-legal issues as an example. Information provided could be applied to any form of online learning. Methods: One academic subject from an undergraduate radiography programme, Case-Based Learning for Professional Studies, which had previously been taught using traditional face-to-face methods, was transformed into an e-learning format. Students who experienced the new e-learning format were evaluated by means of an online evaluation questionnaire. Results: Eighty-three percentage of respondents felt confident/semi-confident about participating in online Chat sessions. Around 34% of respondents thought that the Discussion Board was useful for communicating with fellow students. Nearly 70% of respondents believed that access to online materials enabled them to prepare for lectures and tutorials. However, 34% of students preferred more face-to-face lectures/tutorials. Overall, feedback was positive. Conclusion: Course providers and other relevant stakeholders need to be proactive in determining ways to facilitate undergraduate and post-registration development and learning. E-learning can be utilized to benefit learners who wish to work at their own pace and who cannot attend courses at remote sites. Individuals can reap the benefits of an online learning format and affording learners more flexibility and providing guidance for them, by means of a website, may help to promote a positive attitude to lifelong learning
Rock, Adam J.; Coventry, William L.; Morgan, Methuen I.; Loi, Natasha M.
Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology. PMID:27014147
White, Peter [Department of Optometry and Radiography, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong (China)]. E-mail: email@example.com; Cheung, Alice K.Y. [Department of Optometry and Radiography, Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong (China)]. E-mail: firstname.lastname@example.org
Purpose: To demonstrate how e-learning can be integrated into an undergraduate radiography programme, using an academic subject dealing with ethico-legal issues as an example. Information provided could be applied to any form of online learning. Methods: One academic subject from an undergraduate radiography programme, Case-Based Learning for Professional Studies, which had previously been taught using traditional face-to-face methods, was transformed into an e-learning format. Students who experienced the new e-learning format were evaluated by means of an online evaluation questionnaire. Results: Eighty-three percentage of respondents felt confident/semi-confident about participating in online Chat sessions. Around 34% of respondents thought that the Discussion Board was useful for communicating with fellow students. Nearly 70% of respondents believed that access to online materials enabled them to prepare for lectures and tutorials. However, 34% of students preferred more face-to-face lectures/tutorials. Overall, feedback was positive. Conclusion: Course providers and other relevant stakeholders need to be proactive in determining ways to facilitate undergraduate and post-registration development and learning. E-learning can be utilized to benefit learners who wish to work at their own pace and who cannot attend courses at remote sites. Individuals can reap the benefits of an online learning format and affording learners more flexibility and providing guidance for them, by means of a website, may help to promote a positive attitude to lifelong learning.
Rock, Adam J; Coventry, William L; Morgan, Methuen I; Loi, Natasha M
Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology.
Heitzmann, Nicole; Fischer, Frank; Fischer, Martin R.
To diagnose classroom situations is crucial for teachers' everyday practice. The approach of worked examples with errors seems promising to support the diagnosis of classroom situations in student teachers (Stark et al. in "Learn Instr" 21(1):22-33, 2011). To enhance that approach, error-explanation prompts and an adaptable feedback…
Shabel, Steven J; Murphy, Ryan T; Malinow, Roberto
The lateral habenula (LHb) is activated by aversive stimuli and the omission of reward, inhibited by rewarding stimuli and is hyperactive in helpless rats-an animal model of depression. Here we test the hypothesis that congenital learned helpless (cLH) rats are more sensitive to decreases in reward size and/or less sensitive to increases in reward than wild-type (WT) control rats. Consistent with the hypothesis, we found that cLH rats were slower to switch preference between two responses after a small upshift in reward size on one of the responses but faster to switch their preference after a small downshift in reward size. cLH rats were also more risk-averse than WT rats-they chose a response delivering a constant amount of reward ("safe" response) more often than a response delivering a variable amount of reward ("risky" response) compared to WT rats. Interestingly, the level of bias toward negative events was associated with the rat's level of risk aversion when compared across individual rats. cLH rats also showed impaired appetitive Pavlovian conditioning but more accurate responding in a two-choice sensory discrimination task. These results are consistent with a negative learning bias and risk aversion in cLH rats, suggesting abnormal processing of rewarding and aversive events in the LHb of cLH rats.
Full Text Available We conducted a human fear conditioning experiment in which three different color cues were followed by an aversive electric shock on 0, 50, and 100% of the trials, and thus induced low (L, partial (P, and high (H shock expectancy, respectively. The cues differed with respect to the strength of their shock association (L < P < H and the uncertainty of their prediction (L < P > H. During conditioning we measured pupil dilation and ocular fixations to index differences in the attentional processing of the cues. After conditioning, the shock-associated colors were introduced as irrelevant distracters during visual search for a shape target while shocks were no longer administered and we analyzed the cues’ potential to capture and hold overt attention automatically. Our findings suggest that fear conditioning creates an automatic attention bias for the conditioned cues that depends on their correlation with the aversive outcome. This bias was exclusively linked to the strength of the cues’ shock association for the early attentional processing of cues in the visual periphery, but additionally was influenced by the uncertainty of the shock prediction after participants fixated on the cues. These findings are in accord with attentional learning theories that formalize how associative learning shapes automatic attention.
Koenig, Stephan; Uengoer, Metin; Lachnit, Harald
We conducted a human fear conditioning experiment in which three different color cues were followed by an aversive electric shock on 0, 50, and 100% of the trials, and thus induced low (L), partial (P), and high (H) shock expectancy, respectively. The cues differed with respect to the strength of their shock association (L H). During conditioning we measured pupil dilation and ocular fixations to index differences in the attentional processing of the cues. After conditioning, the shock-associated colors were introduced as irrelevant distracters during visual search for a shape target while shocks were no longer administered and we analyzed the cues’ potential to capture and hold overt attention automatically. Our findings suggest that fear conditioning creates an automatic attention bias for the conditioned cues that depends on their correlation with the aversive outcome. This bias was exclusively linked to the strength of the cues’ shock association for the early attentional processing of cues in the visual periphery, but additionally was influenced by the uncertainty of the shock prediction after participants fixated on the cues. These findings are in accord with attentional learning theories that formalize how associative learning shapes automatic attention. PMID:28588466
Fonger, Nicole L.; Stephens, Ana; Blanton, Maria; Isler, Isil; Knuth, Eric; Gardiner, Angela Murphy
Learning progressions have been demarcated by some for science education, or only concerned with levels of sophistication in student thinking as determined by logical analyses of the discipline. We take the stance that learning progressions can be leveraged in mathematics education as a form of curriculum research that advances a linked…
Button, Katherine S; Kounali, Daphne; Stapinski, Lexine; Rapee, Ronald M; Lewis, Glyn; Munafò, Marcus R
Fear of negative evaluation (FNE) defines social anxiety yet the process of inferring social evaluation, and its potential role in maintaining social anxiety, is poorly understood. We developed an instrumental learning task to model social evaluation learning, predicting that FNE would specifically bias learning about the self but not others. During six test blocks (3 self-referential, 3 other-referential), participants (n = 100) met six personas and selected a word from a positive/negative pair to finish their social evaluation sentences "I think [you are / George is]…". Feedback contingencies corresponded to 3 rules, liked, neutral and disliked, with P[positive word correct] = 0.8, 0.5 and 0.2, respectively. As FNE increased participants selected fewer positive words (β = -0.4, 95% CI -0.7, -0.2, p = 0.001), which was strongest in the self-referential condition (FNE × condition 0.28, 95% CI 0.01, 0.54, p = 0.04), and the neutral and dislike rules (FNE × condition × rule, p = 0.07). At low FNE the proportion of positive words selected for self-neutral and self-disliked greatly exceeded the feedback contingency, indicating poor learning, which improved as FNE increased. FNE is associated with differences in processing social-evaluative information specifically about the self. At low FNE this manifests as insensitivity to learning negative self-referential evaluation. High FNE individuals are equally sensitive to learning positive or negative evaluation, which although objectively more accurate, may have detrimental effects on mental health.
Button, Katherine S.; Kounali, Daphne; Stapinski, Lexine; Rapee, Ronald M.; Lewis, Glyn; Munafò, Marcus R.
Background Fear of negative evaluation (FNE) defines social anxiety yet the process of inferring social evaluation, and its potential role in maintaining social anxiety, is poorly understood. We developed an instrumental learning task to model social evaluation learning, predicting that FNE would specifically bias learning about the self but not others. Methods During six test blocks (3 self-referential, 3 other-referential), participants (n = 100) met six personas and selected a word from a positive/negative pair to finish their social evaluation sentences “I think [you are / George is]…”. Feedback contingencies corresponded to 3 rules, liked, neutral and disliked, with P[positive word correct] = 0.8, 0.5 and 0.2, respectively. Results As FNE increased participants selected fewer positive words (β = −0.4, 95% CI −0.7, −0.2, p = 0.001), which was strongest in the self-referential condition (FNE × condition 0.28, 95% CI 0.01, 0.54, p = 0.04), and the neutral and dislike rules (FNE × condition × rule, p = 0.07). At low FNE the proportion of positive words selected for self-neutral and self-disliked greatly exceeded the feedback contingency, indicating poor learning, which improved as FNE increased. Conclusions FNE is associated with differences in processing social-evaluative information specifically about the self. At low FNE this manifests as insensitivity to learning negative self-referential evaluation. High FNE individuals are equally sensitive to learning positive or negative evaluation, which although objectively more accurate, may have detrimental effects on mental health. PMID:25853835
Full Text Available According to a prominent view of sensorimotor processing in primates, selection and specification of possible actions are not sequential operations. Rather, a decision for an action emerges from competition between different movement plans, which are specified and selected in parallel. For action choices which are based on ambiguous sensory input, the frontoparietal sensorimotor areas are considered part of the common underlying neural substrate for selection and specification of action. These areas have been shown capable of encoding alternative spatial motor goals in parallel during movement planning, and show signatures of competitive value-based selection among these goals. Since the same network is also involved in learning sensorimotor associations, competitive action selection (decision making should not only be driven by the sensory evidence and expected reward in favor of either action, but also by the subject's learning history of different sensorimotor associations. Previous computational models of competitive neural decision making used predefined associations between sensory input and corresponding motor output. Such hard-wiring does not allow modeling of how decisions are influenced by sensorimotor learning or by changing reward contingencies. We present a dynamic neural field model which learns arbitrary sensorimotor associations with a reward-driven Hebbian learning algorithm. We show that the model accurately simulates the dynamics of action selection with different reward contingencies, as observed in monkey cortical recordings, and that it correctly predicted the pattern of choice errors in a control experiment. With our adaptive model we demonstrate how network plasticity, which is required for association learning and adaptation to new reward contingencies, can influence choice behavior. The field model provides an integrated and dynamic account for the operations of sensorimotor integration, working memory and action
Adaptive social learning strategies in temporally and spatially varying environments : how temporal vs. spatial variation, number of cultural traits, and costs of learning influence the evolution of conformist-biased transmission, payoff-biased transmission, and individual learning.
Nakahashi, Wataru; Wakano, Joe Yuichiro; Henrich, Joseph
Long before the origins of agriculture human ancestors had expanded across the globe into an immense variety of environments, from Australian deserts to Siberian tundra. Survival in these environments did not principally depend on genetic adaptations, but instead on evolved learning strategies that permitted the assembly of locally adaptive behavioral repertoires. To develop hypotheses about these learning strategies, we have modeled the evolution of learning strategies to assess what conditions and constraints favor which kinds of strategies. To build on prior work, we focus on clarifying how spatial variability, temporal variability, and the number of cultural traits influence the evolution of four types of strategies: (1) individual learning, (2) unbiased social learning, (3) payoff-biased social learning, and (4) conformist transmission. Using a combination of analytic and simulation methods, we show that spatial-but not temporal-variation strongly favors the emergence of conformist transmission. This effect intensifies when migration rates are relatively high and individual learning is costly. We also show that increasing the number of cultural traits above two favors the evolution of conformist transmission, which suggests that the assumption of only two traits in many models has been conservative. We close by discussing how (1) spatial variability represents only one way of introducing the low-level, nonadaptive phenotypic trait variation that so favors conformist transmission, the other obvious way being learning errors, and (2) our findings apply to the evolution of conformist transmission in social interactions. Throughout we emphasize how our models generate empirical predictions suitable for laboratory testing.
Zen of Cloud: Learning Cloud Computing by Examples on Microsoft Azure provides comprehensive coverage of the essential theories behind cloud computing and the Windows Azure cloud platform. Sharing the author's insights gained while working at Microsoft's headquarters, it presents nearly 70 end-to-end examples with step-by-step guidance on implementing typical cloud-based scenarios.The book is organized into four sections: cloud service fundamentals, cloud solutions, devices and cloud, and system integration and project management. Each chapter contains detailed exercises that provide readers w
Wong, Darren; Poo, Sng Peng; Eng Hock, Ng; Loo Kang, Wee
We describe an example of learning with multiple representations in an A-level revision lesson on mechanics. The context of the problem involved the motion of a ball thrown vertically upwards in air and studying how the associated physical quantities changed during its flight. Different groups of students were assigned to look at the ball's motion using various representations: motion diagrams, vector diagrams, free-body diagrams, verbal description, equations and graphs, drawn against time as well as against displacement. Overall, feedback from students about the lesson was positive. We further discuss the benefits of using computer simulation to support and extend student learning.
Swap, R. J.; Wayland, K.
Field-based, STEM-related service learning / community engagement projects present an opportunity for undergraduate students to demonstrate proficiencies related to the process of inquiry. These proficiencies include: appreciation of the larger project context, articulation of an informed question/hypothesis, project proposal development, interdisciplinary collaboration, project management (including planning, implementation reconfiguration and synthesis) and lastly the generation and handing off of acquired knowledge. Calls for these types of proficiencies have been expressed by governmental, non-governmental as well as the private sector. Accordingly, institutions of higher learning have viewed such activities as opportunities for enriching the learning experience for undergraduate students and for making such students more marketable, especially those from STEM-related fields. This institutional interest has provided an opportunity to support and expand field-based learning. Here we present examples of student-led/faculty-mentored international service learning and community engagement projects along the arc of preparation, implementation and post-field process. Representative examples that draw upon environmental science and engineering knowledge have been selected from more than 20 international undergraduate student projects over past decade and include: slow-sand water filtration, rainwater harvesting, methane biodigesters, water reticulation schemes and development and implementation of rocket stoves for communal cooking. We discuss these efforts in terms of the development of the aforementioned proficiencies, the utility of such proficiencies to the larger enterprise of STEM and the potential for transformative student learning outcomes. We share these experiences and lessons learned with the hope that others may intelligently borrow from our approach in a manner appropriate for their particular context.
Bulf, Hermann; de Hevia, Maria Dolores; Gariboldi, Valeria; Macchi Cassia, Viola
A wealth of studies show that human adults map ordered information onto a directional spatial continuum. We asked whether mapping ordinal information into a directional space constitutes an early predisposition, already functional prior to the acquisition of symbolic knowledge and language. While it is known that preverbal infants represent numerical order along a left-to-right spatial continuum, no studies have investigated yet whether infants, like adults, organize any kind of ordinal information onto a directional space. We investigated whether 7-month-olds' ability to learn high-order rule-like patterns from visual sequences of geometric shapes was affected by the spatial orientation of the sequences (left-to-right vs. right-to-left). Results showed that infants readily learn rule-like patterns when visual sequences were presented from left to right, but not when presented from right to left. This result provides evidence that spatial orientation critically determines preverbal infants' ability to perceive and learn ordered information in visual sequences, opening to the idea that a left-to-right spatially organized mental representation of ordered dimensions might be rooted in biologically-determined constraints on human brain development.
Jurtz, Vanessa Isabell; Johansen, Alexander Rosenberg; Nielsen, Morten; Almagro Armenteros, Jose Juan; Nielsen, Henrik; Sønderby, Casper Kaae; Winther, Ole; Sønderby, Søren Kaae
Deep neural network architectures such as convolutional and long short-term memory networks have become increasingly popular as machine learning tools during the recent years. The availability of greater computational resources, more data, new algorithms for training deep models and easy to use libraries for implementation and training of neural networks are the drivers of this development. The use of deep learning has been especially successful in image recognition; and the development of tools, applications and code examples are in most cases centered within this field rather than within biology. Here, we aim to further the development of deep learning methods within biology by providing application examples and ready to apply and adapt code templates. Given such examples, we illustrate how architectures consisting of convolutional and long short-term memory neural networks can relatively easily be designed and trained to state-of-the-art performance on three biological sequence problems: prediction of subcellular localization, protein secondary structure and the binding of peptides to MHC Class II molecules. All implementations and datasets are available online to the scientific community at https://github.com/vanessajurtz/lasagne4bio. email@example.com. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: firstname.lastname@example.org
Statistical literacy is critical for the modern researcher in Physics and Astronomy. This book empowers researchers in these disciplines by providing the tools they will need to analyze their own data. Chapters in this book provide a statistical base from which to approach new problems, including numerical advice and a profusion of examples. The examples are engaging analyses of real-world problems taken from modern astronomical research. The examples are intended to be starting points for readers as they learn to approach their own data and research questions. Acknowledging that scientific progress now hinges on the availability of data and the possibility to improve previous analyses, data and code are distributed throughout the book. The JAGS symbolic language used throughout the book makes it easy to perform Bayesian analysis and is particularly valuable as readers may use it in a myriad of scenarios through slight modifications.
Malakar, Nabin K.; Lary, D. L.; Moore, A.; Gencaga, D.; Roscoe, B.; Albayrak, Arif; Petrenko, Maksym; Wei, Jennifer
Air quality information is increasingly becoming a public health concern, since some of the aerosol particles pose harmful effects to peoples health. One widely available metric of aerosol abundance is the aerosol optical depth (AOD). The AOD is the integrated light extinction coefficient over a vertical atmospheric column of unit cross section, which represents the extent to which the aerosols in that vertical profile prevent the transmission of light by absorption or scattering. The comparison between the AOD measured from the ground-based Aerosol Robotic Network (AERONET) system and the satellite MODIS instruments at 550 nm shows that there is a bias between the two data products. We performed a comprehensive analysis exploring possible factors which may be contributing to the inter-instrumental bias between MODIS and AERONET. The analysis used several measured variables, including the MODIS AOD, as input in order to train a neural network in regression mode to predict the AERONET AOD values. This not only allowed us to obtain an estimate, but also allowed us to infer the optimal sets of variables that played an important role in the prediction. In addition, we applied machine learning to infer the global abundance of ground level PM2.5 from the AOD data and other ancillary satellite and meteorology products. This research is part of our goal to provide air quality information, which can also be useful for global epidemiology studies.
Le Mens, Gael; Denrell, Jerker
Recent research has argued that several well-known judgment biases may be due to biases in the available information sample rather than to biased information processing. Most of these sample-based explanations assume that decision makers are "naive": They are not aware of the biases in the available information sample and do not correct for them.…
The type and variety of learning strategies used by individuals to acquire behaviours in the wild are poorly understood, despite the presence of behavioural traditions in diverse taxa. Social learning strategies such as conformity can be broadly adaptive, but may also retard the spread of adaptive innovations. Strategies like pay-off-biased learning, by contrast, are effective at diffusing new behaviour but may perform poorly when adaptive behaviour is common. We present a field experiment in a wild primate, Cebus capucinus, that introduced a novel food item and documented the innovation and diffusion of successful extraction techniques. We develop a multilevel, Bayesian statistical analysis that allows us to quantify individual-level evidence for different social and individual learning strategies. We find that pay-off-biased and age-biased social learning are primarily responsible for the diffusion of new techniques. We find no evidence of conformity; instead rare techniques receive slightly increased attention. We also find substantial and important variation in individual learning strategies that is patterned by age, with younger individuals being more influenced by both social information and their own individual experience. The aggregate cultural dynamics in turn depend upon the variation in learning strategies and the age structure of the wild population. PMID:28592681
Lazarov, Amit; Abend, Rany; Seidner, Shiran; Pine, Daniel S; Bar-Haim, Yair
Current attention bias modification (ABM) procedures are designed to implicitly train attention away from threatening stimuli with the hope of reducing stress reactivity and anxiety symptoms. However, the mechanisms underlying effective ABM delivery are not well understood, with awareness of the training contingency suggested as one possible factor contributing to ABM efficacy. Here, 45 high-anxious participants were trained to divert attention away from threat in two ABM sessions. They were randomly assigned to one of three training protocols: an implicit protocol, comprising two standard implicit ABM training sessions; an explicit protocol, comprising two sessions with explicit instruction as to the attention training contingency; and an implicit-explicit protocol, in which participants were not informed of the training contingency in the first ABM session and informed of it at the start of the second session. We examined learning processes and stress reactivity following a stress-induction task. Results indicate that relative to implicit instructions, explicit instructions led to stronger learning during the first training session. Following rest, the explicit and implicit groups exhibited consolidation-related improvement in performance, whereas no such improvement was noted for the implicit-explicit group. Finally, although stress reactivity was reduced after training, contingency awareness did not yield a differential effect on stress reactivity measured using both self-reports and skin conductance, within and across sessions. These results suggest that explicit ABM administration leads to greater initial learning during the training protocol while not differing from standard implicit administration in terms of off-line learning and stress reactivity. Copyright © 2017. Published by Elsevier Ltd.
Askew, Chris; Hagel, Anna; Morgan, Julie
Models of social anxiety suggest that negative social experiences contribute to the development of social anxiety, and this is supported by self-report research. However, there is relatively little experimental evidence for the effects of learning experiences on social cognitions. The current study examined the effect of observing a social performance situation with a negative outcome on children's (8 to 11 years old) fear-related beliefs and cognitive processing. Two groups of children were each shown 1 of 2 animated films of a person trying to score in basketball while being observed by others; in 1 film, the outcome was negative, and in the other, it was neutral. Children's fear-related beliefs about performing in front of others were measured before and after the film and children were asked to complete an emotional Stroop task. Results showed that social fear beliefs increased for children who saw the negative social performance film. In addition, these children showed an emotional Stroop bias for social-anxiety-related words compared to children who saw the neutral film. The findings have implications for our understanding of social anxiety disorder and suggest that vicarious learning experiences in childhood may contribute to the development of social anxiety. (c) 2015 APA, all rights reserved).
Previous research has indicated the disconnect between example-based research focusing on worked examples (WEs) and that focusing on modeling examples. The purpose of this study was to examine and compare the effect of four different types of examples from the two separate lines of research, including standard WEs, erroneous WEs, expert (masterly)…
Fiorella, Logan; van Gog, Tamara; Hoogerheide, Vincent; Mayer, Richard E.
The present study tests whether presenting video modeling examples from the learner's (first-person) perspective promotes learning of an assembly task, compared to presenting video examples from a third-person perspective. Across 2 experiments conducted in different labs, university students viewed a video showing how to assemble an 8-component…
This article discusses transformation of passive knowledge receptivity into experiences of deep learning in a lecture-based music theory course at the second-year undergraduate level through implementation of collaborative projects that evoke natural critical learning environments. It presents an example of such a project, addresses key features…
Full Text Available Individuals with pain-related concerns are likely to interpret ambiguous pain-related information in a threatening manner. It is unknown whether this interpretation bias also occurs for ambiguous pain-related facial expressions. This study examined whether individuals who habitually attach a catastrophic meaning to pain are characterized by negative interpretation bias for ambiguous pain-related facial expressions. Sixty-four female undergraduates completed an incidental learning task during which pictures of faces were presented, each followed by a visual target at one of two locations. Participants indicated target location by pressing one of two response keys. During the learning phase, happy and painful facial expressions predicted target location. During two test phases, morphed facial expressions of pain and happiness were added, equally often followed by a target at either location. Faster responses following morphs to targets at the location predicted by painful expressions compared to targets at the location predicted by happy expressions were taken to reflect pain-related interpretation bias. During one test phase, faces were preceded by either a safe or threatening context cue. High, but not low, pain-catastrophizers responded faster following morphs to targets at the location predicted by painful expressions than to targets at the other location (when participants were aware of the contingency between expression type and target location. When context cues were presented, there was no indication of interpretation bias. Participants were also asked to directly classify the facial expressions that were presented during the incidental learning task. Participants classified morphs more often as happy than as painful, independent of their level of pain catastrophizing. This observation is discussed in terms of differences between indirect and direct measures of interpretation bias.
Definitions of related concepts (e.g., genotype - phenotype ) are prevalent in introductory classes. Consequently, it is important that educators and students know which strategy(s) work best for learning them. This study showed that a new comparative elaboration strategy, called differential-associative processing, was better for learning definitions of related concepts than was an integrative elaborative strategy, called example elaboration. This outcome occurred even though example elaboration was administered in a naturalistic way (Experiment 1) and students spent more time in the example elaboration condition learning (Experiments 1, 2, 3), and generating pieces of information about the concepts (Experiments 2 and 3). Further, with unrelated concepts ( morpheme-fluid intelligence ), performance was similar regardless if students used differential-associative processing or example elaboration (Experiment 3). Taken as a whole, these results suggest that differential-associative processing is better than example elaboration for learning definitions of related concepts and is as good as example elaboration for learning definitions of unrelated concepts.
In the last few years, starting from 2010, science curricula were changed dramatically in the secondary Italian school as consequence of a radical law reform. In particular, Earth Science and Astronomy subjects have been shifted from the last to the previous school years; in addition, these subjects have been integrated with other natural sciences learning, such as biology and chemistry. As a consequence, Italian teachers felt forced to totally revise their teaching methods for all of these disciplines. The most demanding need was adapting content to younger learners, as those of the first years are, who usually do have neither pre-knowledge in physics nor high level maths skills. Secondly, content learning was progressively driven toward a greater attention to environmental issues in order to raise more awareness in learners about global changes as examples of fragile equilibrium of our planet. In this work some examples of activities are shown, to introduce students to some astronomical phenomena in a simpler way, which play a key role in influencing other Earth's events, in order to make pupils more conscious about how and to what extent our planet depends on space, at different time scales. The activities range from moon motions affecting tides, to secondary Earth motions, which are responsible for climate changes, to the possibility to find life forms in other parts of the Universe, to the possibility for humans to live in the space for future space missions. Students are involved in hands-on inquiry-based laboratories that scaffold both theoretic knowledge and practical skills for a deeper understanding of cause-effect relationships existing in the Earth.
Gepperth, Alexander R T; Rebhan, Sven; Hasler, Stephan; Fritsch, Jannik
In this contribution, we present a large-scale hierarchical system for object detection fusing bottom-up (signal-driven) processing results with top-down (model or task-driven) attentional modulation. Specifically, we focus on the question of how the autonomous learning of invariant models can be embedded into a performing system and how such models can be used to define object-specific attentional modulation signals. Our system implements bi-directional data flow in a processing hierarchy. The bottom-up data flow proceeds from a preprocessing level to the hypothesis level where object hypotheses created by exhaustive object detection algorithms are represented in a roughly retinotopic way. A competitive selection mechanism is used to determine the most confident hypotheses, which are used on the system level to train multimodal models that link object identity to invariant hypothesis properties. The top-down data flow originates at the system level, where the trained multimodal models are used to obtain space- and feature-based attentional modulation signals, providing biases for the competitive selection process at the hypothesis level. This results in object-specific hypothesis facilitation/suppression in certain image regions which we show to be applicable to different object detection mechanisms. In order to demonstrate the benefits of this approach, we apply the system to the detection of cars in a variety of challenging traffic videos. Evaluating our approach on a publicly available dataset containing approximately 3,500 annotated video images from more than 1 h of driving, we can show strong increases in performance and generalization when compared to object detection in isolation. Furthermore, we compare our results to a late hypothesis rejection approach, showing that early coupling of top-down and bottom-up information is a favorable approach especially when processing resources are constrained.
Le Mens, Gaël; Denrell, Jerker
Recent research has argued that several well-known judgment biases may be due to biases in the available information sample rather than to biased information processing. Most of these sample-based explanations assume that decision makers are "naive": They are not aware of the biases in the available information sample and do not correct for them. Here, we show that this "naivety" assumption is not necessary. Systematically biased judgments can emerge even when decision makers process available information perfectly and are also aware of how the information sample has been generated. Specifically, we develop a rational analysis of Denrell's (2005) experience sampling model, and we prove that when information search is interested rather than disinterested, even rational information sampling and processing can give rise to systematic patterns of errors in judgments. Our results illustrate that a tendency to favor alternatives for which outcome information is more accessible can be consistent with rational behavior. The model offers a rational explanation for behaviors that had previously been attributed to cognitive and motivational biases, such as the in-group bias or the tendency to prefer popular alternatives. 2011 APA, all rights reserved
Martin, José Luis R; Pérez, Víctor; Sacristán, Montse; Alvarez, Enric
Systematic reviews in mental health have become useful tools for health professionals in view of the massive amount and heterogeneous nature of biomedical information available today. In order to determine the risk of bias in the studies evaluated and to avoid bias in generalizing conclusions from the reviews it is therefore important to use a very strict methodology in systematic reviews. One bias which may affect the generalization of results is publication bias, which is determined by the nature and direction of the study results. To control or minimize this type of bias, the authors of systematic reviews undertake comprehensive searches of medical databases and expand on the findings, often undertaking searches of grey literature (material which is not formally published). This paper attempts to show the consequences (and risk) of generalizing the implications of grey literature in the control of publication bias, as was proposed in a recent systematic work. By repeating the analyses for the same outcome from three different systematic reviews that included both published and grey literature our results showed that confusion between grey literature and publication bias may affect the results of a concrete meta-analysis.
Palmer, John; Mohr, Christine; Krummenacher, Peter; Brugger, Peter
Previous research suggests that implicit sequence learning (ISL) is superior for believers in the paranormal and individuals with increased cerebral dopamine. Thirty-five healthy participants performed feedback-guided anticipations of four arrow directions. A 100-trial random sequence preceded two 100-trial biased sequences in which visual targets (arrows) on trial t tended to be displaced 90 degrees clockwise (CW) or counter-clockwise (CCW) from those on t - 1. ISL was defined as a positive change during the course of the biased run in the difference between pro-bias and counter-bias responses. It was hypothesized that this difference would be greater for believers in the paranormal than for skeptics, for those who received dopamine than for those who received placebo, and for believers who received dopamine than for the other groups. None of the hypotheses were supported by the data. It is suggested that a simple binary guessing task with a focus on prediction accuracy during early trials should be considered for future explorations.
Li, S.; Rupp, D. E.; Hawkins, L.; Mote, P.; McNeall, D. J.; Sarah, S.; Wallom, D.; Betts, R. A.
This study investigates the potential to reduce known summer hot/dry biases over Pacific Northwest in the UK Met Office's atmospheric model (HadAM3P) by simultaneously varying multiple model parameters. The bias-reduction process is done through a series of steps: 1) Generation of perturbed physics ensemble (PPE) through the volunteer computing network weather@home; 2) Using machine learning to train "cheap" and fast statistical emulators of climate model, to rule out regions of parameter spaces that lead to model variants that do not satisfy observational constraints, where the observational constraints (e.g., top-of-atmosphere energy flux, magnitude of annual temperature cycle, summer/winter temperature and precipitation) are introduced sequentially; 3) Designing a new PPE by "pre-filtering" using the emulator results. Steps 1) through 3) are repeated until results are considered to be satisfactory (3 times in our case). The process includes a sensitivity analysis to find dominant parameters for various model output metrics, which reduces the number of parameters to be perturbed with each new PPE. Relative to observational uncertainty, we achieve regional improvements without introducing large biases in other parts of the globe. Our results illustrate the potential of using machine learning to train cheap and fast statistical emulators of climate model, in combination with PPEs in systematic model improvement.
Koenig, Stephan; Nauroth, Peter; Lucke, Sara; Lachnit, Harald; Gollwitzer, Mario; Uengoer, Metin
The present study explores the notion of an out-group fear learning bias that is characterized by facilitated fear acquisition toward harm-doing out-group members. Participants were conditioned with two in-group and two out-group faces as conditioned stimuli. During acquisition, one in-group and one out-group face was paired with an aversive shock whereas the other in-group and out-group face was presented without shock. Psychophysiological measures of fear conditioning (skin conductance and pupil size) and explicit and implicit liking exhibited increased differential responding to out-group faces compared to in-group faces. However, the results did not clearly indicate that harm-doing out-group members were more readily associated with fear than harm-doing in-group members. In contrast, the out-group face not paired with shock decreased conditioned fear and disliking at least to the same extent that the shock-associated out-group face increased these measures. Based on these results, we suggest an account of the out-group fear learning bias that relates to an attentional bias to process in-group information. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
Gastelum, Zoe N.; Henry, Michael J.; Burtner, IV E.R.; Doehle, J. R.; Hampton, S. D.; La Mothe, R. R.; Nordquist, P. L.; Zarzhitsky, D. V.
The International Atomic Energy Agency (IAEA) is interested in increasing capabilities of IAEA safeguards inspectors to access information that would improve their situational awareness on the job. A mobile information platform could potentially provide access to information, analytics, and technical and logistical support to inspectors in the field, as well as providing regular updates to analysts at IAEA Headquarters in Vienna or at satellite offices. To demonstrate the potential capability of such a system, Pacific Northwest National Laboratory (PNNL) implemented a number of example capabilities within a PNNL-developed precision information environment (PIE), and using a tablet as a mobile information platform. PNNL's safeguards proof-of-concept PIE intends to; demonstrate novel applications of mobile information platforms to international safeguards use cases; demonstrate proof-of-principle capability implementation; and provide ''vision''@ for capabilities that could be implemented. This report documents the lessons learned from this two-year development activity for the Precision Information Environment for International Safeguards (PIE-IS), describing the developed capabilities, technical challenges, and considerations for future development, so that developers working to develop a similar system for the IAEA or other safeguards agencies might benefit from our work.
Gastelum, Zoe N. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Henry, Michael J. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Burtner, IV, E. R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Doehle, J. R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Hampton, S. D. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); La Mothe, R. R. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Nordquist, P. L. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Zarzhitsky, D. V. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
The International Atomic Energy Agency (IAEA) is interested in increasing capabilities of IAEA safeguards inspectors to access information that would improve their situational awareness on the job. A mobile information platform could potentially provide access to information, analytics, and technical and logistical support to inspectors in the field, as well as providing regular updates to analysts at IAEA Headquarters in Vienna or at satellite offices. To demonstrate the potential capability of such a system, Pacific Northwest National Laboratory (PNNL) implemented a number of example capabilities within a PNNL-developed precision information environment (PIE), and using a tablet as a mobile information platform. PNNL’s safeguards proof-of-concept PIE intends to; demonstrate novel applications of mobile information platforms to international safeguards use cases; demonstrate proof-of-principle capability implementation; and provide “vision” for capabilities that could be implemented. This report documents the lessons learned from this two-year development activity for the Precision Information Environment for International Safeguards (PIE-IS), describing the developed capabilities, technical challenges, and considerations for future development, so that developers working to develop a similar system for the IAEA or other safeguards agencies might benefit from our work.
Birnbaum, Michael H; Wakcher, Sandra V
Dennehy, Cornelius J.; Labbe, Steve; Lebsock, Kenneth L.
Within the broad aerospace community the importance of identifying, documenting and widely sharing lessons learned during system development, flight test, operational or research programs/projects is broadly acknowledged. Documenting and sharing lessons learned helps managers and engineers to minimize project risk and improve performance of their systems. Often significant lessons learned on a project fail to get captured even though they are well known 'tribal knowledge' amongst the project team members. The physical act of actually writing down and documenting these lessons learned for the next generation of NASA GN&C engineers fails to happen on some projects for various reasons. In this paper we will first review the importance of capturing lessons learned and then will discuss reasons why some lessons are not documented. A simple proven approach called 'Pause and Learn' will be highlighted as a proven low-impact method of organizational learning that could foster the timely capture of critical lessons learned. Lastly some examples of 'lost' GN&C lessons learned from the aeronautics, spacecraft and launch vehicle domains are briefly highlighted. In the context of this paper 'lost' refers to lessons that have not achieved broad visibility within the NASA-wide GN&C CoP because they are either undocumented, masked or poorly documented in the NASA Lessons Learned Information System (LLIS).
McKeon, Helen; Johnston, Kate; Henry, Colette
Entrepreneurial learning has recently become a topic of significant interest, with academics and economists alike recognising that the success of any new business venture is closely linked to the learning and knowledge of the entrepreneur. To date, research into entrepreneurial learning and the specific ways in which entrepreneurs learn is…
Yadiannur, Mitra; Supahar
This research aims to determine the feasibility and effectivity of mobile learning based Worked Example in Electric Circuits (WEIEC) application in improving the high school students' electric circuits interpretation ability on Direct Current Circuits materials. The research method used was a combination of Four-D Models and ADDIE model. The…
Mertens, G.; De Houwer, J.
Whereas it is widely recognized that both verbal threat information and stimulus pairings can install strong and persistent fear, few studies have addressed the interaction between these two pathways of fear. According to the expectancy bias theory of Davey (1992, 1997), verbal information can
Reali, Florencia; Griffiths, Thomas L.
The regularization of linguistic structures by learners has played a key role in arguments for strong innate constraints on language acquisition, and has important implications for language evolution. However, relating the inductive biases of learners to regularization behavior in laboratory tasks can be challenging without a formal model. In this…
Adam John Rock
Full Text Available Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal, Ginsburg, & Schau, 1997. Given the ubiquitous and distributed nature of eLearning systems (Nof, Ceroni, Jeong, & Moghaddam, 2015, teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology.
Keh, Huan-Chao; Wang, Kuei-Min; Wai, Shu-Shen; Huang, Jiung-yao; Hui, Lin; Wu, Ji-Jen
Distance learning in advanced military education can assist officers around the world to become more skilled and qualified for future challenges. Through well-chosen technology, the efficiency of distance-learning can be improved significantly. In this paper we present the architecture of Advanced Military Education-Distance Learning (AME-DL)…
Employers today expect that students will be able to work in teams. Cooperative learning theory addresses how skills such as decision making, problem solving and communication can be learned by individuals in group settings. This paper discusses how cooperative learning can be used in an online and blended environment to increase active learning…
Traditionally, many studies of second language acquisition (SLA) were based on the assumption that learning a new language mainly involves learning a set of grammatical rules, lexical items, and certain new sounds and sound combinations. However, for many second language learners, learning a second language may involve contact and interactions…
Theoretical approaches to learning in practice-based jazz improvisation contexts include situated learning and ecological perspectives. This article focuses on how interest-driven, self-sustaining jazz learning activities can be matched against the results of a recent Swedish investigation based on extensive qualitative interviews with jazz…
Marín, Victoria I.; Jääskelä, Päivikki; Häkkinen, Päivi; Juntunen, Merja; Rasku-Puttonen, Helena; Vesisenaho, Mikko
The use of seamless learning environments that have the potential to support lifelong learning anytime and anywhere has become a reality. In this sense, many educational institutions have started to consider introducing seamless learning environments into their programs. The aim of this study is to analyze how various educational university…
Fredlund, T.; Linder, C.; Airey, J.
In this article we characterize transient learning challenges as learning challenges that arise out of teaching situations rather than conflicts with prior knowledge. We propose that these learning challenges can be identified by paying careful attention to the representations that students produce. Once a transient learning challenge has been identified, teachers can create interventions to address it. By illustration, we argue that an appropriate way to design such interventions is to create variation around the disciplinary-relevant aspects associated with the transient learning challenge.
Højen, Anders; Nazzi, Thierry
Previous research showed that French-learning 16- or 20-month-olds could learn pairs of words that differed by a single consonantal but not vocalic feature. Danish has a richer vowel inventory than French, allowing for 31 phonological vowel contrasts, including vowel length and presence/absence o...
Blackwell, Simon E; Woud, Marcella L; MacLeod, Colin
While control conditions are vitally important in research, selecting the optimal control condition can be challenging. Problems are likely to arise when the choice of control condition is not tightly guided by the specific question that a given study aims to address. Such problems have become increasingly apparent in experimental psychopathology research investigating the experimental modification of cognitive biases, particularly as the focus of this research has shifted from theoretical questions concerning mechanistic aspects of the association between cognitive bias and emotional vulnerability, to questions that instead concern the clinical efficacy of 'cognitive bias modification' (CBM) procedures. We discuss the kinds of control conditions that have typically been employed in CBM research, illustrating how difficulties can arise when changes in the types of research questions asked are not accompanied by changes in the control conditions employed. Crucially, claims made on the basis of comparing active and control conditions within CBM studies should be restricted to those conclusions allowed by the specific control condition employed. CBM studies aiming to establish clinical utility are likely to require quite different control conditions from CBM studies aiming to illuminate mechanisms. Further, conclusions concerning the clinical utility of CBM interventions cannot necessarily be drawn from studies in which the control condition has been chosen to answer questions concerning mechanisms. Appreciating the need to appropriately alter control conditions in the transition from basic mechanisms-focussed investigations to applied clinical research could greatly facilitate the translational process.
Abstract The paper presents discussion about using mathematical functions in order to help academic teachers to verify acquirement of learning outcomes by students on the example of the major “geodesy and cartography”. It is relatively easy to build fuzzy relation describing levels of realization and validation learning outcomes during subject examinations and the fuzzy relation with students’ grades is already built by teachers, the problem is to combine these two relations to get one which describes the level of acquiring learning outcomes by students. There are two main requirements facing this combinations and the paper shows that the best combination according to these requirements is algebraic composition. Keywords: learning outcome, fuzzy relation, algebraic composition.
Rock, Adam J.; Coventry, William L.; Morgan, Methuen I.; Loi, Natasha M.
Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal, Ginsburg, & Schau, 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof, Ceroni, Jeong, & Moghaddam, 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to...
Hsiao, Ju-Yuan; Hung, Chun-Ling; Lan, Yu-Feng; Jeng, Yoau-Chau
Most students always lack of experience and perceive difficult regarding problem posing. The study hypothesized that worked examples may have benefits for supporting students' problem posing activities. A quasi-experiment was conducted in the context of a business mathematics course for examining the effects of integrating worked examples into…
Boekhout, Paul; van Gog, Tamara; van de Wiel, Margje W. J.; Gerards-Last, Dorien; Geraets, Jacques
Background: Worked examples are very effective for novice learners. They typically present a written-out ideal (didactical) solution for learners to study. Aims: This study used worked examples of patient history taking in physiotherapy that presented a "non"-didactical solution (i.e., based on actual performance). The effects of model expertise…
T. Boekhout (Teun); T.A.J.M. van Gog (Tamara); M.W.J. van de Wiel (Margje); D. Gerards-Last (Dorien); F. Geraets (Frank)
textabstractBackground. Worked examples are very effective for novice learners. They typically present a written-out ideal (didactical) solution for learners to study. nAims. This study used worked examples of patient history taking in physiotherapy that presented a non-didactical solution (i.e.,
Poernomo, Alvin; Kang, Dae-Ki
Training a deep neural network with a large number of parameters often leads to overfitting problem. Recently, Dropout has been introduced as a simple, yet effective regularization approach to combat overfitting in such models. Although Dropout has shown remarkable results on many deep neural network cases, its actual effect on CNN has not been thoroughly explored. Moreover, training a Dropout model will significantly increase the training time as it takes longer time to converge than a non-Dropout model with the same architecture. To deal with these issues, we address Biased Dropout and Crossmap Dropout, two novel approaches of Dropout extension based on the behavior of hidden units in CNN model. Biased Dropout divides the hidden units in a certain layer into two groups based on their magnitude and applies different Dropout rate to each group appropriately. Hidden units with higher activation value, which give more contributions to the network final performance, will be retained by a lower Dropout rate, while units with lower activation value will be exposed to a higher Dropout rate to compensate the previous part. The second approach is Crossmap Dropout, which is an extension of the regular Dropout in convolution layer. Each feature map in a convolution layer has a strong correlation between each other, particularly in every identical pixel location in each feature map. Crossmap Dropout tries to maintain this important correlation yet at the same time break the correlation between each adjacent pixel with respect to all feature maps by applying the same Dropout mask to all feature maps, so that all pixels or units in equivalent positions in each feature map will be either dropped or active during training. Our experiment with various benchmark datasets shows that our approaches provide better generalization than the regular Dropout. Moreover, our Biased Dropout takes faster time to converge during training phase, suggesting that assigning noise appropriately in
Diaz, Ana; Garcia, Alfonsa; de la Villa, Agustin
This paper analyses the role of Computer Algebra Systems (CAS) in a model of learning based on competences. The proposal is an e-learning model Linear Algebra course for Engineering, which includes the use of a CAS (Maxima) and focuses on problem solving. A reference model has been taken from the Spanish Open University. The proper use of CAS is…
Lewis, Shelia; Ewing, Christopher
Asynchronous discussions in the online teaching and learning environment significantly contributes to the achievement of student learning outcomes, which is dependent upon qualified and engaged faculty members. The discourse within this article addresses how an online university conducted faculty development through its unique Robust Learning…
Bhattacharyya, Rani; Templin, Elizabeth; Messer, Cynthia; Chazdon, Scott
Engaging communities through research-based participatory evaluation and learning methods can be rewarding for both a community and Extension. A case study of a community tourism development program evaluation shows how participatory evaluation and learning can be mutually reinforcing activities. Many communities value the opportunity to reflect…
Çuhadar, Elif; Ünal, Fatma
In this study, while the definition of informal education, which displays the main features of lifelong learning, is made, it is also attempted to identify the contributions of the local newspapers, through which the society can reach its own unique and necessary information, to the lifelong learning of their readers. In the research, within this…
Cigdam, Harun; Yildirim, Osman Gazi
Educational institutions rapidly adopt concepts and practices of online learning systems for students. But many institutions' online learning programs face enormous difficulty in achieving successful strategies. It is essential to evaluate its different aspects and understand factors which influence its effectiveness. Readiness stands out among…
This chapter examines an Indigenous speaker series formed to foster intercultural partnerships at a Canadian university. Using ensemble leadership and generative learning theories to make sense of the project, the author argues that ensemble leadership is key to designing the generative learning adult learners need in an era of ambiguity.
Tempelaar, Dirk; Sampson, Demetrios G.; Spector, J. Michael; Ifenthaler, Dirk; Isaías, Pedro
This empirical study aims to demonstrate how Dispositional Learning Analytics can contribute in the investigation of the effectiveness of didactical scenarios in authentic settings, where previous research has mostly been laboratory based. Using a showcase based on learning processes of 1080
Full Text Available Feedback design is an important issue in motor imagery BCI systems. Regardless, to date it has not been reported how feedback presentation can optimize co-adaptation between a human brain and such systems. This paper assesses the effect of realistic visual feedback on users’ BC performance and motor imagery skills. We previously developed a tele-operation system for a pair of humanlike robotic hands and showed that BCI control of such hands along with first-person perspective visual feedback of movements can arouse a sense of embodiment in the operators. In the first stage of this study, we found that the intensity of this ownership illusion was associated with feedback presentation and subjects’ performance during BCI motion control. In the second stage, we probed the effect of positive and negative feedback bias on subjects’ BCI performance and motor imagery skills. Although the subject specific classifier, which was set up at the beginning of experiment, detected no significant change in the subjects’ online performance, evaluation of brain activity patterns revealed that subjects’ self-regulation of motor imagery features improved due to a positive bias of feedback and a possible occurrence of ownership illusion. Our findings suggest that in general training protocols for BCIs, manipulation of feedback can play an important role in the optimization of subjects’ motor imagery skills.
Sabelnikova E. V.
Full Text Available We discuss the interpretation of the concept of “learning outcomes”. Theoretical analysis widely represents the interpretations of the learning outcomes of a high school student: academic skills: understanding, application of knowledge to solve problems, synthesis, analysis and evaluation; basic skills and basic knowledge, and skills of a higher order and advanced knowledge; skills of a higher order represented as a system of critical thinking, analytic reasoning, problem solving and written communication; wide abilities interpreted as verbal, quantitative and spatial thinking, understanding, problem solving and decision making. We conclude that each considered approach distinguishes meta-subjective skills, i.e. skills to interact with the quality of information regardless of the context. The ability to measure the meta-skills is discussed on an example of the “Collegiate learning assessment”, realized in the United States
Full Text Available People frequently judge how they are viewed by others during social interactions. These judgments are called metaperceptions. This study investigates the relationship between eagerness to determine the evaluation of others and metaperceptions. We propose that eagerness, which reflects approach motivation, induces positive emotions. We apply feelings-as-information theory and hypothesize that positive emotions cause optimistic self-evaluations and metaperceptions. Participants in three studies interact with judges during a singing contest (Study 1, a speech (Study 2, and an interview (Study 3. Results corroborate that eagerness to learn the evaluation of others is overall related to optimistically biased metaperceptions. This effect is mediated sequentially by positive emotions, optimistic self-evaluations, and increased metaperceptions.
Günter, Tuğçe; Akkuzu, Nalan; Alpat, Şenol
Background: This study uses problem-based learning (PBL) to ensure that students comprehend the significance of green chemistry better by experiencing the stages of identifying the problem, developing hypotheses, and providing solutions within the problem-solving process.
Daboul, Amro; Ivanovska, Tatyana; Bülow, Robin; Biffar, Reiner; Cardini, Andrea
Using 3D anatomical landmarks from adult human head MRIs, we assessed the magnitude of inter-operator differences in Procrustes-based geometric morphometric analyses. An in depth analysis of both absolute and relative error was performed in a subsample of individuals with replicated digitization by three different operators. The effect of inter-operator differences was also explored in a large sample of more than 900 individuals. Although absolute error was not unusual for MRI measurements, including bone landmarks, shape was particularly affected by differences among operators, with up to more than 30% of sample variation accounted for by this type of error. The magnitude of the bias was such that it dominated the main pattern of bone and total (all landmarks included) shape variation, largely surpassing the effect of sex differences between hundreds of men and women. In contrast, however, we found higher reproducibility in soft-tissue nasal landmarks, despite relatively larger errors in estimates of nasal size. Our study exemplifies the assessment of measurement error using geometric morphometrics on landmarks from MRIs and stresses the importance of relating it to total sample variance within the specific methodological framework being used. In summary, precise landmarks may not necessarily imply negligible errors, especially in shape data; indeed, size and shape may be differentially impacted by measurement error and different types of landmarks may have relatively larger or smaller errors. Importantly, and consistently with other recent studies using geometric morphometrics on digital images (which, however, were not specific to MRI data), this study showed that inter-operator biases can be a major source of error in the analysis of large samples, as those that are becoming increasingly common in the 'era of big data'.
Shea, Jennifer; Taylor, Tory
In the last 20 years, developmental evaluation has emerged as a promising approach to support organizational learning in emergent social programs. Through a continuous system of inquiry, reflection, and application of knowledge, developmental evaluation serves as a system of tools, methods, and guiding principles intended to support constructive organizational learning. However, missing from the developmental evaluation literature is a nuanced framework to guide evaluators in how to elevate the organizational practices and concepts most relevant for emergent programs. In this article, we describe and reflect on work we did to develop, pilot, and refine an integrated pilot framework. Drawing on established developmental evaluation inquiry frameworks and incorporating lessons learned from applying the pilot framework, we put forward the Evaluation-led Learning framework to help fill that gap and encourage others to implement and refine it. We posit that without explicitly incorporating the assessments at the foundation of the Evaluation-led Learning framework, developmental evaluation's ability to affect organizational learning in productive ways will likely be haphazard and limited. Copyright © 2017 Elsevier Ltd. All rights reserved.
Schumm, Walter R.; Webb, Farrell J.; Castelo, Carlos S.; Akagi, Cynthia G.; Jensen, Erick J.; Ditto, Rose M.; Spencer Carver, Elaine; Brown, Beverlyn F.
Discusses the use of historical events as examples for teaching college level statistics courses. Focuses on examples of the space shuttle Challenger, Pearl Harbor (Hawaii), and the RMS Titanic. Finds real life examples can bridge a link to short term experiential learning and provide a means for long term understanding of statistics. (KDR)
Huffman, Michael A; Spiezio, Caterina; Sgaravatti, Andrea; Leca, Jean-Baptiste
Demonstrating the ability to 'copy' the behavior of others is an important aspect in determining whether social learning occurs and whether group level differences in a given behavior represent cultural differences or not. Understanding the occurrence of this process in its natural context is essential, but can be a daunting task in the wild. In order to test the social learning hypothesis for the acquisition of leaf swallowing (LS), a self-medicative behavior associated with the expulsion of parasites, we conducted semi-naturalistic experiments on two captive groups of parasite-free, naïve chimpanzees (Pan troglodytes). Individuals in the group were systematically provided appropriate stimuli (rough hispid leaves) identical to those used by chimpanzees in the wild. Individuals initially responded in a variety of ways, ranging from total aversion to normal chewing and swallowing. Over time, however, the two groups adopted different variants for inserting and folding the leaves in the mouth prior to swallowing them (complete and partial LS), following the specific method spontaneously displayed by the first and primary LS models in their respective groups. These variants were similar to LS displayed by chimpanzees in the wild. Using the option-bias method, we found evidence for social learning leading to group-level biased transmission and group-level stabilization of these two variants. This is the first report on two distinct cultural variants innovated in response to the introduction of natural stimuli that emerged and spread spontaneously and concurrently within two adjacent groups of socially housed primates. These observations support the assertion that LS may reflect a generalized propensity for ingesting rough hispid leaves, which can be socially induced and transmitted within a group. Ingesting an adequate number of these leaves induces increased gut motility, which is responsible for the subsequent expulsion of particular parasite species in the wild
Nemati, Shamim; Ghassemi, Mohammad M; Clifford, Gari D
Misdosing medications with sensitive therapeutic windows, such as heparin, can place patients at unnecessary risk, increase length of hospital stay, and lead to wasted hospital resources. In this work, we present a clinician-in-the-loop sequential decision making framework, which provides an individualized dosing policy adapted to each patient's evolving clinical phenotype. We employed retrospective data from the publicly available MIMIC II intensive care unit database, and developed a deep reinforcement learning algorithm that learns an optimal heparin dosing policy from sample dosing trails and their associated outcomes in large electronic medical records. Using separate training and testing datasets, our model was observed to be effective in proposing heparin doses that resulted in better expected outcomes than the clinical guidelines. Our results demonstrate that a sequential modeling approach, learned from retrospective data, could potentially be used at the bedside to derive individualized patient dosing policies.
Kendra S Burbank
Full Text Available Top-down synapses are ubiquitous throughout neocortex and play a central role in cognition, yet little is known about their development and specificity. During sensory experience, lower neocortical areas are activated before higher ones, causing top-down synapses to experience a preponderance of post-synaptic activity preceding pre-synaptic activity. This timing pattern is the opposite of that experienced by bottom-up synapses, which suggests that different versions of spike-timing dependent synaptic plasticity (STDP rules may be required at top-down synapses. We consider a two-layer neural network model and investigate which STDP rules can lead to a distribution of top-down synaptic weights that is stable, diverse and avoids strong loops. We introduce a temporally reversed rule (rSTDP where top-down synapses are potentiated if post-synaptic activity precedes pre-synaptic activity. Combining analytical work and integrate-and-fire simulations, we show that only depression-biased rSTDP (and not classical STDP produces stable and diverse top-down weights. The conclusions did not change upon addition of homeostatic mechanisms, multiplicative STDP rules or weak external input to the top neurons. Our prediction for rSTDP at top-down synapses, which are distally located, is supported by recent neurophysiological evidence showing the existence of temporally reversed STDP in synapses that are distal to the post-synaptic cell body.
Burbank, Kendra S.; Kreiman, Gabriel
Top-down synapses are ubiquitous throughout neocortex and play a central role in cognition, yet little is known about their development and specificity. During sensory experience, lower neocortical areas are activated before higher ones, causing top-down synapses to experience a preponderance of post-synaptic activity preceding pre-synaptic activity. This timing pattern is the opposite of that experienced by bottom-up synapses, which suggests that different versions of spike-timing dependent synaptic plasticity (STDP) rules may be required at top-down synapses. We consider a two-layer neural network model and investigate which STDP rules can lead to a distribution of top-down synaptic weights that is stable, diverse and avoids strong loops. We introduce a temporally reversed rule (rSTDP) where top-down synapses are potentiated if post-synaptic activity precedes pre-synaptic activity. Combining analytical work and integrate-and-fire simulations, we show that only depression-biased rSTDP (and not classical STDP) produces stable and diverse top-down weights. The conclusions did not change upon addition of homeostatic mechanisms, multiplicative STDP rules or weak external input to the top neurons. Our prediction for rSTDP at top-down synapses, which are distally located, is supported by recent neurophysiological evidence showing the existence of temporally reversed STDP in synapses that are distal to the post-synaptic cell body. PMID:22396630
Albrechtsen, Thomas R. S.; Petersen, Morten Rask
see a great importance in the amount of guidance they give their students we will discuss the controversy between Cognitive Load Theory and a social constructivist position and the differences and possible integration of the concept of worked examples on the one hand and the concept of scaffolding...
Full Text Available In response to concerns about the validity of empirical findings in psychology, some scientists use replication studies as a way to validate good science and to identify poor science. Such efforts are resource intensive and are sometimes controversial (with accusations of researcher incompetence when a replication fails to show a previous result. An alternative approach is to examine the statistical properties of the reported literature to identify some cases of poor science. This review discusses some details of this process for prominent findings about racial bias, where a set of studies seems too good to be true. This kind of analysis is based on the original studies, so it avoids criticism from the original authors about the validity of replication studies. The analysis is also much easier to perform than a new empirical study. A variation of the analysis can also be used to explore whether it makes sense to run a replication study. As demonstrated here, there are situations where the existing data suggest that a direct replication of a set of studies is not worth the effort. Such a conclusion should motivate scientists to generate alternative experimental designs that better test theoretical ideas.
Annuschka Salima Eden; Annuschka Salima Eden; Vera eDehmelt; Vera eDehmelt; Matthias eBischoff; Pienie eZwitserlood; Harald eKugel; Kati eKeuper; Peter eZwanzger; Christian eDobel; Christian eDobel; Christian eDobel
Persons suffering from anxiety disorders display facilitated processing of arousing and negative stimuli, such as negative words. This memory bias is reflected in better recall and increased amygdala activity in response to such stimuli. However, individual learning histories were not considered in most studies, a concern that we meet here. Thirty-four female persons (half with high-, half with low trait anxiety) participated in a criterion-based associative word-learning paradigm, in which n...
Eden, Annuschka S.; Dehmelt, Vera; Bischoff, Matthias; Zwitserlood, Pienie; Kugel, Harald; Keuper, Kati; Zwanzger, Peter; Dobel, Christian
Persons suffering from anxiety disorders display facilitated processing of arousing and negative stimuli, such as negative words. This memory bias is reflected in better recall and increased amygdala activity in response to such stimuli. However, individual learning histories were not considered in most studies, a concern that we meet here. Thirty-four female persons (half with high-, half with low trait anxiety) participated in a criterion-based associative word-learning paradigm, in which n...
Braithwaite, David W.; Siegler, Robert S.
Fraction arithmetic is among the most important and difficult topics children encounter in elementary and middle school mathematics. Braithwaite, Pyke, and Siegler (2017) hypothesized that difficulties learning fraction arithmetic often reflect reliance on associative knowledge--rather than understanding of mathematical concepts and procedures--to…
Sasi, Sabri; Chang, Maiga; Altinay-Aksal, Fahriye; Kayimbasioglu, Dervis; Dervis, Huseyin; Kinshuk; Altinay-Gazi, Zehra
Early childhood quality education is a cornerstone in educational development. Many countries have started to develop their own preschool educational system in accordance with the European Union Standards, where learning English language and using technology are prerequisites. In this research, the peace context was used as a mediator for learning…
Pendidikan adalah proses mengubah perilaku manusia, dimana dalam konteks universitas adalah mahasiswa. Perubahan perilaku itu misalnya dari yang tidak mampu mengaplikasikan ilmunya menjadi mampu mengaplikasikan ilmunya. Agar pendidikan dapat berhasil, maka mahasiswa harus mengalami pengalarnan belajar (learning experience) yang relevan. Mengingat bahwa pengalaman belajar ini sangat dipengaruhi oleh aktivitas yang dilakukan mahasiswa, maka adalah sangat penting bahwa mahasiswa melakukan aktivi...
Pendidikan adalah proses mengubah perilaku manusia, dimana dalam konteks universitas adalah mahasiswa. Perubahan perilaku itu misalnya dari yang tidak mampu mengaplikasikan ilmunya menjadi mampu mengaplikasikan ilmunya. Agar pendidikan dapat berhasil, maka mahasiswa harus mengalami pengalarnan belajar (learning experience) yang relevan. Mengingat bahwa pengalaman belajar ini sangat dipengaruhi oleh aktivitas yang dilakukan mahasiswa, maka adalah sangat penting bahwa mahasiswa melakukan aktivi...
Preston, Lou; Harvie, Kate; Wallace, Heather
Inquiry-based learning features strongly in the new Australian Humanities and Social Sciences curriculum and increasingly in primary school practice. Yet, there is little research into, and few exemplars of, inquiry approaches in the primary humanities context. In this article, we outline and explain the implementation of a place-based simulation…
Rincon, Lilian; Parker, Drew
Online learning is coming of age in both postsecondary education and industry. The courses now offered online range from kinesiology to mathematics to complete M.B.A. programs. The growing popularity of online education has created a need to reduce costs without diminishing the value of the edification. In response to this need, an instructional…
Kordumova, S.; Li, X.; Snoek, C.G.M.
Learning video concept detectors from social media sources, such as Flickr images and YouTube videos, has the potential to address a wide variety of concept queries for video search. While the potential has been recognized by many, and progress on the topic has been impressive, we argue that key
Köpsén, Susanne; Nyström, Sofia
Supervision intended to support learning is of great interest in professional knowledge development. No single definition governs the implementation and enactment of supervision because of different conditions, intentions, and pedagogical approaches. Uncertainty exists at a time when knowledge and methods are undergoing constant development. This…
Podolefsky, Noah S.; Finkelstein, Noah D.
This paper describes a model of analogy, analogical scaffolding, which explains present and prior results of student learning with analogies. We build on prior models of representation, blending, and layering of ideas. Extending this model's explanatory power, we propose ways in which the model can be applied to design a curriculum directed at…
Lamie, R. David; Barkley, David L.; Markley, Deborah M.
Rural small businesses struggling against the current of competition from "big box" retailers, weak consumer demand, and on-line shopping options must find strategies that work. Many are finding that adoption of e-commerce strategies is a key to survival, even prosperity. This article highlights the lessons learned from a recent case study…
Wang, Yanqing; Ai, Wenguo; Liang, Yaowen; Liu, Ying
Peer assessment is an efficient and effective learning assessment method that has been used widely in diverse fields in higher education. Despite its many benefits, a fundamental problem in peer assessment is that participants lack the motivation to assess others' work faithfully and fairly. Nonconsensus is a common challenge that makes the…
Günter, Tugçe; Akkuzu, Nalan; Alpat, Senol
Background: This study uses problem-based learning (PBL) to ensure that students comprehend the significance of green chemistry better by experiencing the stages of identifying the problem, developing hypotheses, and providing solutions within the problem-solving process. Purpose: The aim of this study is to research the effect of PBL implemented…
Robertson, Sydney Ian
Students in tertiary education are often faced with the prospect of writing an essay on a topic they know nothing about in advance. In distance learning institutions, essays are a common method of assessment in the UK, and specified course texts remain the main sources of information the students have. How do students use a source text to…
Börchers, M; Tipold, A; Pfarrer, Ch; Fischer, M R; Ehlers, J P
New teaching methods such as e-learning, are increasingly used to support common methods such as lectures, seminars and practical training in universities providing education in veterinary medicine. In the current study, the acceptance of e-learning in the example of the CASUS system by veterinarians as well as students of veterinary medicine of all German-speaking universities was analyzed. Material und methods: For this purpose an online evaluation questionnaire was developed. Members of the target groups were informed by e-mail and references in professional journals, as well as through veterinarian exchange platforms on the internet. Additionally, 224 students' final anatomy marks were compared and correlated to the utilization of CASUS to gain an important insight for the development of new teaching practices in the teaching of veterinary medicine. In total 1581 questionnaires were evaluated. A good acceptance regarding new teaching practices was found, although the classical textbook is still the most important instrument for imparting knowledge. The degree of utilization of e-learning strongly depends on its integration into the teaching content. CASUS is regarded as an efficient teaching method, with over 90% of the respondents indicating a strong desire to expand the number of case studies. Due to the present low degree of integration into the teaching content, no significant correlation could be found between the utilization of anatomy case studies and the final anatomy mark. However, based on their subjective perception, the students reported a high level of success in their study results with the likely effect of supporting increasing self-assurance in the situation of examinations. With the help of e-learning, educational objectives can be achieved that are not attainable by traditional teaching methods, e.g. the review of individual improvements by using the integrated feedback-function of e-learning programs. However, e-learning is not able to
Full Text Available Analysis, the first phase of the typical instructional design process, is often downplayed. This paper focuses on the analysis concerning a series of e-courses for collaborative adult education in semi-formal settings by reporting and generalizing results from the REVIT project. REVIT, an EU-funded research project, offered custom e-courses to learners in several remote European areas and received a ‘best practice’ distinction in social inclusion. These e-courses were designed and developed for the purpose of providing training in aspects of the learners’ professional domains related to the utilization of information and communication technologies. The main challenge was to prove that it is possible and economically feasible to provide meaningful training opportunities via distance education, by utilizing existing infrastructure (“revitalizing schools” and by making use of modern digital technology affordances coupled with suitable distance learning techniques and Web 2.0 tools. ADDIE, the generic instructional systems design model, enhanced with a rapid prototyping phase, was put forth in order to allow stakeholders to interact with a prototypical e-course, which served as an introductory lesson and as a reference point, since its evaluation informed the design choices of all subsequent e-courses. The learning needs approach adopted in REVIT combined learner analysis, context analysis, and needs analysis into a coherent analysis framework in which several methods (observation, estimation, document analysis, survey, and dialogue were exploited. Putting emphasis on the analysis phase and decoupling the design from the delivery of the e-courses facilitated adaptation and localization. Adaptation and localization issues concerning the adoption of the REVIT distance learning framework, taking into account the socio-cultural and pedagogical context, are discussed. A central result reported is that the analysis phase was crucial for the
Andreon, Stefano; Weaver, Brian
Chapter 1: This chapter presents some basic steps for performing a good statistical analysis, all summarized in about one page. Chapter 2: This short chapter introduces the basics of probability theory inan intuitive fashion using simple examples. It also illustrates, again with examples, how to propagate errors and the difference between marginal and profile likelihoods. Chapter 3: This chapter introduces the computational tools and methods that we use for sampling from the posterior distribution. Since all numerical computations, and Bayesian ones are no exception, may end in errors, we also provide a few tips to check that the numerical computation is sampling from the posterior distribution. Chapter 4: Many of the concepts of building, running, and summarizing the resultsof a Bayesian analysis are described with this step-by-step guide using a basic (Gaussian) model. The chapter also introduces examples using Poisson and Binomial likelihoods, and how to combine repeated independent measurements. Chapter 5: All statistical analyses make assumptions, and Bayesian analyses are no exception. This chapter emphasizes that results depend on data and priors (assumptions). We illustrate this concept with examples where the prior plays greatly different roles, from major to negligible. We also provide some advice on how to look for information useful for sculpting the prior. Chapter 6: In this chapter we consider examples for which we want to estimate more than a single parameter. These common problems include estimating location and spread. We also consider examples that require the modeling of two populations (one we are interested in and a nuisance population) or averaging incompatible measurements. We also introduce quite complex examples dealing with upper limits and with a larger-than-expected scatter. Chapter 7: Rarely is a sample randomly selected from the population we wish to study. Often, samples are affected by selection effects, e.g., easier
Pedersen, Kamilla; Moeller, Martin Holdgaard; Paltved, Charlotte
OBJECTIVES: The aim of this study was to explore medical students' learning experiences from the didactic teaching formats using either text-based patient cases or video-based patient cases with similar content. The authors explored how the two different patient case formats influenced students......' perceptions of psychiatric patients and students' reflections on meeting and communicating with psychiatric patients. METHODS: The authors conducted group interviews with 30 medical students who volunteered to participate in interviews and applied inductive thematic content analysis to the transcribed...
Full Text Available Various biological factors have been implicated in convulsive seizures, involving side effects of drugs. For the preclinical safety assessment of drug development, it is difficult to predict seizure-inducing side effects. Here, we introduced a machine learning-based in vitro system designed to detect seizure-inducing side effects. We recorded local field potentials from the CA1 alveus in acute mouse neocortico-hippocampal slices, while 14 drugs were bath-perfused at 5 different concentrations each. For each experimental condition, we collected seizure-like neuronal activity and merged their waveforms as one graphic image, which was further converted into a feature vector using Caffe, an open framework for deep learning. In the space of the first two principal components, the support vector machine completely separated the vectors (i.e., doses of individual drugs that induced seizure-like events and identified diphenhydramine, enoxacin, strychnine and theophylline as “seizure-inducing” drugs, which indeed were reported to induce seizures in clinical situations. Thus, this artificial intelligence-based classification may provide a new platform to detect the seizure-inducing side effects of preclinical drugs.
Braithwaite, David W; Siegler, Robert S
Fraction arithmetic is among the most important and difficult topics children encounter in elementary and middle school mathematics. Braithwaite, Pyke, and Siegler (2017) hypothesized that difficulties learning fraction arithmetic often reflect reliance on associative knowledge-rather than understanding of mathematical concepts and procedures-to guide choices of solution strategies. They further proposed that this associative knowledge reflects distributional characteristics of the fraction arithmetic problems children encounter. To test these hypotheses, we examined textbooks and middle school children in the United States (Experiments 1 and 2) and China (Experiment 3). We asked the children to predict which arithmetic operation would accompany a specified pair of operands, to generate operands to accompany a specified arithmetic operation, and to match operands and operations. In both countries, children's responses indicated that they associated operand pairs having equal denominators with addition and subtraction, and operand pairs having a whole number and a fraction with multiplication and division. The children's associations paralleled the textbook input in both countries, which was consistent with the hypothesis that children learned the associations from the practice problems. Differences in the effects of such associative knowledge on U.S. and Chinese children's fraction arithmetic performance are discussed, as are implications of these differences for educational practice. (PsycINFO Database Record (c) 2018 APA, all rights reserved).
Moscariello, A.; Hoof, T.B. van; Kunakbayeva, G.; Veen, J.H. ten; Belt, F. van den; Twerda, A.; Peters, L.; Davis, P.; Williams, H.
The Geological Model Calibration - Learnings from Integration of Reservoir Geology and Field Performance: example from the Upper Carboniferous Reservoirs of the Southern North Sea. Copyright © (2012) by the European Association of Geoscientists & Engineers All rights reserved.
Lyon, Steve W.; Walter, M. Todd; Jantze, Elin J.; Archibald, Josephine A.
Structuring an education strategy capable of addressing the various spheres of ecohydrology is difficult due to the inter-disciplinary and cross-disciplinary nature of this emergent field. Clearly, there is a need for such strategies to accommodate more progressive educational concepts while highlighting a skills-based education. To demonstrate a possible way to develop courses that include such concepts, we offer a case-study or a 'how-you-can-do-it' example from an ecohydrology course recently co-taught by teachers from Stockholm University and Cornell University at Stockholm University's Navarino Environmental Observatory (NEO) in Costa Navarino, Greece. This course focused on introducing hydrology Master's students to some of the central concepts of ecohydrology while at the same time supplying process-based understanding relevant for characterizing evapotranspiration. As such, the main goal of the course was to explore central theories in ecohydrology and their connection to plant-water interactions and the water cycle in a semiarid environment. In addition to presenting this roadmap for ecohydrology course development, we explore the utility and effectiveness of adopting active teaching and learning strategies drawing from the suite of learn-by-doing, hands-on, and inquiry-based techniques in such a course. We test a gradient of 'activeness' across a sequence of three teaching and learning activities. Our results indicate that there was a clear advantage for utilizing active learning techniques in place of traditional lecture-based styles. In addition, there was a preference among the student towards the more 'active' techniques. This demonstrates the added value of incorporating even the simplest active learning approaches in our ecohydrology (or general) teaching.
Lyon, S. W.; Walter, M. T.; Jantze, E. J.; Archibald, J. A.
Structuring an education strategy capable of addressing the various spheres of ecohydrology is difficult due to the inter-disciplinary and cross-disciplinary nature of this emergent field. Clearly, there is a need for such strategies to accommodate more progressive educational concepts while highlighting a skills-based education. To demonstrate a possible way to develop courses that include such concepts, we offer a case-study or a ';how-you-can-do-it' example from an ecohydrology course recently co-taught by teachers from Stockholm University and Cornell University at Stockholm University's Navarino Environmental Observatory (NEO) in Costa Navarino, Greece. This course focused on introducing hydrology Master's students to some of the central concepts of ecohydrology while at the same time supplying process-based understanding relevant for characterizing evapotranspiration. As such, the main goal of the course was to explore central theories in ecohydrology and their connection to plant-water interactions and the water cycle in a semiarid environment. In addition to presenting this roadmap for ecohydrology course development, we explore the utility and effectiveness of adopting active teaching and learning strategies drawing from the suite of learn-by-doing, hands-on, and inquiry-based techniques in such a course. We test a gradient of ';activeness' across a sequence of three teaching and learning activities. Our results indicate that there was a clear advantage for utilizing active learning techniques in place of traditional lecture-based styles. In addition, there was a preference among the student towards the more ';active' techniques. This demonstrates the added value of incorporating even the simplest active learning approaches in our ecohydrology (or general) teaching.
Moeller, Karl Dieter
This new edition is intended for a one semester course in optics for juniors and seniors in science and engineering; it uses scripts from Maple, MathCad, Mathematica, and MATLAB provide a simulated laboratory where students can learn by exploration and discovery instead of passive absorption. The text covers all the standard topics of a traditional optics course, including: geometrical optics and aberration, interference and diffraction, coherence, Maxwell's equations, wave guides and propagating modes, blackbody radiation, atomic emission and lasers, optical properties of materials, Fourier transforms and FT spectroscopy, image formation, and holography. It contains step by step derivations of all basic formulas in geometrical, wave and Fourier optics. The basic text is supplemented by over 170 files in Maple, MathCad, Mathematica, and MATLAB (many of which are in the text, each suggesting programs to solve a particular problem, and each linked to a topic in or application of optics. The computer files are d...
Mousas, Christos; Anagnostopoulos, Christos-Nikolaos
This paper presents a methodology for estimating the motion of a character's fingers based on the use of motion features provided by a virtual character's hand. In the presented methodology, firstly, the motion data is segmented into discrete phases. Then, a number of motion features are computed for each motion segment of a character's hand. The motion features are pre-processed using restricted Boltzmann machines, and by using the different variations of semantically similar finger gestures in a support vector machine learning mechanism, the optimal weights for each feature assigned to a metric are computed. The advantages of the presented methodology in comparison to previous solutions are the following: First, we automate the computation of optimal weights that are assigned to each motion feature counted in our metric. Second, the presented methodology achieves an increase (about 17%) in correctly estimated finger gestures in comparison to a previous method.
Noah D. Finkelstein
Full Text Available This paper describes a model of analogy, analogical scaffolding, which explains present and prior results of student learning with analogies. We build on prior models of representation, blending, and layering of ideas. Extending this model’s explanatory power, we propose ways in which the model can be applied to design a curriculum directed at teaching abstract ideas in physics using multiple, layered analogies. We report on a recent empirical study that motivates this model. Students taught about electromagnetic waves in a curriculum that builds on the model of analogical scaffolding posted substantially greater gains pre- to postinstruction than students taught using a more traditional (non-analogy-based tutorial (21% vs 7%.
Lessons learned from the JCO Nuclear Criticality Accident of 30 September 1999 in a uranium conversion test plant in Tokai-mura, Japan, are reviewed by referring some pertinent matters from the official report of this accident to remind of the universal characteristics among possible accidents of chemical plants. The paper discusses the responsibility of the establishment or institution to the demand alternation or request change from the client, how to respond to the proposal arising from the factory floor, and the safety control system of every-day maintenance of the factory which are important to prevent accidents in chemical plants. After explaining a background leading to the JCO accident, the author summarizes the lessons as follows: (1) changeable control system, (2) perfect provision of the manual considering the actual condition, and (3) clarification of the roles each played by the managers and the workers are most necessary and important. (S. Ohno)
Recent terrorist threats and actual events have lead to a renewed interest in the technical field of large scale, urban environment decontamination. One of the driving forces for this interest is the real potential for the cleanup and removal of radioactive dispersal device (RDD or “dirty bomb”) residues. In response the U. S. Government has spent many millions of dollars investigating RDD contamination and novel decontamination methodologies. Interest in chemical and biological (CB) cleanup has also peaked with the threat of terrorist action like the anthrax attack at the Hart Senate Office Building and with catastrophic natural events such as Hurricane Katrina. The efficiency of cleanup response will be improved with these new developments and a better understanding of the “old reliable” methodologies. Perhaps the most interesting area of investigation for large area decontamination is that of the RDD. While primarily an economic and psychological weapon, the need to cleanup and return valuable or culturally significant resources to the public is nonetheless valid. Several private companies, universities and National Laboratories are currently developing novel RDD cleanup technologies. Because of its longstanding association with radioactive facilities, the U. S. Department of Energy National Laboratories are at the forefront in developing and testing new RDD decontamination methods. However, such cleanup technologies are likely to be fairly task specific; while many different contamination mechanisms, substrate and environmental conditions will make actual application more complicated. Some major efforts have also been made to model potential contamination, to evaluate both old and new decontamination techniques and to assess their readiness for use. Non-radioactive, CB threats each have unique decontamination challenges and recent events have provided some examples. The U. S. Environmental Protection Agency (EPA), as lead agency for these emergency
Fiorella, Logan; van Gog, T.; Hoogerheide, V.; Mayer, Richard
The present study tests whether presenting video modeling examples from the learner’s (first-person) perspective promotes learning of an assembly task, compared to presenting video examples from a third-person perspective. Across 2 experiments conducted in different labs, university students viewed
Full Text Available “Man is the only being who needs education,” and that "Man can only become man by education" (see footnotes 1 ABSTRACT Since May of 1999, 46 European countries have been engaged in reconstructing their higher education systems to bring about a greater degree of “convergence,” i.e. a move toward common reference points and operating procedures to create a European Higher Education Area. Education has always played an important role in the development of Lithuania, with long and strong traditions as a country with highly educated scientists and cutting-edge research in various fields. In April 2009, the Seimas passed a new Law on Science and Studies, which provides for a major reform of higher education. In recent years there has been an increasing focus on the role universities play in the economy and impact they make in promoting innovation and raising international competitiveness. But until recently there has been a prescriptive view of university-business interactions with a narrow focus on technology transfer. Although technology transfer may be important, it is also necessary to focus on the more diverse and varied impacts of business-university knowledge exchange relations. Thus, I discuss changes in higher education that were implemented in Lithuania during the period of 1992-2012, i. e. Student baskets, notorious optimization of university network in Lithuania, the development of Lithuanian science valleys, etc. In my survey I rely upon an IHEP (Institute for Higher Education Policy expert Cliff Adelman’s idea that the Bologna Process is an analogue to the macroeconomic theory of convergence, the ways in which nations move from different stages of development to a more-or-less common platform of performance. Macroeconomic historians have demonstrated time-and-again: nations that learn from other nations grow; those that do not learn do not. Ultimately, I arrive at a conclusion that reforms are essential and indispensable but
Eden, Annuschka S; Dehmelt, Vera; Bischoff, Matthias; Zwitserlood, Pienie; Kugel, Harald; Keuper, Kati; Zwanzger, Peter; Dobel, Christian
Persons suffering from anxiety disorders display facilitated processing of arousing and negative stimuli, such as negative words. This memory bias is reflected in better recall and increased amygdala activity in response to such stimuli. However, individual learning histories were not considered in most studies, a concern that we meet here. Thirty-four female persons (half with high-, half with low trait anxiety) participated in a criterion-based associative word-learning paradigm, in which neutral pseudowords were paired with aversive or neutral pictures, which should lead to a valence change for the negatively paired pseudowords. After learning, pseudowords were tested with fMRI to investigate differential brain activation of the amygdala evoked by the newly acquired valence. Explicit and implicit memory was assessed directly after training and in three follow-ups at 4-day intervals. The behavioral results demonstrate that associative word-learning leads to an explicit (but no implicit) memory bias for negatively linked pseudowords, relative to neutral ones, which confirms earlier studies. Bilateral amygdala activation underlines the behavioral effect: Higher trait anxiety is correlated with stronger amygdala activation for negatively linked pseudowords than for neutrally linked ones. Most interestingly, this effect is also present for negatively paired pseudowords that participants could not remember well. Moreover, neutrally paired pseudowords evoked higher amygdala reactivity than completely novel ones in highly anxious persons, which can be taken as evidence for generalization. These findings demonstrate that few word-learning trials generate a memory bias for emotional stimuli, indexed both behaviorally and neurophysiologically. Importantly, the typical memory bias for emotional stimuli and the generalization to neutral ones is larger in high anxious persons.
Annuschka Salima Eden
Full Text Available Persons suffering from anxiety disorders display facilitated processing of arousing and negative stimuli, such as negative words. This memory bias is reflected in better recall and increased amygdala activity in response to such stimuli. However, individual learning histories were not considered in most studies, a concern that we meet here. Thirty-four female persons (half with high-, half with low trait anxiety participated in a criterion-based associative word-learning paradigm, in which neutral pseudowords were paired with aversive or neutral pictures, which should lead to a valence change for the negatively paired pseudowords. After learning, pseudowords were tested with fMRI to investigate differential brain activation of the amygdala evoked by the newly acquired valence. Explicit and implicit memory was assessed directly after training and in three follow-ups at four-day intervals. The behavioral results demonstrate that associative word-learning leads to an explicit (but no implicit memory bias for negatively linked pseudowords, relative to neutral ones, which confirms earlier studies. Bilateral amygdala activation underlines the behavioral effect: Higher trait anxiety is correlated with stronger amygdala activation for negatively linked pseudowords than for neutrally linked ones. Most interestingly, this effect is also present for negatively paired pseudowords that participants could not remember well. Moreover, neutrally paired pseudowords evoked higher amygdala reactivity than completely novel ones in highly anxious persons, which can be taken as evidence for generalization. These findings demonstrate that few word-learning trials generate a memory bias for emotional stimuli, indexed both behaviorally and neurophysiologically. Importantly, the typical memory bias for emotional stimuli and the generalization to neutral ones is larger in high anxious persons.
van Wermeskerken, Margot; Grimmius, Bianca; van Gog, Tamara
We investigated the effects of seeing the instructor's (i.e., the model's) face in video modeling examples on students' attention and their learning outcomes. Research with university students suggested that the model's face attracts students' attention away from what the model is doing, but this did not hamper learning. We aimed to investigate…
Baehr, Johanna; Behrens, Jörn; Brüggemann, Michael; Frisius, Thomas; Glessmer, Mirjam S.; Hartmann, Jens; Hense, Inga; Kaleschke, Lars; Kutzbach, Lars; Rödder, Simone; Scheffran, Jürgen
Climate change is commonly regarded as one of 21st century's grand challenges that needs to be addressed by conducting integrated research combining natural and social sciences. To meet this need, how to best train future climate researchers should be reconsidered. Here, we present our experience from a team-taught semester-long course with students of the international master program "Integrated Climate System Sciences" (ICSS) at the University of Hamburg, Germany. Ten lecturers with different backgrounds in physical, mathematical, biogeochemical and social sciences accompanied by a researcher trained in didactics prepared and regularly participated in a course which consisted of weekly classes. The foundation of the course was the use of the concept of 'scales' - climate varying on different temporal and spatial scales - by developing a joint definition of 'scales in the climate system' that is applicable in the natural sciences and in the social sciences. By applying this interdisciplinary definition of 'scales' to phenomena from all components of the climate system and the socio-economic dimensions, we aimed for an integrated description of the climate system. Following the concept of research-driven teaching and learning and using a variety of teaching techniques, the students designed their own scale diagram to illustrate climate-related phenomena in different disciplines. The highlight of the course was the presentation of individually developed scale diagrams by every student with all lecturers present. Based on the already conducted course, we currently re-design the course concept to be teachable by a similarly large group of lecturers but with alternating presence in class. With further refinement and also a currently ongoing documentation of the teaching material, we will continue to use the concept of 'scales' as a vehicle for teaching an integrated view of the climate system.
Raymaker, Dora M
Critical systems thinking (CST) and community based participatory research (CBPR) are distinct approaches to inquiry which share a primary commitment to holism and human emancipation, as well as common grounding in critical theory and emancipatory and pragmatic philosophy. This paper explores their intersections and complements on a historical, philosophical, and theoretical level, and then proposes a hybrid approach achieved by applying CBPR's principles and considerations for operationalizing emancipatory practice to traditional systems thinking frameworks and practices. This hybrid approach is illustrated in practice with examples drawn from of the implementation of the learning organization model in an action research setting with the Autistic community. Our experience of being able to actively attend to, and continuously equalize, power relations within an organizational framework that otherwise has great potential for reinforcing power inequity suggests CBPR's principles and considerations for operationalizing emancipatory practice could be useful in CST settings, and CST's vocabulary, methods, and clarity around systems thinking concepts could be valuable to CBPR practioners.
Pegah Kassraian Fard
Full Text Available Most psychiatric disorders are associated with subtle alterations in brain function and are subject to large inter-individual differences. Typically the diagnosis of these disorders requires time-consuming behavioral assessments administered by a multi-disciplinary team with extensive experience. Whilst the application of machine learning classification methods (ML classifiers to neuroimaging data has the potential to speed and simplify diagnosis of psychiatric disorders, the methods, assumptions, and analytical steps are not currently opaque and accessible to researchers and clinicians outside the field. In this paper, we describe potential classification pipelines for Autism Spectrum Disorder, as an example of a psychiatric disorder. The analyses are based on resting-state fMRI data derived from a multi-site data repository (ABIDE. We compare several popular ML classifiers such as support vector machines, neural networks and regression approaches, among others. In a tutorial style, written to be equally accessible for researchers and clinicians, we explain the rationale of each classification approach, clarify the underlying assumptions, and discuss possible pitfalls and challenges. We also provide the data as well as the MATLAB code we used to achieve our results. We show that out-of-the-box ML classifiers can yield classification accuracies of about 60-70%. Finally, we discuss how classification accuracy can be further improved, and we mention methodological developments that are needed to pave the way for the use of ML classifiers in clinical practice.
Taina M Wewer
Full Text Available This article on principles and practices in Content and Language Integrated Learning (CLIL is also applicable for general foreign and second language instruction. Since there is no ‘one size fits all’ CLIL pedagogy, the origin of the article lies in the need of educators to obtain and exchange ideas of and tools for actual classroom practices (Pérez Cañado, 2017, and ensure that all key features of CLIL are present in instruction. Although there are a few handbooks available for launching CLIL and adopting CLIL pedagogy (e.g., Coyle, Hood, & Marsh, 2010; Mehisto, Marsh, & Frigols, 2008, these provide principles and general examples of content-based instruction at higher levels of education rather than more detailed advice on how to operate in the beginning phases with young language learners, hence the focus on primary education. The Observation Tool for Effective CLIL Teaching created by de Graaff, Koopman, Anikina, and Gerrit (2007 was chosen as the starting point and was complemented with three additional fields that were not markedly included in the original model: cultural aspects, affects, and assessment.
Schmelz, Joan T.
We all have biases, and we are (for the most part) unaware of them. In general, men and women BOTH unconsciously devalue the contributions of women. This can have a detrimental effect on grant proposals, job applications, and performance reviews. Sociology is way ahead of astronomy in these studies. When evaluating identical application packages, male and female University psychology professors preferred 2:1 to hire "Brian” over "Karen” as an assistant professor. When evaluating a more experienced record (at the point of promotion to tenure), reservations were expressed four times more often when the name was female. This unconscious bias has a repeated negative effect on Karen's career. This talk will introduce the concept of unconscious bias and also give recommendations on how to address it using an example for a faculty search committee. The process of eliminating unconscious bias begins with awareness, then moves to policy and practice, and ends with accountability.
Pecas Lopes, J.A. [Universidade do Porto, Porto (Portugal). Faculdade de Engenharia] Hatziargyriou, Nikos D. [National Technical University of Athens, Athens (Greece)
This paper provides an overview of the application of `learning from examples` techniques like pattern recognition, artificial neural networks and decision trees, when used for fast dynamic security assessment. Problems concerning the system security evaluation relatively to transient stability and voltage stability are addressed with more details and references to research works in this field are briefly described. (author) 44 refs., 3 tabs.
Levy, David M; Peart, Sandra J
We wish to deal with investigator bias in a statistical context. We sketch how a textbook solution to the problem of "outliers" which avoids one sort of investigator bias, creates the temptation for another sort. We write down a model of the approbation seeking statistician who is tempted by sympathy for client to violate the disciplinary standards. We give a simple account of one context in which we might expect investigator bias to flourish. Finally, we offer tentative suggestions to deal with the problem of investigator bias which follow from our account. As we have given a very sparse and stylized account of investigator bias, we ask what might be done to overcome this limitation.
Bernard, Robert M.
This paper examines sources of potential bias in systematic reviews and meta-analyses which can distort their findings, leading to problems with interpretation and application by practitioners and policymakers. It follows from an article that was published in the "Canadian Journal of Communication" in 1990, "Integrating Research…
Rodríguez-Quiñonez, J. C.; Sergiyenko, O.; Hernandez-Balbuena, D.; Rivas-Lopez, M.; Flores-Fuentes, W.; Basaca-Preciado, L. C.
Many laser scanners depend on their mechanical construction to guarantee their measurements accuracy, however, the current computational technologies allow us to improve these measurements by mathematical methods implemented in neural networks. In this article we are going to introduce the current laser scanner technologies, give a description of our 3D laser scanner and adjust their measurement error by a previously trained feed forward back propagation (FFBP) neural network with a Widrow-Hoff weight/bias learning function. A comparative analysis with other learning functions such as the Kohonen algorithm and gradient descendent with momentum algorithm is presented. Finally, computational simulations are conducted to verify the performance and method uncertainty in the proposed system.
McElreath, Richard; Bell, Adrian V; Efferson, Charles; Lubell, Mark; Richerson, Peter J; Waring, Timothy
The existence of social learning has been confirmed in diverse taxa, from apes to guppies. In order to advance our understanding of the consequences of social transmission and evolution of behaviour, however, we require statistical tools that can distinguish among diverse social learning strategies. In this paper, we advance two main ideas. First, social learning is diverse, in the sense that individuals can take advantage of different kinds of information and combine them in different ways. Examining learning strategies for different information conditions illuminates the more detailed design of social learning. We construct and analyse an evolutionary model of diverse social learning heuristics, in order to generate predictions and illustrate the impact of design differences on an organism's fitness. Second, in order to eventually escape the laboratory and apply social learning models to natural behaviour, we require statistical methods that do not depend upon tight experimental control. Therefore, we examine strategic social learning in an experimental setting in which the social information itself is endogenous to the experimental group, as it is in natural settings. We develop statistical models for distinguishing among different strategic uses of social information. The experimental data strongly suggest that most participants employ a hierarchical strategy that uses both average observed pay-offs of options as well as frequency information, the same model predicted by our evolutionary analysis to dominate a wide range of conditions.
We describe a study on the motivation of trainees in e-learning-based professional training and on the effect of their motivation upon the perceptions they build about the quality of the courses. We propose the concepts of "perceived motivational gap" and "real motivational gap" as indicators of e-learning quality, which…
Culbertson, Jennifer; Smolensky, Paul
In this article, we develop a hierarchical Bayesian model of learning in a general type of artificial language-learning experiment in which learners are exposed to a mixture of grammars representing the variation present in real learners' input, particularly at times of language change. The modeling goal is to formalize and quantify hypothesized…
Ranjana K. Mehta
Full Text Available Standing desks have proven to be effective and viable solutions to combat sedentary behavior among children during the school day in studies around the world. However, little is known regarding the potential of such interventions on cognitive outcomes in children over time. The purpose of this pilot study was to determine the neurocognitive benefits, i.e., improvements in executive functioning and working memory, of stand-biased desks and explore any associated changes in frontal brain function. 34 freshman high school students were recruited for neurocognitive testing at two time points during the school year: (1 in the fall semester and (2 in the spring semester (after 27.57 (1.63 weeks of continued exposure. Executive function and working memory was evaluated using a computerized neurocognitive test battery, and brain activation patterns of the prefrontal cortex were obtained using functional near infrared spectroscopy. Continued utilization of the stand-biased desks was associated with significant improvements in executive function and working memory capabilities. Changes in corresponding brain activation patterns were also observed. These findings provide the first preliminary evidence on the neurocognitive benefits of standing desks, which to date have focused largely on energy expenditure. Findings obtained here can drive future research with larger samples and multiple schools, with comparison groups that may in turn implicate the importance of stand-biased desks, as simple environmental changes in classrooms, on enhancing children’s cognitive functioning that drive their cognitive development and impact educational outcomes.
Coertjens, Liesje; Donche, Vincent; De Maeyer, Sven; Vanthournout, Gert; Van Petegem, Peter
Longitudinal data is almost always burdened with missing data. However, in educational and psychological research, there is a large discrepancy between methodological suggestions and research practice. The former suggests applying sensitivity analysis in order to the robustness of the results in terms of varying assumptions regarding the mechanism generating the missing data. However, in research practice, participants with missing data are usually discarded by relying on listwise deletion. To help bridge the gap between methodological recommendations and applied research in the educational and psychological domain, this study provides a tutorial example of sensitivity analysis for latent growth analysis. The example data concern students' changes in learning strategies during higher education. One cohort of students in a Belgian university college was asked to complete the Inventory of Learning Styles-Short Version, in three measurement waves. A substantial number of students did not participate on each occasion. Change over time in student learning strategies was assessed using eight missing data techniques, which assume different mechanisms for missingness. The results indicated that, for some learning strategy subscales, growth estimates differed between the models. Guidelines in terms of reporting the results from sensitivity analysis are synthesised and applied to the results from the tutorial example.
Chi, Michelene T. H.; And Others
A study examined in detail the initial encoding of worked-out examples of mechanics problems by "good" and "poor" students, and their subsequent reliance on examples during problem solving. The subjects, three males and five females, were selected from responses to a university campus advertisement. Six of them were working…
Lee, Yoonhee Naseef
The goal of this research was to understand the different kinds of learning that take place in "Mod The Sims" (MTS), an online "Sims" gaming community. The study aimed to explore users' experiences and to understand learning practices that are not commonly observed in formal educational settings. To achieve this goal, the…
Curriculum integration is one of the concepts which has been discussed for years. Telecollaborative projects, which employ elements of distance learning, provide opportunities for putting the idea into practice. Analysis of eTwinning projects undertaken in Polish schools aims at demonstrating the integrative role of distance learning approaches…
Tempelaar, Dirk; Rienties, Bart; Nguyen, Quan
The identification of students’ learning strategies by using multi-modal data that combine trace data with self-report data is the prime aim of this study. Our context is an application of dispositional learning analytics in a large introductory course mathematics and statistics, based on blended
Groenwold, Rolf H H; Knol, Mirjam J
Distance learning through the internet is increasingly popular in higher education. However, it is unknown how participants in epidemiology courses value live vs. distance education. All participants of a 5-day specialisation course in epidemiology were asked to keep a diary on the number of hours they spent on course activities (both live and distance education). Attendance was not compulsory during the course and participants were therefore also asked for the reasons to attend live education (lectures and practicals). In addition, the relation between participants' learning styles (Index of Learning Styles) and their participation in live and distance education was studied. All 54 (100%) participants in the course completed the questionnaire on attendance and 46 (85%) completed the questionnaire on learning styles. The number of hours attending live education was negatively correlated with the number of hours going studying distance learning materials (Pearson correlation -0.5; p education was to stay focused during lectures (50%), and to ask questions during practicals (50%). A lack of time was the most important reason not to attend lectures (52%) or practicals (61%). Learning styles were not association with the number of hours spent on live or distance education. Distance learning may play an important role in epidemiology courses, since it allows participants to study whenever and wherever they prefer, which provides the opportunity to combine courses with clinical duties. An important requirement for distance learning education appears to be the possibility to ask questions and to interact with instructors.
Carpenter, Gail A; Gaddam, Sai Chaitanya
Memories in Adaptive Resonance Theory (ART) networks are based on matched patterns that focus attention on those portions of bottom-up inputs that match active top-down expectations. While this learning strategy has proved successful for both brain models and applications, computational examples show that attention to early critical features may later distort memory representations during online fast learning. For supervised learning, biased ARTMAP (bARTMAP) solves the problem of over-emphasis on early critical features by directing attention away from previously attended features after the system makes a predictive error. Small-scale, hand-computed analog and binary examples illustrate key model dynamics. Two-dimensional simulation examples demonstrate the evolution of bARTMAP memories as they are learned online. Benchmark simulations show that featural biasing also improves performance on large-scale examples. One example, which predicts movie genres and is based, in part, on the Netflix Prize database, was developed for this project. Both first principles and consistent performance improvements on all simulation studies suggest that featural biasing should be incorporated by default in all ARTMAP systems. Benchmark datasets and bARTMAP code are available from the CNS Technology Lab Website: http://techlab.bu.edu/bART/. Copyright 2009 Elsevier Ltd. All rights reserved.
Ott, Derek V M; Ullsperger, Markus; Jocham, Gerhard; Neumann, Jane; Klein, Tilmann A
The prefrontal cortex is known to play a key role in higher-order cognitive functions. Recently, we showed that this brain region is active in reinforcement learning, during which subjects constantly have to integrate trial outcomes in order to optimize performance. To further elucidate the role of the dorsolateral prefrontal cortex (DLPFC) in reinforcement learning, we applied continuous theta-burst stimulation (cTBS) either to the left or right DLPFC, or to the vertex as a control region, respectively, prior to the performance of a probabilistic learning task in an fMRI environment. While there was no influence of cTBS on learning performance per se, we observed a stimulation-dependent modulation of reward vs. punishment sensitivity: Left-hemispherical DLPFC stimulation led to a more reward-guided performance, while right-hemispherical cTBS induced a more avoidance-guided behavior. FMRI results showed enhanced prediction error coding in the ventral striatum in subjects stimulated over the left as compared to the right DLPFC. Both behavioral and imaging results are in line with recent findings that left, but not right-hemispherical stimulation can trigger a release of dopamine in the ventral striatum, which has been suggested to increase the relative impact of rewards rather than punishment on behavior. Copyright © 2011 Elsevier Inc. All rights reserved.
Ott, D.V.M.; Ullsperger, M.; Jocham, G.; Neumann, J.; Klein, T.A.
The prefrontal cortex is known to play a key role in higher-order cognitive functions. Recently, we showed that this brain region is active in reinforcement learning, during which subjects constantly have to integrate trial outcomes in order to optimize performance. To further elucidate the role of
Vimmerstedt, Laura J.; Bush, Brian W.; Peterson, Steven O.
This paper (and its supplemental model) presents novel approaches to modeling interactions and related policies among investment, production, and learning in an emerging competitive industry. New biomass-to-biofuels pathways are being developed and commercialized to support goals for U.S. advanced biofuel use, such as those in the Energy Independence and Security Act of 2007. We explore the impact of learning rates and techno-economics in a learning model excerpted from the Biomass Scenario Model (BSM), developed by the U.S. Department of Energy and the National Renewable Energy Laboratory to explore the impact of biofuel policy on the evolution of the biofuels industry. The BSM integrates investment, production, and learning among competing biofuel conversion options that are at different stages of industrial development. We explain the novel methods used to simulate the impact of differing assumptions about mature industry techno-economics and about learning rates while accounting for the different maturity levels of various conversion pathways. A sensitivity study shows that the parameters studied (fixed capital investment, process yield, progress ratios, and pre-commercial investment) exhibit highly interactive effects, and the system, as modeled, tends toward market dominance of a single pathway due to competition and learning dynamics.
I read with interest the comment by Mark Wilson in the Indian Journal of Medical Ethics regarding bias and conflicts of interest in medical journals. Wilson targets one journal (the New England Journal of Medicine: NEJM) and one particular "scandal" to make his point that journals' decisions on publication are biased by commercial conflicts of interest (CoIs). It is interesting that he chooses the NEJM which, by his own admission, had one of the strictest CoI policies and had published widely on this topic. The feeling is that if the NEJM can be guilty, they can all be guilty.
Cher M. Hill
Full Text Available Teacher inquiry, in which teachers study their own professional practice, is currently a popular form of experiential learning that is considered a powerful tool to bring about effective change in teaching and learning. Little empirical evidence, however, exists to explain precisely if and how this pedagogical methodology moves teachers toward transformation of practice. Using grounded theory methodology, we examined twelve end of term graduate level learning portfolios and administered a survey to 336 in-service teachers enrolled in a two-year graduate diploma program in the Faculty of Education at Simon Fraser University, Canada. We found powerful evidence that our programs were highly impactful, with 94% of teachers reporting transformative learning within the second year of the program. Using portfolio data we examined the process of the teacher transformations. Our findings revealed that teachers’ abilities to interrogate their subjective-objective stance deepened their experiential learning. Using three case studies we exemplify how transformative pathways were formulated and conclude with a discussion of the implications of learning through experience, including the value of student-generated learning goals, continuous interfacing of theory and practice, seeing your ‘teaching’ through the eyes of your students/colleagues or parents, and the power of living your research question in the context of your own classroom and school setting. We end the paper on a cautionary note pointing out the vulnerability of programs of this nature in an era of accountability, standardization, quality control, and risk management all of which eclipse approaches that focus on authentic practical problems and student generated solutions.
Donnat, Ph.; Treimany, C.; Gouedard, C.; Morice, O.
This document presents some examples which were used for debugging the code. It seemed useful to write these examples onto a book to be sure the code would not regret; to give warranties for the code's functionality; to propose some examples to illustrate the possibilities and the limits of Miro. (author)
Full Text Available Two problems can be identified which counteract the need for further training: On the one hand the clientele of skilled workers is not necessarily keen on further training. On the other hand the time and cost pressure within the sector does not offer any room for time-consuming further training measures far away from the workplace. This is why the project “Virtual Learning on the building site – (Vila-b” was realized in cooperation with the project partners of the University of Bremen (Working group »Digital Media« of the Centre for Information Technology as well as from the economy (Arbeitskreis ökologischer Holzbau e. V. and Claus Holm, pm|c. The project team has tested a concept which facilitated learning adapted to the occupational reality and supported by the advantages of digital media. The central didactical elements for the development of this further training course are the contextual and methodological orientation to real work processes as well as the use of digital mobile media which facilitate learning directly at the workplace. The present article starts with a description of the theoretical basics for learning within the work process and discusses the didactical elements which are necessary for work process oriented learning with digital and mobile media.
Full Text Available Emerging business requirements, stemming from a holistic view over an organisation’s activities, place additional pressure on technical infrastructures and call for operational agility and a better alignment between business and technology. Business process oriented learning unites corporate training and business process management. Given the importance of an organisation’s human capital to business success, aligning individual training with business priorities, becomes a key challenge. The implementation of this new business service entails integrating learning into daily working tasks and putting in place mechanisms for the effective management of business processes, organisational roles, competencies and learning processes, to reduce the time to fill competency gaps and to build proficiency according to evolving business needs. In this paper we outline the main characteristics of this approach and provide insights regarding the changing role of the involved corporate information systems and the multiple aspects of the integration work.
Full Text Available Curriculum integration is one of the concepts which has been discussed for years. Telecollaborative projects, which employ elements of distance learning, provide opportunities for putting the idea into practice. Analysis of eTwinning projects undertaken in Polish schools aims at demonstrating the integrative role of distance learning approaches and their contribution to integration of various themes in educational context. As the eTwinning framework is very flexible, allowing for teacher and students autonomy the projects may vary in the topics, age and number of participants, duration scope within curriculum etc. The study shows various levels and perspectives of curriculum integration which take place in eTwinning projects. It also discusses the role of distance learning at primary and secondary educational levels. The challenge is to transform international collaboration of selected schools an everyday practice for all learners and teachers.
María Martínez Lirola
Full Text Available Cooperative learning allows students acquisition of competences that are essential for the labour market such as leadership, critical thinking, communication, and so on. For this reason, different cooperative activities were designed in a language subject in English Studies so that students could work in groups and acquire those competences. This article describes some such activities and the emotional competences that students acquire with them. Moreover, a survey was conducted in order to establish students’ opinions about the main competences they acquired with the activities designed and their opinion about a cooperative methodology. Students’ answers were positive and they were aware of what they had learned.
Full Text Available The detection of an error in the motor output and the correction in the next movement are critical components of any form of motor learning. Accordingly, a variety of iterative learning models have assumed that a fraction of the error is adjusted in the next trial. This critical fraction, the correction gain, learning rate, or feedback gain, has been frequently estimated via least-square regression of the obtained data set. Such data contain not only the inevitable noise from motor execution, but also noise from measurement. It is generally assumed that this noise averages out with large data sets and does not affect the parameter estimation. This study demonstrates that this is not the case and that in the presence of noise the conventional estimate of the correction gain has a significant bias, even with the simplest model. Furthermore, this bias does not decrease with increasing length of the data set. This study reveals this limitation of current system identification methods and proposes a new method that overcomes this limitation. We derive an analytical form of the bias from a simple regression method (Yule-Walker and develop an improved identification method. This bias is discussed as one of other examples for how the dynamics of noise can introduce significant distortions in data analysis.
van Veen, Saskia C.; de Wildt-Liesveld, Renée; Bunders, Joske F. G.; Regeer, Barbara J.
Change processes are increasingly seen as the solution to entrenched (social) problems. However, change is difficult to realise while dealing with multiple actors, values, and approaches. (Inter)organisational learning is seen as a way to facilitate reflective practices in social change that support emergent changes, vicarious learning, and…
Josse Delfgaauw; Michiel Souverijn
markdownabstract__Abstract__ When verifiable performance measures are imperfect, organizations often resort to subjective performance pay. This may give supervisors the power to direct employees towards tasks that mainly benefit the supervisor rather than the organization. We cast a principal-supervisor-agent model in a multitask setting, where the supervisor has an intrinsic preference towards specific tasks. We show that subjective performance pay based on evaluation by a biased supervisor ...
Henry, S.; Fureix, C.; Rowberry, R.; Bateson, M.; Hausberger, M.
This field study tested the hypothesis that domestic horses living under putatively challenging-to-welfare conditions (for example involving social, spatial, feeding constraints) would present signs of poor welfare and co-occurring pessimistic judgement biases. Our subjects were 34 horses who had been housed for over 3 years in either restricted riding school situations ( e.g. kept in single boxes, with limited roughage, ridden by inexperienced riders; N = 25) or under more naturalistic conditions ( e.g. access to free-range, kept in stable social groups, leisure riding; N = 9). The horses' welfare was assessed by recording health-related, behavioural and postural indicators. Additionally, after learning a location task to discriminate a bucket containing either edible food (`positive' location) or unpalatable food (`negative' location), the horses were presented with a bucket located near the positive position, near the negative position and halfway between the positive and negative positions to assess their judgement biases. The riding school horses displayed the highest levels of behavioural and health-related problems and a pessimistic judgment bias, whereas the horses living under more naturalistic conditions displayed indications of good welfare and an optimistic bias. Moreover, pessimistic bias data strongly correlated with poor welfare data. This suggests that a lowered mood impacts a non-human species' perception of its environment and highlights cognitive biases as an appropriate tool to assess the impact of chronic living conditions on horse welfare.
Henry, S; Fureix, C; Rowberry, R; Bateson, M; Hausberger, M
This field study tested the hypothesis that domestic horses living under putatively challenging-to-welfare conditions (for example involving social, spatial, feeding constraints) would present signs of poor welfare and co-occurring pessimistic judgement biases. Our subjects were 34 horses who had been housed for over 3 years in either restricted riding school situations (e.g. kept in single boxes, with limited roughage, ridden by inexperienced riders; N = 25) or under more naturalistic conditions (e.g. access to free-range, kept in stable social groups, leisure riding; N = 9). The horses' welfare was assessed by recording health-related, behavioural and postural indicators. Additionally, after learning a location task to discriminate a bucket containing either edible food ('positive' location) or unpalatable food ('negative' location), the horses were presented with a bucket located near the positive position, near the negative position and halfway between the positive and negative positions to assess their judgement biases. The riding school horses displayed the highest levels of behavioural and health-related problems and a pessimistic judgment bias, whereas the horses living under more naturalistic conditions displayed indications of good welfare and an optimistic bias. Moreover, pessimistic bias data strongly correlated with poor welfare data. This suggests that a lowered mood impacts a non-human species' perception of its environment and highlights cognitive biases as an appropriate tool to assess the impact of chronic living conditions on horse welfare.
Bublitz, Bruce; Philipich, Kirk; Blatz, Robert
The purpose of this teaching note is to describe an experiential learning exercise used in a master's level financial accounting theory course. The experiential exercise illustrates how order effects can affect user's judgments, a long-standing research finding. This experiential exercise was used in an attempt to make students more cognizant of…
de los Santos, Desiree´ M.; Montes, Antonio; Sa´nchez-Coronilla, Antonio; Navas, Javier
A Project Based Learning (PBL) methodology was used in the practical laboratories of the Advanced Physical Chemistry department. The project type proposed simulates "real research" focusing on sol-gel synthesis and the application of the obtained sol as a stone consolidant. Students were divided into small groups (2 to 3 students) to…
Stacey, Kaye; Price, Beth; Steinle, Vicki
This paper discusses issues arising in the design of questions to use in an on-line computer-based formative assessment system, focussing on how best to identify the stages of a learning hierarchy for reporting to teachers. Data from several hundred students is used to illustrate how design decisions have been made for a test on interpreting line…
Martínez Lirola, María
Cooperative learning allows students acquisition of competences that are essential for the labour market such as leadership, critical thinking, communication, and so on. For this reason, different cooperative activities were designed in a language subject in English Studies so that students could work in groups and acquire those competences. This…
An organisational change-process in a UK local authority (LA) over two years is examined using transcribed excerpts from three meetings. The change-process is analysed using a Foucauldian analytical tool--Iterative Learning Conversations (ILCS). An Educational Psychology Service was changed from being primarily an education-focussed…
An overlapping generations model is an applied dynamic general equilibrium model for which the lifecycle models are employed as main analytical tools. At any point in time, there are overlapping generations consisting of individuals born this year, individuals born last year, individuals born two years ago, and so on. As we saw in the analysis of lifecycle models, each individual makes an optimal consumption-saving plan to maximize lifetime utility over her/his lifecycle. For example, an indi...
The essay focuses on the area of Brescia where, in spite of significant transformations over time of buildings and territory, many examples of traditional architecture still exist. The aim of the paper is also to suggest, by presenting some case studies, a strategy for conservation which proposes a dialogue between traditional methods, technological innovations and economic sustainability of interventions. Keywords: Traditional architecture, Brescia, Sustainability, Construction techniques, Protection
The presentation focused on an so called integrated mixed method research design example on a basis of a Czech Science Foundation Project Nr. GAP407/12/0432 "Foreign Language Learning Strategies and Achievement: Analysis of Strategy Clusters and Sequences". All main integrated parts of the mixed methods research design were discussed: the aim, theoretical framework, research question, methods and validity threats. Prezentace se zaměřovala na tzv. integrovaný vícemetodový výzkumný design na...
Rasner, P I; Pushkar', D Iu; Kolontarev, K B; Kotenkov, D V
The appearance of new surgical technique always requires evaluation of its effectiveness and ease of acquisition. A comparative study of the results of the first three series of successive robot-assisted radical prostatectomy (RARP) performed on at time by three surgeons, was conducted. The series consisted of 40 procedures, and were divided into 4 groups of 10 operations for the analysis. When comparing data, statistically significant improvement of intra- and postoperative performance in each series was revealed, with increase in the number of operations performed, and in each subsequent series compared with the preceding one. We recommend to perform the planned conversion at the first operation. In our study, previous laparoscopic experience did not provide any significant advantages in the acquisition of robot-assisted technology. To characterize the individual learning curve, we recommend the use of the number of operations that the surgeon looked in the life-surgery regimen and/or in which he participated as an assistant before his own surgical activity, as well as the indicator "technical defect". In addition to the term "individual learning curve", we propose to introduce the terms "surgeon's individual training phase", and "clinic's learning curve".
Roberts, Gareth; Fedzechkina, Maryia
According to the competitive exclusion principle (Gause, 1934), competition for the same niche must eventually lead one competitor to extinction or the occupation of a new niche. This principle applies in both biology and the cultural evolution of language, where different words and structures compete for the same function or meaning (Aronoff, 2016). Across languages, for example, word order trades off with case marking as a means of indicating who did what to whom in a sentence. Previous experimental work has shed light on how such trade-offs come about as languages adapt to human biases through learning and production, with biases becoming amplified through iterated learning over generations. At the same time, a large body of work has documented the impact of social biases on language change. However, little work has investigated how social biases interact with learning and production biases. In particular, the social dimension of language may provide alternative niches for otherwise redundant forms, preventing or slowing their extinction. We tested this hypothesis in an iterated-learning experiment in which participants were exposed to a language with two dialects, both of which had fixed word order, but differed in whether they employed case markers. In one condition, we biased participants socially towards speakers of the dialect that employed case; in other conditions we provided no bias, or biased participants for or against the dialect without case. As expected under our hypothesis, the use of case markers declined over time in all conditions, but the social bias in favor of case-dialect speakers slowed the decline. Copyright © 2017 Elsevier B.V. All rights reserved.
Schwartz, Sharon; Campbell, Ulka B; Gatto, Nicolle M; Gordon, Kirsha
Epidemiology textbooks typically divide biases into 3 general categories-confounding, selection bias, and information bias. Despite the ubiquity of this categorization, authors often use these terms to mean different things. This hinders communication among epidemiologists and confuses students who are just learning about the field. To understand the sources of this problem, we reviewed current general epidemiology textbooks to examine how the authors defined and categorized biases. We found that much of the confusion arises from different definitions of "validity" and from a mixing of 3 overlapping organizational features in defining and differentiating among confounding, selection bias, and information bias: consequence, the result of the problem; cause, the processes that give rise to the problem; and cure, how these biases can be addressed once they occur. By contrast, a consistent taxonomy would provide (1) a clear and consistent definition of what unites confounding, selection bias, and information bias and (2) a clear articulation and consistent application of the feature that distinguishes these categories. Based on a distillation of these textbook discussions, we provide an example of a taxonomy that we think meets these criteria.
Lyon, S. W.; Walter, M. T.; Jantze, E. J.; Archibald, J. A.
Structuring an education strategy capable of addressing the various spheres of ecohydrology is difficult due to the inter-disciplinary and cross-disciplinary nature of this emergent field. Clearly, there is a need for such strategies to accommodate more progressive educational concepts while highlighting a skills-based education. To demonstrate a possible way to develop courses that include such concepts, we offer a case-study or a "how-you-can-do-it" example from an ecohydrology course recently co-taught by teachers from Stockholm University and Cornell University at the Navarino Environmental Observatory (NEO) in Costa Navarino, Greece. This course focused on introducing hydrology Master's students to some of the central concepts of ecohydrology while at the same time supplying process-based understanding relevant for characterizing evapotranspiration. As such, the main goal of the course was to explore central theories in ecohydrology and their connection to plant-water interactions and the water cycle in a semiarid environment. In addition to presenting this roadmap for ecohydrology course development, we explore the utility and effectiveness of adopting active teaching and learning strategies drawing from the suite of learn-by-doing, hands-on, and inquiry-based techniques in such a course. We test a gradient of "activeness" across a sequence of three teaching and learning activities. Our results indicate that there was a clear advantage for utilizing active learning techniques in place of traditional lecture-based styles. In addition, there was a preference among the student towards the more "active" techniques. This demonstrates the added value of incorporating even the simplest active learning approaches in our ecohydrology (or general) teaching.
National Aeronautics and Space Administration — This is a textbook, created example for illustration purposes. The System takes inputs of Pt, Ps, and Alt, and calculates the Mach number using the Rayleigh Pitot...
Guo, Ashley Z.; Sevgen, Emre; Sidky, Hythem; Whitmer, Jonathan K.; Hubbell, Jeffrey A.; de Pablo, Juan J.
A machine learning assisted method is presented for molecular simulation of systems with rugged free energy landscapes. The method is general and can be combined with other advanced sampling techniques. In the particular implementation proposed here, it is illustrated in the context of an adaptive biasing force approach where, rather than relying on discrete force estimates, one can resort to a self-regularizing artificial neural network to generate continuous, estimated generalized forces. By doing so, the proposed approach addresses several shortcomings common to adaptive biasing force and other algorithms. Specifically, the neural network enables (1) smooth estimates of generalized forces in sparsely sampled regions, (2) force estimates in previously unexplored regions, and (3) continuous force estimates with which to bias the simulation, as opposed to biases generated at specific points of a discrete grid. The usefulness of the method is illustrated with three different examples, chosen to highlight the wide range of applicability of the underlying concepts. In all three cases, the new method is found to enhance considerably the underlying traditional adaptive biasing force approach. The method is also found to provide improvements over previous implementations of neural network assisted algorithms.
Pedersen, Kamilla; Moeller, Martin Holdgaard; Paltved, Charlotte; Mors, Ole; Ringsted, Charlotte; Morcke, Anne Mette
The aim of this study was to explore medical students' learning experiences from the didactic teaching formats using either text-based patient cases or video-based patient cases with similar content. The authors explored how the two different patient case formats influenced students' perceptions of psychiatric patients and students' reflections on meeting and communicating with psychiatric patients. The authors conducted group interviews with 30 medical students who volunteered to participate in interviews and applied inductive thematic content analysis to the transcribed interviews. Students taught with text-based patient cases emphasized excitement and drama towards the personal clinical narratives presented by the teachers during the course, but never referred to the patient cases. Authority and boundary setting were regarded as important in managing patients. Students taught with video-based patient cases, in contrast, often referred to the patient cases when highlighting new insights, including the importance of patient perspectives when communicating with patients. The format of patient cases included in teaching may have a substantial impact on students' patient-centeredness. Video-based patient cases are probably more effective than text-based patient cases in fostering patient-centered perspectives in medical students. Teachers sharing stories from their own clinical experiences stimulates both engagement and excitement, but may also provoke unintended stigma and influence an authoritative approach in medical students towards managing patients in clinical psychiatry.
Wei, Jun; Jiang, Guo-Qing; Liu, Xin
This study proposed three algorithms that can potentially be used to provide sea surface temperature (SST) conditions for typhoon prediction models. Different from traditional data assimilation approaches, which provide prescribed initial/boundary conditions, our proposed algorithms aim to resolve a flow-dependent SST feedback between growing typhoons and oceans in the future time. Two of these algorithms are based on linear temperature equations (TE-based), and the other is based on an innovative technique involving machine learning (ML-based). The algorithms are then implemented into a Weather Research and Forecasting model for the simulation of typhoon to assess their effectiveness, and the results show significant improvement in simulated storm intensities by including ocean cooling feedback. The TE-based algorithm I considers wind-induced ocean vertical mixing and upwelling processes only, and thus obtained a synoptic and relatively smooth sea surface temperature cooling. The TE-based algorithm II incorporates not only typhoon winds but also ocean information, and thus resolves more cooling features. The ML-based algorithm is based on a neural network, consisting of multiple layers of input variables and neurons, and produces the best estimate of the cooling structure, in terms of its amplitude and position. Sensitivity analysis indicated that the typhoon-induced ocean cooling is a nonlinear process involving interactions of multiple atmospheric and oceanic variables. Therefore, with an appropriate selection of input variables and neuron sizes, the ML-based algorithm appears to be more efficient in prognosing the typhoon-induced ocean cooling and in predicting typhoon intensity than those algorithms based on linear regression methods.
Yunarto, Wanda Nugroho
Abstrak Example and Non-Example Learning Model merupakan model pembelajaran yang menggunakan gambar sebagai media pembelajaran yang bertujuan mendorong mahasiswa untuk belajar berfikir kritis dengan jalan memecahkan permasalahan-permasalahan yang terkandung dalam contoh-contoh permasalahan/ konsep yang disajikan. Tujuan dari penelitian ini adalah mendapatkan gambaran mengenai bagaimana penerapan model pembelajaran Example and non-Example pada mahasiswa program studi Pendidikan Matematika Univ...
Feb 24, 2016 ... suggested that codon usage bias is driven by selection, particularly for .... For example, as mentioned above, highly expressed genes tend to use fewer ... directional codon bias measure effective number of codons (ENc) was ...
Cislak, Aleksandra; Formanowicz, Magdalena; Saguy, Tamar
The bias against women in academia is a documented phenomenon that has had detrimental consequences, not only for women, but also for the quality of science. First, gender bias in academia affects female scientists, resulting in their underrepresentation in academic institutions, particularly in higher ranks. The second type of gender bias in science relates to some findings applying only to male participants, which produces biased knowledge. Here, we identify a third potentially powerful source of gender bias in academia: the bias against research on gender bias. In a bibliometric investigation covering a broad range of social sciences, we analyzed published articles on gender bias and race bias and established that articles on gender bias are funded less often and published in journals with a lower Impact Factor than articles on comparable instances of social discrimination. This result suggests the possibility of an underappreciation of the phenomenon of gender bias and related research within the academic community. Addressing this meta-bias is crucial for the further examination of gender inequality, which severely affects many women across the world.
Braithwaite, David W.; Siegler, Robert S.
Many students' knowledge of fractions is adversely affected by whole number bias, the tendency to focus on the separate whole number components (numerator and denominator) of a fraction rather than on the fraction's magnitude (ratio of numerator to denominator). Although whole number bias appears early in the fraction learning process and under…
Börstler, Jürgen; Christensen, Henrik Bærbak; Bennedsen, Jens
Example programs play an important role in learning to program. They work as templates, guidelines, and inspiration for learners when developing their own programs. It is therefore important to provide learners with high quality examples. In this paper, we discuss properties of example programs...... that might affect the teaching and learning of object-oriented programming. Furthermore, we present an evaluation instrument for example programs and report on initial experiences of its application to a selection of examples from popular introductory programming textbooks....
Howard, Ayanna; Borenstein, Jason
Recently, there has been an upsurge of attention focused on bias and its impact on specialized artificial intelligence (AI) applications. Allegations of racism and sexism have permeated the conversation as stories surface about search engines delivering job postings for well-paying technical jobs to men and not women, or providing arrest mugshots when keywords such as "black teenagers" are entered. Learning algorithms are evolving; they are often created from parsing through large datasets of online information while having truth labels bestowed on them by crowd-sourced masses. These specialized AI algorithms have been liberated from the minds of researchers and startups, and released onto the public. Yet intelligent though they may be, these algorithms maintain some of the same biases that permeate society. They find patterns within datasets that reflect implicit biases and, in so doing, emphasize and reinforce these biases as global truth. This paper describes specific examples of how bias has infused itself into current AI and robotic systems, and how it may affect the future design of such systems. More specifically, we draw attention to how bias may affect the functioning of (1) a robot peacekeeper, (2) a self-driving car, and (3) a medical robot. We conclude with an overview of measures that could be taken to mitigate or halt bias from permeating robotic technology.
Full Text Available Textbook has a strong influence on the formation of children’s attitudes and value system. Therefore, Islamic textbooks as the main learning source for Muslim children in Indonesia need to consider the gender equality. This is very important to note, because feminists often view that Islam contains teachings of gender inequality. Islam places men in the higher position, while women are placed in the lower position. For example, men can be imam for women in prayer, but women cannot be imam for men. It is easier for children to learn textbook material presented in pictures. Therefore, the pictures presented in Islamic textbooks ideally do not contain gender bias. So, a research is needed to know if there is gender bias in the pictures presented in Islamic textbooks taught to Muslim children in Indonesia. To prove it, a literary research is conducted on the Islamic textbooks taught to the first grade Muslim student of Islamic Elementary School/ Madrasah Ibtidaiyah (MI in Indonesia which includes pictures in their teaching materials. Islamic textbooks studied in the research include Fikih, Akidah Akhlak, and Arabic textbooks. The results of this study conclude that the pictures presented in Islamic textbooks taught in Muslim children in Indonesia contain gender bias. The man favor pictures are more than those of woman favor. Based on the conclusion, this study recommends an improvement of pictures presented in Islamic textbooks taught to Muslim children in Indonesia.
Cox, Louis Anthony Tony
Decision biases can distort cost-benefit evaluations of uncertain risks, leading to risk management policy decisions with predictably high retrospective regret. We argue that well-documented decision biases encourage learning aversion, or predictably suboptimal learning and premature decision making in the face of high uncertainty about the costs, risks, and benefits of proposed changes. Biases such as narrow framing, overconfidence, confirmation bias, optimism bias, ambiguity aversion, and hyperbolic discounting of the immediate costs and delayed benefits of learning, contribute to deficient individual and group learning, avoidance of information seeking, underestimation of the value of further information, and hence needlessly inaccurate risk-cost-benefit estimates and suboptimal risk management decisions. In practice, such biases can create predictable regret in selection of potential risk-reducing regulations. Low-regret learning strategies based on computational reinforcement learning models can potentially overcome some of these suboptimal decision processes by replacing aversion to uncertain probabilities with actions calculated to balance exploration (deliberate experimentation and uncertainty reduction) and exploitation (taking actions to maximize the sum of expected immediate reward, expected discounted future reward, and value of information). We discuss the proposed framework for understanding and overcoming learning aversion and for implementing low-regret learning strategies using regulation of air pollutants with uncertain health effects as an example. © 2015 Society for Risk Analysis.
Gates, Allison; Vandermeer, Ben; Hartling, Lisa
To evaluate the reliability of RobotReviewer's risk of bias judgments. In this prospective cross-sectional evaluation, we used RobotReviewer to assess risk of bias among 1,180 trials. We computed reliability with human reviewers using Cohen's kappa coefficient and calculated sensitivity and specificity. We investigated differences in reliability by risk of bias domain, topic, and outcome type using the chi-square test in meta-analysis. Reliability (95% CI) was moderate for random sequence generation (0.48 [0.43, 0.53]), allocation concealment (0.45 [0.40, 0.51]), and blinding of participants and personnel (0.42 [0.36, 0.47]); fair for overall risk of bias (0.34 [0.25, 0.44]); and slight for blinding of outcome assessors (0.10 [0.06, 0.14]), incomplete outcome data (0.14 [0.08, 0.19]), and selective reporting (0.02 [-0.02, 0.05]). Reliability for blinding of participants and personnel (P < 0.001), blinding of outcome assessors (P = 0.005), selective reporting (P < 0.001), and overall risk of bias (P < 0.001) differed by topic. Sensitivity and specificity (95% CI) ranged from 0.20 (0.18, 0.23) to 0.76 (0.72, 0.80) and from 0.61 (0.56, 0.65) to 0.95 (0.93, 0.96), respectively. Risk of bias appraisal is subjective. Compared with reliability between author groups, RobotReviewer's reliability with human reviewers was similar for most domains and better for allocation concealment, blinding of participants and personnel, and overall risk of bias. Copyright © 2018 Elsevier Inc. All rights reserved.
Ayars, Alisabeth; Nichols, Shaun
Previous studies on rule learning show a bias in favor of act-based rules, which prohibit intentionally producing an outcome but not merely allowing the outcome. Nichols, Kumar, Lopez, Ayars, and Chan (2016) found that exposure to a single sample violation in which an agent intentionally causes the outcome was sufficient for participants to infer that the rule was act-based. One explanation is that people have an innate bias to think rules are act-based. We suggest an alternative empiricist account: since most rules that people learn are act-based, people form an overhypothesis (Goodman, 1955) that rules are typically act-based. We report three studies that indicate that people can use information about violations to form overhypotheses about rules. In study 1, participants learned either three "consequence-based" rules that prohibited allowing an outcome or three "act-based" rules that prohibiting producing the outcome; in a subsequent learning task, we found that participants who had learned three consequence-based rules were more likely to think that the new rule prohibited allowing an outcome. In study 2, we presented participants with either 1 consequence-based rule or 3 consequence-based rules, and we found that those exposed to 3 such rules were more likely to think that a new rule was also consequence based. Thus, in both studies, it seems that learning 3 consequence-based rules generates an overhypothesis to expect new rules to be consequence-based. In a final study, we used a more subtle manipulation. We exposed participants to examples act-based or accident-based (strict liability) laws and then had them learn a novel rule. We found that participants who were exposed to the accident-based laws were more likely to think a new rule was accident-based. The fact that participants' bias for act-based rules can be shaped by evidence from other rules supports the idea that the bias for act-based rules might be acquired as an overhypothesis from the
To find the secrets of business success, what could be more natural than studying successful businesses? In fact, nothing could be more dangerous, warns this Stanford professor. Generalizing from the examples of successful companies is like generalizing about New England weather from data taken only in the summer. That's essentially what businesspeople do when they learn from good examples and what consultants, authors, and researchers do when they study only existing companies or--worse yet--only high-performing companies. They reach conclusions from unrepresentative data samples, falling into the classic statistical trap of selection bias. Drawing on a wealth of case studies, for instance, one researcher concluded that great leaders share two key traits: They persist, often despite initial failures, and they are able to persuade others to join them. But those traits are also the hallmarks of spectacularly unsuccessful entrepreneurs, who must persist in the face of failure to incur large losses and must be able to persuade others to pour their money down the drain. To discover what makes a business successful, then, managers should look at both successes and failures. Otherwise, they will overvalue risky business practices, seeing only those companies that won big and not the ones that lost dismally. They will not be able to tell if their current good fortune stems from smart business practices or if they are actually coasting on past accomplishments or good luck. Fortunately, economists have developed relatively simple tools that can correct for selection bias even when data about failed companies are hard to come by. Success may be inspirational, but managers are more likely to find the secrets of high performance if they give the stories of their competitors'failures as full a hearing as they do the stories of dazzling successes.
Lowry, Michael R.
This paper describes a rational reconstruction of Einstein's discovery of special relativity, validated through an implementation: the Erlanger program. Einstein's discovery of special relativity revolutionized both the content of physics and the research strategy used by theoretical physicists. This research strategy entails a mutual bootstrapping process between a hypothesis space for biases, defined through different postulated symmetries of the universe, and a hypothesis space for physical theories. The invariance principle mutually constrains these two spaces. The invariance principle enables detecting when an evolving physical theory becomes inconsistent with its bias, and also when the biases for theories describing different phenomena are inconsistent. Structural properties of the invariance principle facilitate generating a new bias when an inconsistency is detected. After a new bias is generated. this principle facilitates reformulating the old, inconsistent theory by treating the latter as a limiting approximation. The structural properties of the invariance principle can be suitably generalized to other types of biases to enable primal-dual learning.
Szymenderski, Peggy; Yagudina, Liliya; Burenkova, Olga
In this paper we consider the question of how quality assurance can have a real, positive impact on the quality of teaching and learning at universities, considering the realities of different systems--the system of control and the system of quality culture--in using the example of two universities: the KNITU-KAI in Russia and the TU Dresden in…
Pugh, Greg L.
The pink triangle exercise is an example of an experiential learning exercise that creates cognitive dissonance and deep learning of unrealized internalized biases among social work students. Students wear a button with a pink triangle on it for 1 day and write a reflection paper. The exercise increases self-awareness, cultural competence, and the…
dr. Pierre Gorissen
This document consists of an example of a Learning Design based on the What is Greatness example originally created by James Dalziel from WebMCQ using LAMS. Note: The example has been created in parallel with the actual development of the Alfanet system. So no claims can be made that the example
Howard, K. L.; Suchy-Mabrouk, A.; Noble, P. J.; Mensing, S. A.; Ewing-Taylor, J.
A growing need for broad dissemination of current scientific research and improved scientific literacy requires new models of professional development that allow for direct collaboration between educators and university researchers. One example is a project funded by the National Science Foundation (NSF) as part of a study titled, "Reconstructing 2500 years of environmental change at the periphery of Rome: Integrating paleoecology and socioeconomic history to understand human response to climate." This project involves a team of middle school teachers working with researchers at the University of Nevada, Reno (UNR) to gain first-hand knowledge in multidisciplinary research connecting science and society, and applies a similar approach in the classroom. In 2013, the team's science teacher traveled to Italy as a member of the science research group. A series of workshops introduced the remaining teachers to the research project. Teachers collaborated to develop a Project Based Learning (PBL) unit that incorporated Next Generation Science Standards and encompassed English, Social Studies, Math, and Science curricula using a pedagogical approach different from the single subject-based PBL's usually taught in their school district. The PBL unit draws on the NSF study and focuses on exploring the balance between economic and environmental issues surrounding local wetlands. In May 2014, 160 middle school students worked in groups to create and test a question about physio-chemical parameters in a nearby wetland and used these data to discuss local economic development. Initially, students claimed polarized views of environmental issues or economic development interests; however, during a multimedia session showcasing results, students communicated more informed perspectives that clearly incorporated knowledge gained from their own research. Some students were able to make recommendations for good practices involving planned economic development near the wetland
Most of the literature on combination of forecasts deals with the assumption of unbiased individual forecasts. Here, we consider the case of biased forecasts and discuss two different combination techniques resulting in an unbiased forecast. On the one hand we correct the individual forecasts, and on the other we calculate bias based weights. A simulation study gives some insight in the situations where we should use the different methods.
Olesia L. Dyshko; Tetiana V. Zubekhina; Nataliia B. Pavlyshyna
The article analyzes the state of implementation of information and communication technologies (ICT) in the organization of e-learning in higher education (using the experience of specialities «Tourism» and «Social Work»). The urgency of e-learning technologies application and related information and communication technologies is proved. Author determined the advantages and disadvantages of the popular platform Moodle e-learning. The results of research on active use of ICT, e-learning platfo...
The studies on autonomous learning based on the theories of constructivism and the advantages of technology propose valuable ideas for modern teaching theories and practices. In this paper, we put forward ways and methods in developing learner awareness, learning strategies and habits of autonomous learning in Henan College of Finance and Taxation…
Journal of Genetics, Vol. 83, No. 2, August 2004. Keywords. codon bias; alcohol dehydrogenase; Darwinian ... RESEARCH COMMENTARY. Benefits of being biased! SUTIRTH DEY*. Evolutionary Biology Laboratory, Evolutionary & Organismal Biology Unit,. Jawaharlal Nehru Centre for Advanced Scientific Research,.
Y. Mahendra Singh, M. R. Singh
Common fixed point results due to Pant et al. [Pant et al., Weak reciprocal continuity and fixed point theorems, Ann Univ Ferrara, 57(1), 181-190 (2011)] are extended to a class of non commuting operators called occasionally weakly biased pair[ N. Hussain, M. A. Khamsi A. Latif, Commonfixed points for JH-operators and occasionally weakly biased pairs under relaxed conditions, Nonlinear Analysis, 74, 2133-2140 (2011)]. We also provideillustrative examples to justify the improvements. Abstract....
Abrahamyan, Arman; Silva, Laura Luz; Dakin, Steven C; Carandini, Matteo; Gardner, Justin L
When making choices under conditions of perceptual uncertainty, past experience can play a vital role. However, it can also lead to biases that worsen decisions. Consistent with previous observations, we found that human choices are influenced by the success or failure of past choices even in a standard two-alternative detection task, where choice history is irrelevant. The typical bias was one that made the subject switch choices after a failure. These choice history biases led to poorer performance and were similar for observers in different countries. They were well captured by a simple logistic regression model that had been previously applied to describe psychophysical performance in mice. Such irrational biases seem at odds with the principles of reinforcement learning, which would predict exquisite adaptability to choice history. We therefore asked whether subjects could adapt their irrational biases following changes in trial order statistics. Adaptability was strong in the direction that confirmed a subject's default biases, but weaker in the opposite direction, so that existing biases could not be eradicated. We conclude that humans can adapt choice history biases, but cannot easily overcome existing biases even if irrational in the current context: adaptation is more sensitive to confirmatory than contradictory statistics.
E.R. (Else) Kuiper; M.W. (Martijn) Hartog; T. (Thomas) Fischer; W. (Wolf) Hilzensauer; J. (Joe) Cullen
Background and aims of Links-up Links-up is a two-year research project that is co-financed by the Lifelong Learning programme of the European Commission. The project started in November 2009 and is carried out by an international project team: The project co-coordinator University of Erlangen
Olesia L. Dyshko
Full Text Available The article analyzes the state of implementation of information and communication technologies (ICT in the organization of e-learning in higher education (using the experience of specialities «Tourism» and «Social Work». The urgency of e-learning technologies application and related information and communication technologies is proved. Author determined the advantages and disadvantages of the popular platform Moodle e-learning. The results of research on active use of ICT, e-learning platforms, choice of ICT-based survey of the Ukrainian higher educational institutions that provide teaching training courses in specialities «Tourism» and» «Social work» are presented. It has been found that teachers prefer e-learning platforms, various Internet sites, multimedia presentations, video software Skype and Viber.
Colbeck, Roger; Kent, Adrian
Alice is a charismatic quantum cryptographer who believes her parties are unmissable; Bob is a (relatively) glamorous string theorist who believes he is an indispensable guest. To prevent possibly traumatic collisions of self-perception and reality, their social code requires that decisions about invitation or acceptance be made via a cryptographically secure variable-bias coin toss (VBCT). This generates a shared random bit by the toss of a coin whose bias is secretly chosen, within a stipulated range, by one of the parties; the other party learns only the random bit. Thus one party can secretly influence the outcome, while both can save face by blaming any negative decisions on bad luck. We describe here some cryptographic VBCT protocols whose security is guaranteed by quantum theory and the impossibility of superluminal signaling, setting our results in the context of a general discussion of secure two-party computation. We also briefly discuss other cryptographic applications of VBCT
Colbeck, Roger; Kent, Adrian
Alice is a charismatic quantum cryptographer who believes her parties are unmissable; Bob is a (relatively) glamorous string theorist who believes he is an indispensable guest. To prevent possibly traumatic collisions of self-perception and reality, their social code requires that decisions about invitation or acceptance be made via a cryptographically secure variable-bias coin toss (VBCT). This generates a shared random bit by the toss of a coin whose bias is secretly chosen, within a stipulated range, by one of the parties; the other party learns only the random bit. Thus one party can secretly influence the outcome, while both can save face by blaming any negative decisions on bad luck. We describe here some cryptographic VBCT protocols whose security is guaranteed by quantum theory and the impossibility of superluminal signaling, setting our results in the context of a general discussion of secure two-party computation. We also briefly discuss other cryptographic applications of VBCT.
Van Gog, Tamara; Kester, Liesbeth; Paas, Fred
Van Gog, T., Kester, L., & Paas, F. (2010, August). Effects of worked examples, example-problem pairs, and problem-example pairs compared to problem solving. Paper presented at the Biannual EARLI SIG meeting of Instructional design and Learning and instruction with computers, Ulm, Germany.
Full Text Available We estimate the CPI bias in Korea by employing the approach of Engel’s Law as suggested by Hamilton (2001. This paper is the first attempt to estimate the bias using Korean panel data, Korean Labor and Income Panel Study(KLIPS. Following Hamilton’s model with nonlinear specification correction, our estimation result shows that the cumulative CPI bias over the sample period (2000-2005 was 0.7 percent annually. This CPI bias implies that about 21 percent of the inflation rate during the period can be attributed to the bias. In light of purchasing power parity, we provide an interpretation of the estimated bias.
Olga R. Chepyuk; Anton O. Shalyminov
This article discusses the possibility of organizing a practice-based learning using modern web-based technologies of distance learning like cMOOC. The authors share their experience of practical implementation of proprietary technology in the organization of a University course of innovative entrepreneurship. Based on their practice results authors propose the concept of a new generation of educational platforms based on the four vectors of development.
Olga R. Chepyuk
Full Text Available This article discusses the possibility of organizing a practice-based learning using modern web-based technologies of distance learning like cMOOC. The authors share their experience of practical implementation of proprietary technology in the organization of a University course of innovative entrepreneurship. Based on their practice results authors propose the concept of a new generation of educational platforms based on the four vectors of development.
Mao, Yao-Yuan; Zentner, Andrew R.; Wechsler, Risa H.
Secondary halo bias, commonly known as `assembly bias', is the dependence of halo clustering on a halo property other than mass. This prediction of the Λ Cold Dark Matter cosmology is essential to modelling the galaxy distribution to high precision and interpreting clustering measurements. As the name suggests, different manifestations of secondary halo bias have been thought to originate from halo assembly histories. We show conclusively that this is incorrect for cluster-size haloes. We present an up-to-date summary of secondary halo biases of high-mass haloes due to various halo properties including concentration, spin, several proxies of assembly history, and subhalo properties. While concentration, spin, and the abundance and radial distribution of subhaloes exhibit significant secondary biases, properties that directly quantify halo assembly history do not. In fact, the entire assembly histories of haloes in pairs are nearly identical to those of isolated haloes. In general, a global correlation between two halo properties does not predict whether or not these two properties exhibit similar secondary biases. For example, assembly history and concentration (or subhalo abundance) are correlated for both paired and isolated haloes, but follow slightly different conditional distributions in these two cases. This results in a secondary halo bias due to concentration (or subhalo abundance), despite the lack of assembly bias in the strict sense for cluster-size haloes. Due to this complexity, caution must be exercised in using any one halo property as a proxy to study the secondary bias due to another property.
This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/IPython notebooks, which are provided as supplementary downloads. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Modern Python modules like Pandas, Sympy, and Scikit-learn are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowl...
This documents Phase 1 determinations on sampler induced bias for four sampler types used in tank characterization. Each sampler, grab sampler or bottle-on-a-string, auger sampler, sludge sampler and universal sampler, is briefly discussed and their physical limits noted. Phase 2 of this document will define additional testing and analysis to further define Sampler Bias
Department of the Army position unless so designated by other authorized documents. Citation of manufacturer’s or trade names does not constitute an... Interior view of the photovoltaic bias generator showing wrapped-wire side of circuit board...3 Fig. 4 Interior view of the photovoltaic bias generator showing component side of circuit board
On what grounds can we conclude that an act of categorization is biased? In this chapter, it is contended that in the absence of objective norms of what categories actually are, biases in categorization can only be specified in relation to theoretical understandings of categorization. Therefore, the
Eilks, Ingo; Witteck, Torsten; Pietzner, Verena
This paper discusses what chemistry students might see while working with animations found on the Internet and how these electronic illustrations can potentially interact to reinforce rather than resolve misconceptions about chemical principles that a student may possess. The Daniell voltaic cell serves as an example to illustrate the ways in…
James G. MacKinnon; Anthony A. Smith Jr.
This paper discusses ways to reduce the bias of consistent estimators that are biased in finite samples. It is necessary that the bias function, which relates parameter values to bias, should be estimable by computer simulation or by some other method. If so, bias can be reduced or, in some cases that may not be unrealistic, even eliminated. In general, several evaluations of the bias function will be required to do this. Unfortunately, reducing bias may increase the variance, or even the mea...
Although traditional departments of anatomy are vanishing from medical school rosters, anatomical education still remains an important part of the professional training of physicians. It is of some interest to examine whether history can teach us anything about how to reform modern anatomy. Are there lessons to be learned from the history of…
Quarrie, Sofija Pekic
Several teachers at the Faculty of Agriculture at the University of Belgrade recognised the need to improve teaching methods in order to actively involve students in the teaching process, help them learn more effectively, and reduce the low exam pass rate. This led to a purpose-designed course on improving academic skills, after which the author…
Burmeister, Mareike; Eilks, Ingo
This paper describes the development and evaluation of a secondary school lesson plan for chemistry education on the topic Education for Sustainable Development (ESD). The lessons focus both on the chemistry of plastics and on learning about the societal evaluation of competing, chemistry-based industrial products. A specific teaching method was…
Schmidt, Matthew; Galyen, Krista; Laffey, James; Babiuch, Ryan; Schmidt, Carla
Design-based research (DBR) and open source software are both acknowledged as potentially productive ways for advancing learning technologies. These approaches have practical benefits for the design and development process and for building and leveraging community to augment and sustain design and development. This report presents a case study of…
Francisco David de la Peña Esteban
Full Text Available The development of the information and communication technologies (ICT, integrated within the current knowledge society, has transformed the way in which the human being relates to its environment. The integration of internet on mobile devices is one of the most representative cases on this matter. The universalization of smartphones has allowed not only to amplify the interpersonal communication but also explore new scenarios previously unsuspected. The application of mobile technologies to the education, which has been defined as m-learning, is breaking schemes of the traditional binominio teaching and learning to articulate pillar more dynamic as immediate access to knowledge, collaborative work or personalized learning. As a result of the numerous m-learning applications, it was considered appropriate to focus this research in the field of heritage education. That’s why an application (app for mobile that allows to interpret a cultural itinerary articulated in the industrial heritage of Madrid has been designed. The objective of this study consists of analysing how changes the app user’s perception of the industrial heritage after finishing the route in order to get results that allow design educational projects of and implement more effective cultural policies.
The best way to learn anything is by doing. The author uses a friendly tone and fun examples to ensure that you learn the basics of application development. Once you have read this book, you should have the necessary skills to build your own applications.If you have no experience but want to learn how to create applications in HTML5, this book is the only help you'll need. Using practical examples, HTML5 Web Application Development by Example will develop your knowledge and confidence in application development.
Difference in behaviour during the cognitive bias test suggests that fish cognitive bias can be affected by living conditions. Therefore this type of test should be taken to consideration as a tool in further fish welfare studies. It can be especially useful in studies concerning influence of living conditions that cannot be examined in direct way for example by preference test.
Boleij, H.; van't Klooster, J.; Lavrijsen, M.; Kirchhoff, S.; Arndt, S.S.; Ohl, F.
Emotional states are known to affect cognitive processes. For example highly anxious individuals interpret ambiguous stimuli more negatively than low anxious people, an effect called negative judgement bias. Recently, the measurement of judgement bias has been used to try and indicate emotional
Birch, Stephen; Lee, Myeong Soo; Robinson, Nicola; Alraek, Terje
Several systematic reviews suggest that acupuncture is effective for knee osteoarthritis (OA), and furthermore a safe and cost-effective treatment for this condition. A recent clinical practice guideline (CPG) from the National Institute for Health and Care Excellence (NICE), in the United Kingdom, recommended against the use of acupuncture on the grounds that the effect size (ES) in comparison with sham acupuncture is too small. Safety data were not considered in the review, in addition the levels of evidence for acupuncture against other recommended therapies were not compared. Consequently, it is argued that this NICE guideline has limitations that lead to several potential biases in its evaluation of acupuncture, which were not addressed correctly: (1) NICE's prior scoping process limited its review. (2) NICE introduced the method of developing recommendations based on the consideration of which interventions make "minimal important differences" of an ES of 0.5 or greater, rather than the statistical significance of the effect of an intervention when compared with an appropriate comparison. (3) Evidence that sham acupuncture is not physiologically inert and has some level of beneficial effect, hence artificially reducing the magnitude of the ES in comparison with sham. (4) The low adverse effects profile of acupuncture. (5) Evidence from trials comparing acupuncture with usual or standard care was not considered, nor was cost-effectiveness data. (6) Lack of the usual CPG "head-to-head" comparisons between interventions. If the same criteria and methods that have been applied to acupuncture were applied to other NICE-recommended therapies for knee OA, including patient centeredness, patient education, self-management and weight loss, nonsteroidal anti-inflammatory drug (NSAIDs), and cyclooxygenase-2 inhibitor (COX-2 inhibitors), these too would no longer be recommended and opiates would become the first line of drug prescription. Given the problems with sham
Makransky, Guido; Bonde, Mads T; Wulff, Julie S G; Wandall, Jakob; Hood, Michelle; Creed, Peter A; Bache, Iben; Silahtaroglu, Asli; Nørremølle, Anne
Simulation based learning environments are designed to improve the quality of medical education by allowing students to interact with patients, diagnostic laboratory procedures, and patient data in a virtual environment. However, few studies have evaluated whether simulation based learning environments increase students' knowledge, intrinsic motivation, and self-efficacy, and help them generalize from laboratory analyses to clinical practice and health decision-making. An entire class of 300 University of Copenhagen first-year undergraduate students, most with a major in medicine, received a 2-h training session in a simulation based learning environment. The main outcomes were pre- to post- changes in knowledge, intrinsic motivation, and self-efficacy, together with post-intervention evaluation of the effect of the simulation on student understanding of everyday clinical practice were demonstrated. Knowledge (Cohen's d = 0.73), intrinsic motivation (d = 0.24), and self-efficacy (d = 0.46) significantly increased from the pre- to post-test. Low knowledge students showed the greatest increases in knowledge (d = 3.35) and self-efficacy (d = 0.61), but a non-significant increase in intrinsic motivation (d = 0.22). The medium and high knowledge students showed significant increases in knowledge (d = 1.45 and 0.36, respectively), motivation (d = 0.22 and 0.31), and self-efficacy (d = 0.36 and 0.52, respectively). Additionally, 90 % of students reported a greater understanding of medical genetics, 82 % thought that medical genetics was more interesting, 93 % indicated that they were more interested and motivated, and had gained confidence by having experienced working on a case story that resembled the real working situation of a doctor, and 78 % indicated that they would feel more confident counseling a patient after the simulation. The simulation based learning environment increased students' learning, intrinsic motivation, and
Drecourt, J.-P.; Madsen, H.; Rosbjerg, Dan
This paper reviews two different approaches that have been proposed to tackle the problems of model bias with the Kalman filter: the use of a colored noise model and the implementation of a separate bias filter. Both filters are implemented with and without feedback of the bias into the model state....... The colored noise filter formulation is extended to correct both time correlated and uncorrelated model error components. A more stable version of the separate filter without feedback is presented. The filters are implemented in an ensemble framework using Latin hypercube sampling. The techniques...... are illustrated on a simple one-dimensional groundwater problem. The results show that the presented filters outperform the standard Kalman filter and that the implementations with bias feedback work in more general conditions than the implementations without feedback. 2005 Elsevier Ltd. All rights reserved....
Full Text Available We examine two departures of individual perceptions of randomness from probability theory: the hot hand and the gambler's fallacy, and their respective opposites. This paper's first contribution is to use data from the field (individuals playing roulette in a casino to demonstrate the existence and impact of these biases that have been previously documented in the lab. Decisions in the field are consistent with biased beliefs, although we observe significant individual heterogeneity in the population. A second contribution is to separately identify these biases within a given individual, then to examine their within-person correlation. We find a positive and significant correlation across individuals between hot hand and gambler's fallacy biases, suggesting a common (root cause of the two related errors. We speculate as to the source of this correlation (locus of control, and suggest future research which could test this speculation.
Orlando, Nicola; The ATLAS collaboration
The modelling of Minimum Bias (MB) is a crucial ingredient to learn about the description of soft QCD processes and to simulate the environment at the LHC with many concurrent pp interactions (pile-up). We summarise the ATLAS minimum bias measurements with proton-proton collision at 13 TeV center-of-mass-energy at the Large Hadron Collider.
Anil V. Mishra; Umaru B. Conteh
This paper constructs the float adjusted measure of home bias and explores the determinants of bond home bias by employing the International Monetary Fund's high quality dataset (2001 to 2009) on cross-border bond investment. The paper finds that Australian investors' prefer investing in countries with higher economic development and more developed bond markets. Exchange rate volatility appears to be an impediment for cross-border bond investment. Investors prefer investing in countries with ...
Just, T.; Csapo, G.
ENIQ (European Network for Inspection and Qualification) has developed regulations on how to qualify non-destructive testing (NDT) methods and techniques in a standardized and structured manner. Two major innovative qualifications were carried out and reviewed with regard to implementation, according to the recommended German practice of ENIQ. The conclusions were drawn after performing the ENIQ qualification procedure for in-service inspections (ISI) of real components in nuclear power plants (NPP). The first example covers the qualification of NDT methods for the detection and characterization of surface, subsurface and underclad cracks in the area of the austenitic cladded RPV surface. Open and blind tests were conducted applying UT and ET (from the ID) and UT (from the OD) on realistic flaws (artificially induced IGSCC, hot cracks and fatigue cracks) in the cladding of a full scale RPV mock-up from MPA Stuttgart. The second example covers the qualification of mechanised RT in combination with tomography (developed by the BAM) for the sizing of cracks in pipe welds. For both qualification procedures TUEV NORD SysTec experts were part of the qualification body. The proposed NDT procedures have been qualified within defined limits of application. Recommendations were made to optimise the procedures and the techniques itself further. (orig.)
Although traditional departments of anatomy are vanishing from medical school rosters, anatomical education still remains an important part of the professional training of physicians. It is of some interest to examine whether history can teach us anything about how to reform modern anatomy. Are there lessons to be learned from the history of anatomical teaching in the United States that can help in the formulation of contents and purposes of a new anatomy? This question is explored by a review of US anatomical teaching with special reference to Franklin Paine Mall and the University of Michigan Medical School. An historical perspective reveals that there is a tradition of US anatomical teaching and research that is characterized by a zeal for reform and innovation, scientific endeavor, and active, student-driven learning. Further, there is a tradition of high standards in anatomical teaching through the teachers' engagement in scientific anatomy and of adaptability to new requirements. These traditional strengths can inform the innovation of modern anatomy in terms of its two duties--its duty to anatomy as a science and its duty toward anatomical education. Copyright 2010 American Association of Anatomists.
An example of how to use the magni.reproducibility package for storing metadata along with results from a computational experiment. The example is based on simulating the Mandelbrot set.......An example of how to use the magni.reproducibility package for storing metadata along with results from a computational experiment. The example is based on simulating the Mandelbrot set....
Hatcher, Gerry; Okuda, Craig
The effects of climate change on the near shore coastal environment including ocean acidification, accelerated erosion, destruction of coral reefs, and damage to marine habitat have highlighted the need for improved equipment to study, monitor, and evaluate these changes . This is especially true where areas of study are remote, large, or beyond depths easily accessible to divers. To this end, we have developed three examples of low cost and easily deployable real-time ocean observation platforms. We followed a scalable design approach adding complexity and capability as familiarity and experience were gained with system components saving both time and money by reducing design mistakes. The purpose of this paper is to provide information for the researcher, technician, or engineer who finds themselves in need of creating or acquiring similar platforms.
is censoring: selection by the size of estimate; SR3 selects the optimal combination of fit and size; and SR4 selects the first satisficing result. The last four SRs are steered by priors and result in bias. The MST and the FAT-PET have been developed for detection and correction of such bias. The simulations......Economic research typically runs J regressions for each selected for publication – it is often selected as the ‘best’ of the regressions. The paper examines five possible meanings of the word ‘best’: SR0 is ideal selection with no bias; SR1 is polishing: selection by statistical fit; SR2...... are made by data variation, while the model is the same. It appears that SR0 generates narrow funnels much at odds with observed funnels, while the other four funnels look more realistic. SR1 to SR4 give the mean a substantial bias that confirms the prior causing the bias. The FAT-PET MRA works well...
Neel, Rebecca; Shapiro, Jenessa R
How do Whites approach interracial interactions? We argue that a previously unexamined factor-beliefs about the malleability of racial bias-guides Whites' strategies for difficult interracial interactions. We predicted and found that those who believe racial bias is malleable favor learning-oriented strategies such as taking the other person's perspective and trying to learn why an interaction is challenging, whereas those who believe racial bias is fixed favor performance-oriented strategies such as overcompensating in the interaction and trying to end the interaction as quickly as possible. Four studies support these predictions. Whether measured (Studies 1, 3, and 4) or manipulated (Study 2), beliefs that racial bias is fixed versus malleable yielded these divergent strategies for difficult interracial interactions. Furthermore, beliefs about the malleability of racial bias are distinct from related constructs (e.g., prejudice and motivations to respond without prejudice; Studies 1, 3, and 4) and influence self-reported (Studies 1-3) and actual (Study 4) strategies in imagined (Studies 1-2) and real (Studies 3-4) interracial interactions. Together, these findings demonstrate that beliefs about the malleability of racial bias influence Whites' approaches to and strategies within interracial interactions. PsycINFO Database Record (c) 2012 APA, all rights reserved
Borstler, Jurgen; Nordstrom, Marie; Paterson, James H.
Example programs play an important role in the teaching and learning of programming. Students as well as teachers rank examples as the most important resources for learning to program. Example programs work as role models and must therefore always be consistent with the principles and rules we are teaching. However, it is difficult to find or…
Love, Bradley C; Kopeć, Łukasz; Guest, Olivia
People are optimistic about their prospects relative to others. However, existing studies can be difficult to interpret because outcomes are not zero-sum. For example, one person avoiding cancer does not necessitate that another person develops cancer. Ideally, optimism bias would be evaluated within a closed formal system to establish with certainty the extent of the bias and the associated environmental factors, such that optimism bias is demonstrated when a population is internally inconsistent. Accordingly, we asked NFL fans to predict how many games teams they liked and disliked would win in the 2015 season. Fans, like ESPN reporters assigned to cover a team, were overly optimistic about their team's prospects. The opposite pattern was found for teams that fans disliked. Optimism may flourish because year-to-year team results are marked by auto-correlation and regression to the group mean (i.e., good teams stay good, but bad teams improve).
Love, Bradley C.
People are optimistic about their prospects relative to others. However, existing studies can be difficult to interpret because outcomes are not zero-sum. For example, one person avoiding cancer does not necessitate that another person develops cancer. Ideally, optimism bias would be evaluated within a closed formal system to establish with certainty the extent of the bias and the associated environmental factors, such that optimism bias is demonstrated when a population is internally inconsistent. Accordingly, we asked NFL fans to predict how many games teams they liked and disliked would win in the 2015 season. Fans, like ESPN reporters assigned to cover a team, were overly optimistic about their team’s prospects. The opposite pattern was found for teams that fans disliked. Optimism may flourish because year-to-year team results are marked by auto-correlation and regression to the group mean (i.e., good teams stay good, but bad teams improve). PMID:26352146
Jensen, Henning Tarp; Robinson, Sherman; Tarp, Finn
The measurement issue is the key issue in the literature on trade policy-induced agri-cultural price incentive bias. This paper introduces a general equilibrium effective rate of protection (GE-ERP) measure, which extends and generalizes earlier partial equilibrium nominal protection measures...... shares and intersectoral linkages - are crucial for determining the sign and magnitude of trade policy bias. The GE-ERP measure is therefore uniquely suited to capture the full impact of trade policies on agricultural price incentives. A Monte Carlo procedure confirms that the results are robust....... For the 15 sample countries, the results indicate that the agricultural price incentive bias, which was generally perceived to exist during the 1980s, was largely eliminated during the 1990s. The results also demonstrate that general equilibrium effects and country-specific characteristics - including trade...
S. S. Khromov
Full Text Available The article is devoted to the elaboration of methodology and technique of the master’s distance course in linguistics for Russian students. The research novelty lies in the fact that the course presents the results methodic and scientific work of the teachers’ and students’ stuff. Within the course framework we plan to transfer the communicative activity concept to the distance forms of education and modeling a new type of the educational product.The purposes of the research are: 1 to develop the distance learning methodology and technique for a linguistic master’s course; 2 to elaborate an internal structure of the project; 3 to demonstrate which vocational, language and speech competencies are to appear as tge result of the project; 4 to describe the algorithm of the full-time lecture course in linguistics in a distance format; 5 to conduct a pedagogical experiment realizing the distance learning education in master’s linguistic course; 6 to prove the innovation and the productivity of the elaborated master’s course in linguistics.The research is based on 1 the paper variant of the full-time lecture course 2 the curriculum of the lecture course 3 the concept of the master’s course in linguistics 4 the concept of the distance course in linguistics 5 students’ interviews 6 virtual tools The research methods are 1 descriptive 2 project 3 comparative 4 statistic methodsConclusion. The novelty and the productivity of the course have been proved and they are manifested in the following 1 in the ability to develop vocational, language and speech competences of the students 2 in developing individual trajectories of the students 3 in expanding sociocultural potential of the students 4 in developing sociocultural potential of the students 5 in intensifying education process. As a result of the experiment we can state that 1 the methodology and technique of distance tools in projecting master’s course in linguistics are described 2 the
Full Text Available Many universities in the Czech Republic lack students´ interest in the studies of natural science. That is why all the universities have to come up with an idea how to popularize these scientific fields to attract potential university applicants. One of the ways of achieving that is to create educational centres, which are able, thanks to these programmes, to approach students of primary and secondary schools and show them the natural sciences. The presented example of one particular educational centre (Bioskop Masaryk University, Brno, the Czech Republic evaluates the success rate of their activities while using written questionnaire survey among the visitors of the programmes (students of primary and secondary schools as well as their pedagogues. The results have shown that thanks to these activities the centre created quality conditions for popularization of natural sciences. The results have also proven the centre´s ability to present natural sciences in an attractive and entertaining way to students of elementary and secondary schools. These students expressed their interest in the study of natural sciences and they would like to visit the centre again
Zhu, Gao-Ru; Porter, John H; Xu, Xue-Gong
In order to observe and understand long-term and large-scale ecological changes, the US National Science Foundation initiated a Long-Term Ecological Research (LTER) program in 1980. Over the past 30 years, the US LTER program has achieved advances in ecological and social science research, and in the development of site-based research infrastructure. This paper attributed the success of the program to five characteristics, i.e., 1) consistency of research topics and data across the network, 2) long-term time scale of both the research and the program, 3) flexibility in research content and funding procedures, 4) growth of LTER to include international partners, new disciplines such as social science, advanced research methods, and cooperation among sites, and 5) sharing of data and educational resources. The Virginia Coast Reserve LTER site was taken as an example to illustrate how the US LTER works at site level. Some suggestions were made on the China long-term ecological research, including strengthening institution construction, improving network and inter-site cooperation, emphasizing data quality, management, and sharing, reinforcing multidisciplinary cooperation, and expanding public influence.
Borisov, N.M.; Panin, M.P.
The report proposes a visual criterion of importance biasing both of forward and adjoint simulation. The similarity of contribution Monte Carlo and importance biasing random collision event distribution is proved. The conservation of total number of random trajectory crossings of surfaces, which separate the source and the detector is proposed as importance biasing quality criterion. The use of this criterion is demonstrated on the example of forward vs. adjoint importance biasing in gamma ray deep penetration problem. The larger amount of published data on forward field characteristics than on adjoint leads to the more accurate approximation of adjoint importance function in comparison to forward, for it adjoint importance simulation is more effective than forward. The proposed criterion indicates it visually, showing the most uniform distribution of random trajectory crossing events for the most effective importance biasing parameters and pointing to the direction of tuning importance biasing parameters. (orig.)
Culbertson, Jennifer; Newport, Elissa L
A fundamental question for cognitive science concerns the ways in which languages are shaped by the biases of language learners. Recent research using laboratory language learning paradigms, primarily with adults, has shown that structures or rules that are common in the languages of the world are learned or processed more easily than patterns that are rare or unattested. Here we target child learners, investigating a set of biases for word order learning in the noun phrase studied by Culbertson, Smolensky, and Legendre (2012) in college-age adults. We provide the first evidence that child learners exhibit a preference for typologically common harmonic word order patterns-those which preserve the order of the head with respect to its complements-validating the psychological reality of a principle formalized in many different linguistic theories. We also discuss important differences between child and adult learners in terms of both the strength and content of the biases at play during language learning. In particular, the bias favoring harmonic patterns is markedly stronger in children than adults, and children (unlike adults) acquire adjective ordering more readily than numeral ordering. The results point to the importance of investigating learning biases across development in order to understand how these biases may shape the history and structure of natural languages. Copyright © 2015 Elsevier B.V. All rights reserved.
Culbertson, Jennifer; Newport, Elissa L.
A fundamental question for cognitive science concerns the ways in which languages are shaped by the biases of language learners. Recent research using laboratory language learning paradigms, primarily with adults, has shown that structures or rules that are common in the languages of the world are learned or processed more easily than patterns that are rare or unattested. Here we target child learners, investigating a set of biases for word order learning in the noun phrase studied by Culbertson, Smolensky & Legendre (2012) in college-age adults. We provide the first evidence that child learners exhibit a preference for typologically common harmonic word order patterns—those which preserve the order of the head with respect to its complements—validating the psychological reality of a principle formalized in many different linguistic theories. We also discuss important differences between child and adult learners in terms of both the strength and content of the biases at play during language learning. In particular, the bias favoring harmonic patterns is markedly stronger in children than adults, and children (unlike adults) acquire adjective ordering more readily than numeral ordering. The results point to the importance of investigating learning biases across development in order to understand how these biases may shape the history and structure of natural languages. PMID:25800352
Reid, Beth A.; Verde, Licia; Dolag, Klaus; Matarrese, Sabino; Moscardini, Lauro
The strong dependence of the large-scale dark matter halo bias on the (local) non-Gaussianity parameter, f NL , offers a promising avenue towards constraining primordial non-Gaussianity with large-scale structure surveys. In this paper, we present the first detection of the dependence of the non-Gaussian halo bias on halo formation history using N-body simulations. We also present an analytic derivation of the expected signal based on the extended Press-Schechter formalism. In excellent agreement with our analytic prediction, we find that the halo formation history-dependent contribution to the non-Gaussian halo bias (which we call non-Gaussian halo assembly bias) can be factorized in a form approximately independent of redshift and halo mass. The correction to the non-Gaussian halo bias due to the halo formation history can be as large as 100%, with a suppression of the signal for recently formed halos and enhancement for old halos. This could in principle be a problem for realistic galaxy surveys if observational selection effects were to pick galaxies occupying only recently formed halos. Current semi-analytic galaxy formation models, for example, imply an enhancement in the expected signal of ∼ 23% and ∼ 48% for galaxies at z = 1 selected by stellar mass and star formation rate, respectively
Jensen, Henning Tarp; Robinson, Sherman; Tarp, Finn
Measurement is a key issue in the literature on price incentive bias induced by trade policy. We introduce a general equilibrium measure of the relative effective rate of protection, which generalizes earlier protection measures. For our fifteen sample countries, results indicate that the agricul...
Phillips, Nicole A; Tannan, Shruti C; Kalliainen, Loree K
Although explicit sex-based discrimination has largely been deemed unacceptable in professional settings, implicit gender bias persists and results in a significant lack of parity in plastic surgery and beyond. Implicit gender bias is the result of a complex interplay of cultural and societal expectations, learned behaviors, and standardized associations. As such, both male and female surgeons are subject to its influence. A review of the literature was conducted, examining theories of gender bias, current manifestations of gender bias in plastic surgery and other fields, and interventions designed to address gender bias. Multiple studies demonstrate persistent gender bias that impacts female physicians at all levels of training. Several institutions have enacted successful interventions to identify and address gender bias. Explicit gender bias has largely disappeared, yet unconscious or implicit gender bias persists. A wide-scale commitment to addressing implicit gender bias in plastic surgery is necessary and overdue. Recommendations include immediate actions that can be undertaken on an individual basis, and changes that should be implemented at a national and international level by leaders in the field.
Kwan, Johnny S H; Kung, Annie W C; Sham, Pak C
Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias.
Full Text Available Phạm Nguyễn Du’s influential text Humble Comments on the Analects (Luận Ngữ Ngu Án 論語愚按 is an outstanding example of a Vietnamese adaptation and reworking of an East Asian intellectual tradition. In organizing his work, Phạm departed from convention by rearranging the extant chapters of the Analects into four “books”: “Sage” (Thánh 聖, “Learning” (Học 學, “Official” (Sĩ 仕, and “Politics” (Chính 政. Moreover, Phạm placed particular emphasis on the “Learning” book, and thus underscored his contention that the classic text was especially relevant and meaningful to eighteenth-century Vietnam. This paper attempts to read Phạm’s work in the contexts of both Confucian tradition and contemporary education. First, it examines Phạm’s composition of the Humble Comments based on Jack Mezirow’s theory of transformative learning. Phạm’s writing process in this work presents a fascinating case of transformative learning, in which the author questions received assumptions about the world and himself, puts forward new propositions, and elaborates these via an original reading of a classic. Through the analysis of Phạm Nguyễn Du’s life and his preface to the Humble Comments, one can also gain a better view of the Vietnamese reception of Zhu Xi’s Neo-Confucianism, and more particularly, of Zhu’s dictum of “learning for the sake of one’s self” (weiji zhi xue 為己 之學. Lastly, this dictum will be reappraised to show its validity in contemporary educational contexts.
This chapter looks at the development and nature of learning objects, meta-tagging standards and taxonomies, learning object repositories, learning object repository characteristics, and types of learning object repositories, with type examples. (Contains 1 table.)
Culbertson, Jennifer; Smolensky, Paul; Legendre, Geraldine
How recurrent typological patterns, or universals, emerge from the extensive diversity found across the world's languages constitutes a central question for linguistics and cognitive science. Recent challenges to a fundamental assumption of generative linguistics--that universal properties of the human language acquisition faculty constrain the…
Nielsen, Heino Bohn
This paper characterizes the finite-sample bias of the maximum likelihood estimator (MLE) in a reduced rank vector autoregression and suggests two simulation-based bias corrections. One is a simple bootstrap implementation that approximates the bias at the MLE. The other is an iterative root...
Biro, Peter A
Sampling animals from the wild for study is something nearly every biologist has done, but despite our best efforts to obtain random samples of animals, 'hidden' trait biases may still exist. For example, consistent behavioral traits can affect trappability/catchability, independent of obvious factors such as size and gender, and these traits are often correlated with other repeatable physiological and/or life history traits. If so, systematic sampling bias may exist for any of these traits. The extent to which this is a problem, of course, depends on the magnitude of bias, which is presently unknown because the underlying trait distributions in populations are usually unknown, or unknowable. Indeed, our present knowledge about sampling bias comes from samples (not complete population censuses), which can possess bias to begin with. I had the unique opportunity to create naturalized populations of fish by seeding each of four small fishless lakes with equal densities of slow-, intermediate-, and fast-growing fish. Using sampling methods that are not size-selective, I observed that fast-growing fish were up to two-times more likely to be sampled than slower-growing fish. This indicates substantial and systematic bias with respect to an important life history trait (growth rate). If correlations between behavioral, physiological and life-history traits are as widespread as the literature suggests, then many animal samples may be systematically biased with respect to these traits (e.g., when collecting animals for laboratory use), and affect our inferences about population structure and abundance. I conclude with a discussion on ways to minimize sampling bias for particular physiological/behavioral/life-history types within animal populations.
Anthony, Ann Strong
Gender bias in nursing education impedes recruitment and retention of males into the profession. Nurse educators who are unaware of men's historical contributions to the profession may unknowingly perpetuate gender bias. The author describes how traditional stereotypes can be challenged and teaching/learning strategies can be customized to gender-driven learning styles.
Magelssen, Morten; Pedersen, Reidar; Førde, Reidun
A central task for clinical ethics consultants and committees (CEC) is providing analysis of, and advice on, prospective or retrospective clinical cases. However, several kinds of biases may threaten the integrity, relevance or quality of the CEC's deliberation. Bias should be identified and, if possible, reduced or counteracted. This paper provides a systematic classification of kinds of bias that may be present in a CEC's case deliberation. Six kinds of bias are discussed, with examples, as to their significance and risk factors. Possible remedies are suggested. The potential for bias is greater when the case deliberation is performed by an individual ethics consultant than when an entire clinical ethics committee is involved. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Duarte et al. draw attention to the "embedding of liberal values and methods" in social psychological research. They note how these biases are often invisible to the researchers themselves. The authors themselves fall prey to these "invisible biases" by utilizing the five-factor model of personality and the trait of openness to experience as one possible explanation for the under-representation of political conservatives in social psychology. I show that the manner in which the trait of openness to experience is conceptualized and measured is a particularly blatant example of the very liberal bias the authors decry.
Tanzania is one of the jurisdictions in Africa that follow an adversarial criminal justice system. Despite a number of problems associated with the fact that the criminal justice system overutilises imprisonment, there is still a lack of diversionary measures to complement the system. This article investigates restorative justice as ...
1 déc. 2010 ... Inspiré de recherches et d'expériences concrètes émanant de Chine et d'Asie du Sud et du Sud-Est, ce livre présente et analyse des démarches nouvelles en matière d'apprentissage collaboratif et de communautés de praticiens. Les études de cas illustrent comment, grâce aux efforts conjugués de ...
In this paper, I contest the view of the group as a source of bias and irrationality, especially prevalent within social psychology. I argue that this negative evaluation often arises by applying inappropriate standards, relating to the wrong level of analysis (often the individual level). Second, the image of the group as bad and biasing is often overstated. For example, the evidence suggests that intergroup discrimination, rather than being universal or generic, is often constrained, proportionate and reflects functional and rational strategies for managing threats and opportunities at the group level. Third, although the recent upsurge of interest in group emotions could be seen to reinforce the dualism between rationality and emotion, the contemporary functional approach argues for group emotions as augmenting rather than contradicting rationality. However, we should be wary (and weary) of narrow economic and individualist notions of rationality; group identity may offer the opportunity to redefine rationality in more collective and prosocial ways.
Data assimilation methods rely on numerous assumptions about the errors involved in measuring and forecasting atmospheric fields. One of the more disturbing of these is that short-term model forecasts are assumed to be unbiased. In case of atmospheric moisture, for example, observational evidence shows that the systematic component of errors in forecasts and analyses is often of the same order of magnitude as the random component. we have implemented a sequential algorithm for estimating forecast moisture bias from rawinsonde data in the Goddard Earth Observing System Data Assimilation System (GEOS DAS). The algorithm is designed to remove the systematic component of analysis errors and can be easily incorporated in an existing statistical data assimilation system. We will present results of initial experiments that show a significant reduction of bias in the GEOS DAS moisture analyses.
In his excellent article about commercial conflict of interest, Mark Wilson quotes Dennis Thompson, a political scientist who provided a searching analysis of the concept of conflict of interest (Col). Using Thompson's analysis, Wilson writes: "Determining whether factors such as ambition, the pursuit of fame and financial gain had biased a judgment was challenging. Motives are not always clear to either the conflicted party or to an outside observer." In this commentary, I aim to broaden the discussion beyond the narrowly commercial aspects of Col. I argue that bias can be introduced in major scientific journals by the editors' choices and policies. The context is a controversy that erupted in 2013 over the adequacy of informed consent in a clinical trial involving extremely premature infants. In this, as in Wilson's example, the players included the New England Journal of Medicine (NEJM), as well as the highest officials of the US National Institutes of Health (NIH).
Reflecting Equity and Diversity. Part I: Guidelines and Procedure for Evaluating Bias in Instructional Materials. Part II: Bias Awareness Training Worksheets. Part III: Bias Awareness and Procedure Training Course.
Bebermeyer, Jim; Edmond, Mary, Ed.
Reflecting a need to prepare students for working in diverse organizations, this document was developed to increase school officials' awareness of bias in instructional materials and help them select bias-free materials. A number of the examples illustrate situations dealing with diversity in the workplace. The guide is divided into three parts:…
Praise for the Fourth Edition: ""This book is . . . an excellent source of examples for regression analysis. It has been and still is readily readable and understandable."" -Journal of the American Statistical Association Regression analysis is a conceptually simple method for investigating relationships among variables. Carrying out a successful application of regression analysis, however, requires a balance of theoretical results, empirical rules, and subjective judgment. Regression Analysis by Example, Fifth Edition has been expanded
"SIGA OS EXEMPLOS" DOS ALUNOS: APRENDIZAGENS EM AULAS EXPLORATÓRIO-INVESTIGATIVAS NO 4o. ANO DO ENSINO FUNDAMENTAL. "FOLLOW THE EXAMPLES" OF STUDENTS: LEARNING IN EXPLORATORY-INVESTIGATIVE ACTIVITIES IN THE 4TH GRADE OF ELEMENTARY SCHOOL
training course. The first author of this article, who was the course trainer, took part in some of those classes. Data were composed by videotapes and its transcriptions, teacher’s oral narratives and notes, researcher appointments, and students’ appointments and pictures. The study was based on the literature about explorative-investigative mathematics researches in classes of primary education, and about teacher learning, a subject of permanent formation. The data analysis was focused on three different developed activities, and the results showed the students’ learning of geometrical contents with concepts of plane geometric figures, the use of the ruler, and new ways of participation in a context of oral and written discussion and negotiating of concepts. On the other hand, the teacher focused her activities on a better way of guiding those classes, allowing the children participation by asking about and discussing their own or their peer’s productions. Her learning was also related to her autonomy to choose the activities and manage time in classroom. We empathize that classes about plane geometric figures can be based on examples made by the very students, in opposition to learning based on pre-printed illustrations.
Liliana Gheorghian, Mariana
The Secondary School "Teodor Balan" was evaluated by the National Agency for Quality Assurance with the highest score in an urban area of the county, and is part of the community Gura Humorului, a tourist resort of national interest since 2005. Starting with 2006 the local government implemented a Local Plan, which promotes the concept of sustainable development adopted at the Earth Summit in Rio de Janeiro, in 1992. Our school shares the concept of sustainable development and regularly re-evaluates the relationship between man and nature, advocates solidarity between generations, and has constantly developed various successful programs with the students, parents, teachers, and local companies and administration. Quarterly, we maintain and protect the river valley of Moldova arboretum nearby the reserve Oligocene "Stone Pine" and the natural reserve "Stone Hawk". Regarding the preservation of forests, teams of students and teachers from the school conduct activities of afforestation and greening, for the protection of birds. In order to raise public awareness about the harmful effects of radiation on the environment, my work degree in Physics, sustained in 2007, had as theme: Ionizing radiation and radiation protection. The effects of climate change and increasing temperature, as well as the extinction of species such as Amanita regalis and Tremiscus helvelloides mushrooms was studied by my biology colleague, Adriana. She obtained her Ist teaching degree in 2008, with the study "Diversity of macromycetes reported in natural ecosystems surrounding Gura Humorului". There were also organized 3 roundtables in a public awareness campaign initiated by the Ministry of Environment and Climate Change on "Integrated Nutrient Pollution Control", and the students learned to take test samples to determine water quality in wells and springs. In order to promote these activities performed by both teachers and students, we organized a National Symposium on "Life sciences at the
Research on the exchange bias (EB) phenomenon has witnessed a flurry of activity during recent years, which stems from its use in magnetic sensors and as stabilizers in magnetic reading heads. EB was discovered in 1956 but it attracted only limited attention until these applications, closely related to giant magnetoresistance, were developed during the last decade. In this review, I initially give a short introduction, listing the most salient experimental results and what is required from an EB theory. Next, I indicate some of the obstacles in the road towards a satisfactory understanding of the phenomenon. The main body of the text reviews and critically discusses the activity that has flourished, mainly during the last 5 years, in the theoretical front. Finally, an evaluation of the progress made, and a critical assessment as to where we stand nowadays along the road to a satisfactory theory, is presented
Schumacher, Sophie E; Kemps, Eva; Tiggemann, Marika
Recent evidence has demonstrated that bias modification training has potential to reduce cognitive biases for attractive targets and affect health behaviours. The present study investigated whether cognitive bias modification training could be applied to reduce approach bias for chocolate and affect subsequent chocolate consumption. A sample of 120 women (18-27 years) were randomly assigned to an approach-chocolate condition or avoid-chocolate condition, in which they were trained to approach or avoid pictorial chocolate stimuli, respectively. Training had the predicted effect on approach bias, such that participants trained to approach chocolate demonstrated an increased approach bias to chocolate stimuli whereas participants trained to avoid such stimuli showed a reduced bias. Further, participants trained to avoid chocolate ate significantly less of a chocolate muffin in a subsequent taste test than participants trained to approach chocolate. Theoretically, results provide support for the dual process model's conceptualisation of consumption as being driven by implicit processes such as approach bias. In practice, approach bias modification may be a useful component of interventions designed to curb the consumption of unhealthy foods. Copyright © 2015 Elsevier Ltd. All rights reserved.
C. Reggiani; G. Rossini
Home bias affects trade in goods, services and financial assets. It is mostly generated by "natural" trade barriers. Among these dividers we may list many behavioral and sociological factors, such as status quo biases and a few kind of ‘embeddedness’. Unfortunately these factors are difficult to measure. An important part of ‘embeddedness’ may be related to religious attitudes. Is there any relation between economic home bias and religious attitudes at the individual tier? Our aim is to provi...
Gluud, Lise Lotte
Research on bias in clinical trials may help identify some of the reasons why investigators sometimes reach the wrong conclusions about intervention effects. Several quality components for the assessment of bias control have been suggested, but although they seem intrinsically valid, empirical...... evidence is needed to evaluate their effects on the extent and direction of bias. This narrative review summarizes the findings of methodological studies on the influence of bias in clinical trials. A number of methodological studies suggest that lack of adequate randomization in published trial reports...
We introduce code query by example for customisation of evolvable software products in general and of enterprise resource planning systems (ERPs) in particular. The concept is based on an initial empirical study on practices around ERP systems. We motivate our design choices based on those empirical results, and we show how the proposed solution helps with respect to the infamous upgrade problem: the conflict between the need for customisation and the need for upgrade of ERP systems. We further show how code query by example can be used as a form of lightweight static analysis, to detect automatically potential defects in large software products. Code query by example as a form of lightweight static analysis is particularly interesting in the context of ERP systems: it is often the case that programmers working in this field are not computer science specialists but more of domain experts. Hence, they require a simple language to express custom rules.
Iwata, Koji; Tsukimori, Kazuyuki; Ueno, Mutsuo
FINAS is a general purpose structural analysis computer program which was developed by Japan Nuclear Cycle Development Institute for the analysis of static, dynamic and thermal responses of elastic and inelastic structures by the finite element method. This manual contains typical analysis examples that illustrate applications of FINAS to a variety of structural engineering problems. The first part of this manual presents fundamental examples in which numerical solutions by FINAS are compared with some analytical reference solutions, and the second part of this manual presents more complex examples intended for practical application. All the input data images and principal results for each problem are included in this manual for beginners' convenience. All the analyses are performed by using the FINAS Version 13.0. (author)
Richards, Evan; Polak, Jeff; Hardin, Ashley; Risley, John, , Dr.
Research shows students can learn from worked examples.^1 This pilot study compared two groups of students' performance (10 each) in solving physics problems. One group had access to interactive examples^2 released in WebAssign^3, while the other group had access to the counterpart textbook examples. Verbal data from students in problem solving sessions was collected using a think aloud protocol^4 and the data was analyzed using Chi's procedures.^5 An explanation of the methodology and results will be presented. Future phases of this pilot study based upon these results will also be discussed. ^1Atkinson, R.K., Derry, S.J., Renkl A., Wortham, D. (2000). ``Learning from Examples: Instructional Principles from the Worked Examples Research'', Review of Educational Research, vol. 70, n. 2, pp. 181-214. ^2Serway, R.A. & Faughn, J.S. (2006). College Physics (7^th ed.). Belmont, CA: Thomson Brooks/Cole. ^3 see www.webassign.net ^4 Ericsson, K.A. & Simon, H.A. (1984). Protocol Analysis: Verbal Reports as Data. Cambridge, Massachusetts: The MIT Press. ^5 Chi, Michelene T.H. (1997). ``Quantifying Qualitative Analyses of Verbal Data: A Practical Guide,'' The Journal of the Learning Sciences, vol. 6, n. 3, pp. 271-315.
Farooq, Omar; Taouss, Mohammed
Can information environment of a firm explain home bias in analysts’ recommendations? Can the extent of agency problems explain optimism difference between foreign and local analysts? This paper answers these questions by documenting the effect of information environment on home bias in analysts’...
Lilienfeld, Scott O; Latzman, Robert D
Although disparities in political ideology are rooted partly in dispositional differences, Hibbing et al.'s analysis paints with an overly broad brush. Research on the personality correlates of liberal-conservative differences points not to global differences in negativity bias, but to differences in threat bias, probably emanating from differences in fearfulness. This distinction bears implications for etiological research and persuasion efforts.
Caspersen, Michael Edelgaard; Alphonce, Carl; Decker, Adrienne
Giving students an appreciation of the benefits of using design patterns and an ability to use them effectively in developing code presents several interesting pedagogical challenges. This paper discusses pedagogical lessons learned at the "Killer Examples" for Design Patterns and Objects First s...... series of workshops held at the Object Oriented Programming, Systems, Languages and Applications (OOPSLA) conference over the past four years. It also showcases three "killer examples" which can be used to support the teaching of design patterns.......Giving students an appreciation of the benefits of using design patterns and an ability to use them effectively in developing code presents several interesting pedagogical challenges. This paper discusses pedagogical lessons learned at the "Killer Examples" for Design Patterns and Objects First...
Rocha, Luis E. C.; Masuda, Naoki; Holme, Petter
Temporal networks have been increasingly used to model a diversity of systems that evolve in time; for example, human contact structures over which dynamic processes such as epidemics take place. A fundamental aspect of real-life networks is that they are sampled within temporal and spatial frames. Furthermore, one might wish to subsample networks to reduce their size for better visualization or to perform computationally intensive simulations. The sampling method may affect the network structure and thus caution is necessary to generalize results based on samples. In this paper, we study four sampling strategies applied to a variety of real-life temporal networks. We quantify the biases generated by each sampling strategy on a number of relevant statistics such as link activity, temporal paths and epidemic spread. We find that some biases are common in a variety of networks and statistics, but one strategy, uniform sampling of nodes, shows improved performance in most scenarios. Given the particularities of temporal network data and the variety of network structures, we recommend that the choice of sampling methods be problem oriented to minimize the potential biases for the specific research questions on hand. Our results help researchers to better design network data collection protocols and to understand the limitations of sampled temporal network data.
Zetsche, Ulrike; Rief, Winfried; Exner, Cornelia
Overestimating the occurrence of threatening events has been highlighted as a central cognitive factor in the maintenance of obsessive-compulsive disorder (OCD). The present study examined the different facets of this cognitive bias, its underlying mechanisms, and its specificity to OCD. For this purpose, threat estimation, probabilistic classification learning (PCL) and psychopathological measures were assessed in 23 participants with OCD, 30 participants with social phobia, and 31 healthy controls. Whereas healthy participants showed an optimistic expectation bias regarding positive and negative future events, OCD participants lacked such a bias. This lack of an optimistic expectation bias was not specific to OCD. Compared to healthy controls, OCD participants overestimated their personal risk for experiencing negative events, but did not differ from controls in their risk estimation regarding other people. Finally, OCD participants' biases in the prediction of checking-related events were associated with their impairments in learning probabilistic cue-outcome associations in a disorder-relevant context. In sum, the present results add to a growing body of research demonstrating that cognitive biases in OCD are context-dependent. Copyright © 2015. Published by Elsevier Ltd.
Walters, Caroline E; Kendal, Jeremy R
Epidemiological models have been applied to human health-related behaviors that are affected by social interaction. Typically these models have not considered conformity bias, that is, the exaggerated propensity to adopt commonly observed behaviors or opinions, or content biases, where the content of the learned trait affects the probability of adoption. Here we consider an interaction of these two effects, presenting an SIS-type model for the spread and persistence of a behavior which is transmitted via social learning. Uptake is controlled by a nonlinear dependence on the proportion of individuals demonstrating the behavior in a population. Three equilibrium solutions are found, their linear stability is analyzed and the results are compared with a model for unbiased social learning. Our analysis focuses on the effects of the strength of conformity bias and the effects of content biases which alter a conformity threshold frequency of the behavior, above which there is an exaggerated propensity for adoption. The strength of the conformity bias is found to qualitatively alter the predictions regarding whether the trait becomes endemic within the population and the proportion of individuals who display the trait when it is endemic. As the conformity strength increases, the number of feasible equilibrium solutions increases from two to three, leading to a situation where the stable equilibrium attained is dependent upon the initial state. Varying the conformity threshold frequency directionally alters the behavior invasion threshold. Finally we discuss the possible application of this model to binge drinking behavior. Copyright © 2013 Elsevier Inc. All rights reserved.
Inglis, Matthew; Simpson, Adrian
In this paper we briefly describe the dual process account of reasoning, and explain the role of heuristic biases in human thought. Concentrating on the so-called matching bias effect, we describe a piece of research that indicates a correlation between success at advanced level mathematics and an ability to override innate and misleading…
Marlène Elias; Susan S Hummel; Bimbika S Basnett; Carol J.P. Colfer
Gender biases persist in forestry research and practice. These biases result in reduced scientific rigor and inequitable, ineffective, and less efficient policies, programs, and interventions. Drawing from a two-volume collection of current and classic analyses on gender in forests, we outline five persistent and inter-related themes: gendered governance, tree tenure,...
It is 30 years since NAEYC published "Anti-Bias Curriculum Tools for Empowering Young Children" (Derman-Sparks & ABC Task Force, 1989). Since then, anti-bias education concepts have become part of the early childhood education (ECE) narrative in the United States and many other countries. It has brought a fresh way of thinking about…
Full Text Available Individuals’ gaze behavior reflects the choice they will ultimately make. For example, people confronting a choice among multiple stimuli tend to look longer at stimuli that are subsequently chosen than at other stimuli. This tendency, called the gaze bias effect, is a key aspect of visual decision-making. Nevertheless, no study has examined the generality of the gaze bias effect in older adults. Here, we used a two-alternative forced-choice task (2AFC to compare the gaze behavior reflective of different stages of decision processes demonstrated by younger and older adults. Participants who had viewed two faces were instructed to choose the one that they liked/disliked or the one that they judged to be more/less similar to their own face. Their eye movements were tracked while they chose. The results show that the gaze bias effect occurred during the remaining time in both age groups irrespective of the decision type. However, no gaze bias effect was observed for the preference judgment during the first dwell time. Our study demonstrated that the gaze bias during the remaining time occurred regardless of decision-making task and age. Further study using diverse participants, such as clinic patients or infants, may help to generalize the gaze bias effect and to elucidate the mechanisms underlying the gaze bias.
Adrian Viliami Bell
Full Text Available Evolutionary models broadly support a number of social learning strategies likely important in economic behavior. Using a simple model of price dynamics, I show how prestige bias, or copying of famed (and likely successful individuals, influences price equilibria and investor disposition in a way that exacerbates or creates market bubbles. I discuss how integrating the social learning and demographic forces important in cultural evolution with economic models provides a fruitful line of inquiry into real-world behavior.
Desjacques, Vincent; Jeong, Donghui; Schmidt, Fabian
This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy statistics. We then review the excursion-set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.
Jeong, Donghui; Desjacques, Vincent; Schmidt, Fabian
Here, we briefly introduce the key results of the recent review (arXiv:1611.09787), whose abstract is as following. This review presents a comprehensive overview of galaxy bias, that is, the statistical relation between the distribution of galaxies and matter. We focus on large scales where cosmic density fields are quasi-linear. On these scales, the clustering of galaxies can be described by a perturbative bias expansion, and the complicated physics of galaxy formation is absorbed by a finite set of coefficients of the expansion, called bias parameters. The review begins with a detailed derivation of this very important result, which forms the basis of the rigorous perturbative description of galaxy clustering, under the assumptions of General Relativity and Gaussian, adiabatic initial conditions. Key components of the bias expansion are all leading local gravitational observables, which include the matter density but also tidal fields and their time derivatives. We hence expand the definition of local bias to encompass all these contributions. This derivation is followed by a presentation of the peak-background split in its general form, which elucidates the physical meaning of the bias parameters, and a detailed description of the connection between bias parameters and galaxy (or halo) statistics. We then review the excursion set formalism and peak theory which provide predictions for the values of the bias parameters. In the remainder of the review, we consider the generalizations of galaxy bias required in the presence of various types of cosmological physics that go beyond pressureless matter with adiabatic, Gaussian initial conditions: primordial non-Gaussianity, massive neutrinos, baryon-CDM isocurvature perturbations, dark energy, and modified gravity. Finally, we discuss how the description of galaxy bias in the galaxies' rest frame is related to clustering statistics measured from the observed angular positions and redshifts in actual galaxy catalogs.
Full Text Available Neutrosophy can be widely applied in physics and the like. For example, one of the reasons for 2011 Nobel Prize for physics is "for the discovery of the accelerating expansion of the universe through observations of distant supernovae", but according to neutrosophy, there exist seven or nine states of accelerating expansion and contraction and the neutrosophic state in the universe. Another two examples are "a revision to Gödel's incompleteness theorem by neutrosophy" and "six neutral (neutrosophic fundamental interactions". In addition, the "partial and temporary unified theory so far" is discussed (including "partial and temporary unified electromagnetic theory so far", "partial and temporary unified gravitational theory so far", "partial and temporary unified theory of four fundamental interactions so far", and "partial and temporary unified theory of natural science so far".
Abell, Martha L
Maple by Example, Third Edition, is a reference/text with CD for beginning and experienced students, professional engineers, and other Maple users. This new edition has been updated to be compatible with the most recent release of the Maple software. Coverage includes built-in Maple commands used in courses and practices that involve calculus, linear algebra, business mathematics, ordinary and partial differential equations, numerical methods, graphics and more. The CD-ROM provides updated Maple input and all text from the book.* Updated coverage of Maple features and functions * Backwards compatible for all versions* New applications from a variety of fields, including biology, physics and engineering* Expanded topics with many additional examples
The concept of the plasma horizon, defined as the boundary of the region in which an infinitely thin plasma can be supported against Coulomb attraction by a magnetic field, shows that the argument of selective accretion does not rule out the existence of charged black holes embedded in a conducting plasma. A detailed account of the covariant definition of plasma horizon is given and some examples of plasma horizons are presented. 7 references
Bishop , Matt; Elliott , Chip
Part 2: WISE 7; International audience; Robust programming lies at the heart of the type of coding called “secure programming”. Yet it is rarely taught in academia. More commonly, the focus is on how to avoid creating well-known vulnerabilities. While important, that misses the point: a well-structured, robust program should anticipate where problems might arise and compensate for them. This paper discusses one view of robust programming and gives an example of how it may be taught.
Bülow, Anne Marie
This paper suggests that for negotiation studies, the well-researched role of cognitive closure in decision-making should be supplemented with specific research on what sort of information is seized on as unambiguous, salient and easily processable by negotiators. A study of email negotiation...... is reported that suggests that negotiators seize on concrete examples as building blocks that produce immediate positive feedback and consequent utilization in establishing common ground....
Cirka, Carol C.; Corrigall, Elizabeth A.
In this article, we demonstrate that an exercise using metaphors to overcome cognitive biases helped students to proactively imagine and prepare for an expanded set of potential crises. The exercise complements traditional textbook approaches to crisis management and incorporates creativity skill building in a realistic context. Learning outcomes…
Zimmermann, Jacqueline F.; Moscovitch, Morris; Alain, Claude
Long-term memory (LTM) has been shown to bias attention to a previously learned visual target location. Here, we examined whether memory-predicted spatial location can facilitate the detection of a faint pure tone target embedded in real world audio clips (e.g., soundtrack of a restaurant). During an initial familiarization task, participants…
Nuland, A.J.M. van; Helmich, R.C.G.; Dirkx, M.F.M.; Zach, H.; Bloem, B.R.; Toni, I.; Cools, R.; Ouden, H.E.M. den
Objective: Assess dopaminergic effects on choice bias in Parkinson's disease (PD). Background: Bradykinesia, rigidity and resting tremor are the core symptoms of PD, but many patients also suffer from cognitive dysfunction. For instance, PD patients have an increased tendency to learn from aversive
Full Text Available Nowadays learning technologies transformed educational systems with impressive progress of Information and Communication Technologies (ICT. Furthermore, when these technologies are available, affordable and accessible, they represent more than a transformation for people with disabilities. They represent real opportunities with access to an inclusive education and help to overcome the obstacles they met in classical educational systems. In this paper, we will cover basic concepts of e-accessibility, universal design and assistive technologies, with a special focus on accessible e-learning systems. Then, we will present recent research works conducted in our research Laboratory LaTICE toward the development of an accessible online learning environment for persons with disabilities from the design and specification step to the implementation. We will present, in particular, the accessible version “MoodleAcc+” of the well known e-learning platform Moodle as well as new elaborated generic models and a range of tools for authoring and evaluating accessible educational content.
Fox, Elaine; Ridgewell, Anna; Ashwin, Chris
Humans differ in terms of biased attention for emotional stimuli and these biases can confer differential resilience and vulnerability to emotional disorders. Selective processing of positive emotional information, for example, is associated with enhanced sociability and well-being while a bias for negative material is associated with neuroticism and anxiety. A tendency to selectively avoid negative material might also be associated with mental health and well-being. The neurobiological mecha...
Working definition of cognitive bias: Patterns by which information is sought and interpreted that can lead to systematic errors in decisions. Cognitive bias is used in diverse fields: Economics, Politics, Intelligence, Marketing, to name a few. Attempts to ground cognitive science in physical characteristics of the cognitive apparatus exceed our knowledge. Studies based on correlations; strict cause and effect is difficult to pinpoint. Effects cited in the paper and discussed here have been replicated many times over, and appear sound. Many biases have been described, but it is still unclear whether they are all distinct. There may only be a handful of fundamental biases, which manifest in various ways. Bias can effect system verification in many ways . Overconfidence -> Questionable decisions to deploy. Availability -> Inability to conceive critical tests. Representativeness -> Overinterpretation of results. Positive Test Strategies -> Confirmation bias. Debiasing at individual level very difficult. The potential effect of bias on the verification process can be managed, but not eliminated. Worth considering at key points in the process.
E S Nwauche
Full Text Available This article reviews the interpretation of section 6(2(aii of the Promotion of Administrative Justice Act which makes an administrator “biased or reasonably suspected of bias” a ground of judicial review. In this regard, the paper reviews the determination of administrative bias in South Africa especially highlighting the concept of institutional bias. The paper notes that inspite of the formulation of the bias ground of review the test for administrative bias is the reasonable apprehension test laid down in the case of President of South Africa v South African Rugby Football Union(2 which on close examination is not the same thing. Accordingly the paper urges an alternative interpretation that is based on the reasonable suspicion test enunciated in BTR Industries South Africa (Pty Ltd v Metal and Allied Workers Union and R v Roberts. Within this context, the paper constructs a model for interpreting the bias ground of review that combines the reasonable suspicion test as interpreted in BTR Industries and R v Roberts, the possibility of the waiver of administrative bias, the curative mechanism of administrative appeal as well as some level of judicial review exemplified by the jurisprudence of article 6(1 of the European Convention of Human Rights, especially in the light of the contemplation of the South African Magistrate Court as a jurisdictional route of judicial review.
Pulcu, Erdem; Browning, Michael
Affective bias, the tendency to differentially prioritise the processing of negative relative to positive events, is commonly observed in clinical and non-clinical populations. However, why such biases develop is not known. Using a computational framework, we investigated whether affective biases may reflect individuals' estimates of the information content of negative relative to positive events. During a reinforcement learning task, the information content of positive and negative outcomes was manipulated independently by varying the volatility of their occurrence. Human participants altered the learning rates used for the outcomes selectively, preferentially learning from the most informative. This behaviour was associated with activity of the central norepinephrine system, estimated using pupilometry, for loss outcomes. Humans maintain independent estimates of the information content of distinct positive and negative outcomes which may bias their processing of affective events. Normalising affective biases using computationally inspired interventions may represent a novel approach to treatment development.
Full Text Available Teaching critical thinking skill is a central pedagogical aim in many courses. These skills, it is hoped, will be both portable (applicable in a wide range of contexts and durable (not forgotten quickly. Yet, both of these virtues are challenged by pervasive and potent cognitive biases, such as motivated reasoning, false consensus bias and hindsight bias. In this paper, I argue that a focus on the development of metacognitive skill shows promise as a means to inculcate debiasing habits in students. Such habits will help students become more critical reasoners. I close with suggestions for implementing this strategy.
Marinković, Zlatica; Pronić-Rančić, Olivera; Marković, Vera
Empirical models of microwave transistors based on an equivalent circuit are valid for only one bias point. Bias-dependent analysis requires repeated extractions of the model parameters for each bias point. In order to make model bias-dependent, a new hybrid empirical-neural model of microwave field-effect transistors is proposed in this article. The model is a combination of an equivalent circuit model including noise developed for one bias point and two prior knowledge input artificial neural networks (PKI ANNs) aimed at introducing bias dependency of scattering (S) and noise parameters, respectively. The prior knowledge of the proposed ANNs involves the values of the S- and noise parameters obtained by the empirical model. The proposed hybrid model is valid in the whole range of bias conditions. Moreover, the proposed model provides better accuracy than the empirical model, which is illustrated by an appropriate modelling example of a pseudomorphic high-electron mobility transistor device.
Benoit, William Lyon
Examines the concept of example in Aristotle's inventional theory. Rejects recent claims that the example reasons from part to part, without a mediating generalization, and then explicates Aristotle's view of the example. (JMF)
Welnicka, Katarzyna; Bærentzen, Jakob Andreas; Aanæs, Henrik
We address the problem of analysis of families of shapes which can be classified according to two categories: the main one corresponding usually to the coarse shape which we call the function and the more subtle one which we call the style. The style and the function both contribute to the overal...... this similarity should be reflected across different functions. We show the usability of our methods first on the example of a number of chess sets which our method helps sort. Next, we investigate the problem of finding a replacement for a missing tooth given a database of teeth....
An example of feedstock optimization at an olefins plant which has the flexibility to process different kinds of raw materials while maintaining the same product slate, is presented. Product demand and prices, and the number of units in service as well as the required resources to operate these units are considered to be fixed. The plant profitability is a function of feedstock choice, plus constant costs which are the non-volume related costs. The objective is to find a set or combination of feedstocks that could match the client product demands and fall within the unit's design and capacity, while maximizing the financial operating results
A Beginner's Guide following the ""by Example"" approach. There will be 5-8 major examples that will be used in the book to develop advanced plugins with the Eclipse IDE.This book is for Java developers who are familiar with Eclipse as a Java IDE and are interested in learning how to develop plug-ins for Eclipse. No prior knowledge of Eclipse plug-in development or OSGi is necessary, although you are expected to know how to create, run, and debug Java programs in Eclipse.
A literacy coach collaborates with a new teacher to incorporate structured note-taking and summarizing into a science class. Many students struggle with these skills and require explicit instruction before they are able to work independently. Using the gradual release of responsibility framework, the literacy coach begins by modeling how to choose…
Wiederman, Michael W.
Suggests that instructors teaching psychological assessment can use a demonstration to illustrate potential biases when subjectively interpreting response to projective stimuli. Outlines the classroom procedure, notes styles of learning involved, and presents a summary of student evaluations. (DSK)
Engaging Citizens In Discussions of Coastal Climate ChangeTwo examples of place-based research that engaged community members will be presented. Lessons learned in how to engage community members and working with high school students and hands-on learning across generations can provide insights into social and ecosystem change will be shared.
Kruger, L. E.; Johnson, A. C.
By engaging community members as research partners, people become not just the subject of the story, they become storytellers as well. Participatory community-based research that engages community residents in gathering and sharing their lived experiences is instrumental in connecting people to each other and their forests and forest science and helpful when confronted by change. Two examples of place-based research that engaged community members as researchers will be presented. What factors led to collaborative outcomes that integrated citizen-informed knowledge with scientific knowledge? What lessons were learned in how best to engage community members? How did working with high school students draw even hesitant members of the community to participate? By strengthening bonds between students and their communities, both natural and social environments, we can provide young people with opportunities to better understand how they fit into the greater community and their natural environment. Hands-on learning that explores experiences in nature across generations can benefit communities, especially youth, and can provide insights into social and ecosystem change.
S. Roy (Santanu); J.M.A. Viaene (Jean-Marie)
textabstractAnalyzes international trade where consumer preferences exhibit country bias. Why country biases arise; How trade can occur in the presence of country bias; Implication for the pattern of trade and specialization.
Joshua L Kalla
Full Text Available The Internet has dramatically expanded citizens' access to and ability to engage with political information. On many websites, any user can contribute and edit "crowd-sourced" information about important political figures. One of the most prominent examples of crowd-sourced information on the Internet is Wikipedia, a free and open encyclopedia created and edited entirely by users, and one of the world's most accessed websites. While previous studies of crowd-sourced information platforms have found them to be accurate, few have considered biases in what kinds of information are included. We report the results of four randomized field experiments that sought to explore what biases exist in the political articles of this collaborative website. By randomly assigning factually true but either positive or negative and cited or uncited information to the Wikipedia pages of U.S. senators, we uncover substantial evidence of an editorial bias toward positivity on Wikipedia: Negative facts are 36% more likely to be removed by Wikipedia editors than positive facts within 12 hours and 29% more likely within 3 days. Although citations substantially increase an edit's survival time, the editorial bias toward positivity is not eliminated by inclusion of a citation. We replicate this study on the Wikipedia pages of deceased as well as recently retired but living senators and find no evidence of an editorial bias in either. Our results demonstrate that crowd-sourced information is subject to an editorial bias that favors the politically active.
Kalla, Joshua L; Aronow, Peter M
The Internet has dramatically expanded citizens' access to and ability to engage with political information. On many websites, any user can contribute and edit "crowd-sourced" information about important political figures. One of the most prominent examples of crowd-sourced information on the Internet is Wikipedia, a free and open encyclopedia created and edited entirely by users, and one of the world's most accessed websites. While previous studies of crowd-sourced information platforms have found them to be accurate, few have considered biases in what kinds of information are included. We report the results of four randomized field experiments that sought to explore what biases exist in the political articles of this collaborative website. By randomly assigning factually true but either positive or negative and cited or uncited information to the Wikipedia pages of U.S. senators, we uncover substantial evidence of an editorial bias toward positivity on Wikipedia: Negative facts are 36% more likely to be removed by Wikipedia editors than positive facts within 12 hours and 29% more likely within 3 days. Although citations substantially increase an edit's survival time, the editorial bias toward positivity is not eliminated by inclusion of a citation. We replicate this study on the Wikipedia pages of deceased as well as recently retired but living senators and find no evidence of an editorial bias in either. Our results demonstrate that crowd-sourced information is subject to an editorial bias that favors the politically active.
Domaradzka, Ewa; Bielecki, Maksymilian
Numerous studies have shown that biases in visual attention might be evoked by affective and personally relevant stimuli, for example addiction-related objects. Despite the fact that addiction is often linked to specific products and systematic purchase behaviors, no studies focused directly on the existence of bias evoked by brands. Smokers are characterized by high levels of brand loyalty and everyday contact with cigarette packaging. Using the incentive-salience mechanism as a theoretical framework, we hypothesized that this group might exhibit a bias toward the preferred cigarette brand. In our study, a group of smokers ( N = 40) performed a dot probe task while their eye movements were recorded. In every trial a pair of pictures was presented - each of them showed a single cigarette pack. The visual properties of stimuli were carefully controlled, so branding information was the key factor affecting subjects' reactions. For each participant, we compared gaze behavior related to the preferred vs. other brands. The analyses revealed no attentional bias in the early, orienting phase of the stimulus processing and strong differences in maintenance and disengagement. Participants spent more time looking at the preferred cigarettes and saccades starting at the preferred brand location had longer latencies. In sum, our data shows that attentional bias toward brands might be found in situations not involving choice or decision making. These results provide important insights into the mechanisms of formation and maintenance of attentional biases to stimuli of personal relevance and might serve as a first step toward developing new attitude measurement techniques.
Moher, Jeff; Song, Joo-Hyun
Target selection is often biased by an observer's recent experiences. However, not much is known about whether these selection biases influence behavior across different effectors. For example, does looking at a red object make it easier to subsequently reach towards another red object? In the current study, we asked observers to find the uniquely colored target object on each trial. Randomly intermixed pre-trial cues indicated the mode of action: either an eye movement or a visually guided reach movement to the target. In Experiment 1, we found that priming of popout, reflected in faster responses following repetition of the target color on consecutive trials, occurred regardless of whether the effector was repeated from the previous trial or not. In Experiment 2, we examined whether an inhibitory selection bias away from a feature could transfer across effectors. While priming of popout reflects both enhancement of the repeated target features and suppression of the repeated distractor features, the distractor previewing effect isolates a purely inhibitory component of target selection in which a previewed color is presented in a homogenous display and subsequently inhibited. Much like priming of popout, intertrial suppression biases in the distractor previewing effect transferred across effectors. Together, these results suggest that biases for target selection driven by recent trial history transfer across effectors. This indicates that representations in memory that bias attention towards or away from specific features are largely independent from their associated actions.
Nutt, Paul C.
The consequences and dilemmas posed by learning issues for decision making are discussed. Learning requires both awareness of barriers and a coping strategy. The motives to hold back information essential for learning stem from perverse incentives, obscure outcomes, and the hindsight bias. There is little awareness of perverse incentives that…
Culbertson, Jennifer; Kirby, Simon
The extent to which the linguistic system—its architecture, the representations it operates on, the constraints it is subject to—is specific to language has broad implications for cognitive science and its relation to evolutionary biology. Importantly, a given property of the linguistic system can be “specific” to the domain of language in several ways. For example, if the property evolved by natural selection under the pressure of the linguistic function it serves then the property is domain-specific in the sense that its design is tailored for language. Equally though, if that property evolved to serve a different function or if that property is domain-general, it may nevertheless interact with the linguistic system in a way that is unique. This gives a second sense in which a property can be thought of as specific to language. An evolutionary approach to the language faculty might at first blush appear to favor domain-specificity in the first sense, with individual properties of the language faculty being specifically linguistic adaptations. However, we argue that interactions between learning, culture, and biological evolution mean any domain-specific adaptations that evolve will take the form of weak biases rather than hard constraints. Turning to the latter sense of domain-specificity, we highlight a very general bias, simplicity, which operates widely in cognition and yet interacts with linguistic representations in domain-specific ways. PMID:26793132
Libarkin, J. C.; Gold, A. U.; Harris, S. E.; McNeal, K.; Bowles, R.
Understanding learning in geoscience classrooms requires that we use valid and reliable instruments aligned with intended learning outcomes. Nearly one hundred instruments assessing conceptual understanding in undergraduate science and engineering classrooms (often called concept inventories) have been published and are actively being used to investigate learning. The techniques used to develop these instruments vary widely, often with little attention to psychometric principles of measurement. This paper will discuss the importance of using psychometric principles to design, evaluate, and revise research instruments, with particular attention to the validity and reliability steps that must be undertaken to ensure that research instruments are providing meaningful measurement. An example from a climate change inventory developed by the authors will be used to exemplify the importance of validity and reliability, including the value of item response theory for instrument development. A 24-item instrument was developed based on published items, conceptions research, and instructor experience. Rasch analysis of over 1000 responses provided evidence for the removal of 5 items for misfit and one item for potential bias as measured via differential item functioning. The resulting 18-item instrument can be considered a valid and reliable measure based on pre- and post-implementation metrics. Consideration of the relationship between respondent demographics and concept inventory scores provides unique insight into the relationship between gender, religiosity, values and climate change understanding.
Yeung, Sai Wing
People often makes inductive inferences that go beyond the data that are given. In order to generate these inferences, people must rely on inductive biases - constraints on learning that guide conclusion from limited data. This thesis presents a survey of three topics concerning people's inductive biases.The first part of this thesis examines people's expectations about the strengths of causes in elemental causal induction - learning about the relationship between a single cause and effect. T...
Full Text Available The behavioral and cognitive characteristics of dangerous drivers differ significantly from those of safe drivers. However, differences in emotional information processing have seldom been investigated. Previous studies have revealed that drivers with higher anger/anxiety trait scores are more likely to be involved in crashes and that individuals with higher anger traits exhibit stronger negativity biases when processing emotions compared with control groups. However, researchers have not explored the relationship between emotional information processing and driving behavior. In this study, we examined the emotional information processing differences between dangerous drivers and safe drivers. Thirty-eight non-professional drivers were divided into two groups according to the penalty points that they had accrued for traffic violations: 15 drivers with 6 or more points were included in the dangerous driver group, and 23 drivers with 3 or fewer points were included in the safe driver group. The emotional Stroop task was used to measure negativity biases, and both behavioral and electroencephalograph data were recorded. The behavioral results revealed stronger negativity biases in the dangerous drivers than in the safe drivers. The bias score was correlated with self-reported dangerous driving behavior. Drivers with strong negativity biases reported having been involved in mores crashes compared with the less-biased drivers. The event-related potentials (ERPs revealed that the dangerous drivers exhibited reduced P3 components when responding to negative stimuli, suggesting decreased inhibitory control of information that is task-irrelevant but emotionally salient. The influence of negativity bias provides one possible explanation of the effects of individual differences on dangerous driving behavior and traffic crashes.
Wagner, Elaine Rumsey; Orme, Susan Marla; Turner, Heidi Jean; Yopp, David
Mathematicians use example generation to test and verify mathematical ideas; however, the processes through which undergraduates learn to productively generate examples are not well understood. We engaged calculus students in a teaching experiment designed to develop skills in productively generating examples to learn novel concepts. This article…
Krieger, Miriam; Felder, Stefan
Rather than conforming to the assumption of perfect rationality in neoclassical economic theory, decision behavior has been shown to display a host of systematic biases. Properly understood, these patterns can be instrumentalized to improve outcomes in the public realm. We conducted a laboratory experiment to study whether decisions over health insurance policies are subject to status quo bias and, if so, whether experience mitigates this framing effect. Choices in two treatment groups with status quo defaults are compared to choices in a neutrally framed control group. A two-step design features sorting of subjects into the groups, allowing us to control for selection effects due to risk preferences. The results confirm the presence of a status quo bias in consumer choices over health insurance policies. However, this effect of the default framing does not persist as subjects repeat this decision in later periods of the experiment. Our results have implications for health care policy, for example suggesting that the use of non-binding defaults in health insurance can facilitate the spread of co-insurance policies and thereby help contain health care expenditure.
Krieger, Miriam; Felder, Stefan
Rather than conforming to the assumption of perfect rationality in neoclassical economic theory, decision behavior has been shown to display a host of systematic biases. Properly understood, these patterns can be instrumentalized to improve outcomes in the public realm. We conducted a laboratory experiment to study whether decisions over health insurance policies are subject to status quo bias and, if so, whether experience mitigates this framing effect. Choices in two treatment groups with status quo defaults are compared to choices in a neutrally framed control group. A two-step design features sorting of subjects into the groups, allowing us to control for selection effects due to risk preferences. The results confirm the presence of a status quo bias in consumer choices over health insurance policies. However, this effect of the default framing does not persist as subjects repeat this decision in later periods of the experiment. Our results have implications for health care policy, for example suggesting that the use of non-binding defaults in health insurance can facilitate the spread of co-insurance policies and thereby help contain health care expenditure. PMID:23783222
Full Text Available Rather than conforming to the assumption of perfect rationality in neoclassical economic theory, decision behavior has been shown to display a host of systematic biases. Properly understood, these patterns can be instrumentalized to improve outcomes in the public realm. We conducted a laboratory experiment to study whether decisions over health insurance policies are subject to status quo bias and, if so, whether experience mitigates this framing effect. Choices in two treatment groups with status quo defaults are compared to choices in a neutrally framed control group. A two-step design features sorting of subjects into the groups, allowing us to control for selection effects due to risk preferences. The results confirm the presence of a status quo bias in consumer choices over health insurance policies. However, this effect of the default framing does not persist as subjects repeat this decision in later periods of the experiment. Our results have implications for health care policy, for example suggesting that the use of non-binding defaults in health insurance can facilitate the spread of co-insurance policies and thereby help contain health care expenditure.
Tattar, Narayanachart Prabhanjan
Full of screenshots and examples, this Beginner's Guide by Example will teach you practically everything you need to know about R statistical application development from scratch. You will begin learning the first concepts of statistics in R which is vital in this fast paced era and it is also a bargain as you do not need to do a preliminary course on the subject.
Golob, Edward J; Lewald, Jörg; Getzmann, Stephan; Mock, Jeffrey R
Speech recognition starts with representations of basic acoustic perceptual features and ends by categorizing the sound based on long-term memory for word meaning. However, little is known about whether the reverse pattern of lexical influences on basic perception can occur. We tested for a lexical influence on auditory spatial perception by having subjects make spatial judgments of number stimuli. Four experiments used pointing or left/right 2-alternative forced choice tasks to examine perceptual judgments of sound location as a function of digit magnitude (1-9). The main finding was that for stimuli presented near the median plane there was a linear left-to-right bias for localizing smaller-to-larger numbers. At lateral locations there was a central-eccentric location bias in the pointing task, and either a bias restricted to the smaller numbers (left side) or no significant number bias (right side). Prior number location also biased subsequent number judgments towards the opposite side. Findings support a lexical influence on auditory spatial perception, with a linear mapping near midline and more complex relations at lateral locations. Results may reflect coding of dedicated spatial channels, with two representing lateral positions in each hemispace, and the midline area represented by either their overlap or a separate third channel.
Sukhera, Javeed; Watling, Chris
Existing literature on implicit bias is fragmented and comes from a variety of fields like cognitive psychology, business ethics, and higher education, but implicit-bias-informed educational approaches have been underexplored in health professions education and are difficult to evaluate using existing tools. Despite increasing attention to implicit bias recognition and management in health professions education, many programs struggle to meaningfully integrate these topics into curricula. The authors propose a six-point actionable framework for integrating implicit bias recognition and management into health professions education that draws on the work of previous researchers and includes practical tools to guide curriculum developers. The six key features of this framework are creating a safe and nonthreatening learning context, increasing knowledge about the science of implicit bias, emphasizing how implicit bias influences behaviors and patient outcomes, increasing self-awareness of existing implicit biases, improving conscious efforts to overcome implicit bias, and enhancing awareness of how implicit bias influences others. Important considerations for designing implicit-bias-informed curricula-such as individual and contextual variables, as well as formal and informal cultural influences-are discussed. The authors also outline assessment and evaluation approaches that consider outcomes at individual, organizational, community, and societal levels. The proposed framework may facilitate future research and exploration regarding the use of implicit bias in health professions education.
Several ways for detection and assessment of collinearity in measured data are discussed. Because data collinearity usually results in poor least squares estimates, two estimation techniques which can limit a damaging effect of collinearity are presented. These two techniques, the principal components regression and mixed estimation, belong to a class of biased estimation techniques. Detection and assessment of data collinearity and the two biased estimation techniques are demonstrated in two examples using flight test data from longitudinal maneuvers of an experimental aircraft. The eigensystem analysis and parameter variance decomposition appeared to be a promising tool for collinearity evaluation. The biased estimators had far better accuracy than the results from the ordinary least squares technique.
Cottam, Joseph A.; Blaha, Leslie M.
Systems have biases. Their interfaces naturally guide a user toward specific patterns of action. For example, modern word-processors and spreadsheets are both capable of taking word wrapping, checking spelling, storing tables, and calculating formulas. You could write a paper in a spreadsheet or could do simple business modeling in a word-processor. However, their interfaces naturally communicate which function they are designed for. Visual analytic interfaces also have biases. In this paper, we outline why simple Markov models are a plausible tool for investigating that bias and how they might be applied. We also discuss some anticipated difficulties in such modeling and touch briefly on what some Markov model extensions might provide.
Kvita, Jiri; The ATLAS collaboration
The modelling of Minimum Bias (MB) is a crucial ingredient to learn about the description of soft QCD processes. It has also a significant relevance for the simulation of the environment at the LHC with many concurrent pp interactions (“pileup”). The ATLAS collaboration has provided new measurements of the inclusive charged particle multiplicity and its dependence on transverse momentum and pseudorapidity in special data sets with low LHC beam currents, recorded at center of mass energies of 8 TeV and 13 TeV. The measurements cover a wide spectrum using charged particle selections with minimum transverse momentum of both 100 MeV and 500 MeV and in various phase space regions of low and high charged particle multiplicities.
Yi Xiang; Miklos Sarvary
Bias in the market for news is well-documented. Recent research in economics explains the phenomenon by assuming that consumers want to read (watch) news that is consistent with their tastes or prior beliefs rather than the truth. The present paper builds on this idea but recognizes that (i) besides “biased” consumers, there are also “conscientious” consumers whose sole interest is in discovering the truth, and (ii) consistent with reality, media bias is constrained by the truth. These two fa...
Phillips, P.E.; Wootton, A.J.; Rowan, W.L.; Ritz, C.P.; Rhodes, T.L.; Bengtson, R.D.; Hodge, W.L.; Durst, R.D.; McCool, S.C.; Richards, B.; Gentle, K.W.; Schoch, P.; Forster, J.C.; Hickok, R.L.; Evans, T.E.
Experiments using an electrically biased limiter have been performed on the Texas Experimental Tokamak (TEXT). A small movable limiter is inserted past the main poloidal ring limiter (which is electrically connected to the vacuum vessel) and biased at V Lim with respect to it. The floating potential, plasma potential and shear layer position can be controlled. With vertical strokeV Lim vertical stroke ≥ 50 V the plasma density increases. For V Lim Lim > 0 the results obtained are inconclusive. Variation of V Lim changes the electrostatic turbulence which may explain the observed total flux changes. (orig.)
Full Text Available Abstract Reporting bias represents a major problem in the assessment of health care interventions. Several prominent cases have been described in the literature, for example, in the reporting of trials of antidepressants, Class I anti-arrhythmic drugs, and selective COX-2 inhibitors. The aim of this narrative review is to gain an overview of reporting bias in the medical literature, focussing on publication bias and selective outcome reporting. We explore whether these types of bias have been shown in areas beyond the well-known cases noted above, in order to gain an impression of how widespread the problem is. For this purpose, we screened relevant articles on reporting bias that had previously been obtained by the German Institute for Quality and Efficiency in Health Care in the context of its health technology assessment reports and other research work, together with the reference lists of these articles. We identified reporting bias in 40 indications comprising around 50 different pharmacological, surgical (e.g. vacuum-assisted closure therapy, diagnostic (e.g. ultrasound, and preventive (e.g. cancer vaccines interventions. Regarding pharmacological interventions, cases of reporting bias were, for example, identified in the treatment of the following conditions: depression, bipolar disorder, schizophrenia, anxiety disorder, attention-deficit hyperactivity disorder, Alzheimer's disease, pain, migraine, cardiovascular disease, gastric ulcers, irritable bowel syndrome, urinary incontinence, atopic dermatitis, diabetes mellitus type 2, hypercholesterolaemia, thyroid disorders, menopausal symptoms, various types of cancer (e.g. ovarian cancer and melanoma, various types of infections (e.g. HIV, influenza and Hepatitis B, and acute trauma. Many cases involved the withholding of study data by manufacturers and regulatory agencies or the active attempt by manufacturers to suppress publication. The ascertained effects of reporting bias included the
Layton, Danielle M; Clarke, Michael
To review how articles are retrieved from bibliographic databases, what article identification and translation problems have affected research, and how these problems can contribute to research waste and affect clinical practice. This literature review sought and appraised articles regarding identification- and translation-bias in the medical and dental literature, which limit the ability of users to find research articles and to use these in practice. Articles can be retrieved from bibliographic databases by performing a word or index-term (for example, MeSH for MEDLINE) search. Identification of articles is challenging when it is not clear which words are most relevant, and which terms have been allocated to indexing fields. Poor reporting quality of abstracts and articles has been reported across the medical literature at large. Specifically in dentistry, research regarding time-to-event survival analyses found the allocation of MeSH terms to be inconsistent and inaccurate, important words were omitted from abstracts by authors, and the quality of reporting in the body of articles was generally poor. These shortcomings mean that articles will be difficult to identify, and difficult to understand if found. Use of specialized electronic search strategies can decrease identification bias, and use of tailored reporting guidelines can decrease translation bias. Research that cannot be found, or cannot be used results in research waste, and undermines clinical practice. Identification- and translation-bias have been shown to affect time-to-event dental articles, are likely affect other fields of research, and are largely unrecognized by authors and evidence seekers alike. By understanding that the problems exist, solutions can be sought to improve identification and translation of our research. Copyright © 2015 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.
Winegard, Bo; Reynolds, Tania; Baumeister, Roy F.; Plant, E. Ashby
Research indicates that antigay bias follows a specific pattern (and probably has throughout written history, at least in the West): (a) men evince more antigay bias than women; (b) men who belong to traditionally male coalitions evince more antigay bias than those who do not; (c) antigay bias is
Sekar Akrom Faradiza
Balanced Scorecard (BSC is a comprehensive performance measurement. BSC is not only used financial indicators but also non financial indicators there are customer, internal process business and learning and growth perspective. By using BSC, evaluators have common and unique measures. When evaluate manager performance, evaluator tends to only use common measures and ignore unique measures. This is called common measures bias. This study aims to investigate whether dissaggregated and aggregated BSC and management communication can overcome common measures bias and intent to BSC approach. This study also will evaluate whether these approach will affect evaluator decision when allocated compensation. We conduct 2x2x2 experiment of undergraduate accounting students. Participant act as a senior manager and evaluate the performance of two divisions and then allocated the bonus. ANOVA repeated measurement are used to conduct hypothesis test. The results showed that dissaggregated BSC and management communication could not overcome common measures bias but effected management decision when allocated compensation.
Alex F. Mendelson
Full Text Available The last decade has seen a great proliferation of supervised learning pipelines for individual diagnosis and prognosis in Alzheimer's disease. As more pipelines are developed and evaluated in the search for greater performance, only those results that are relatively impressive will be selected for publication. We present an empirical study to evaluate the potential for optimistic bias in classification performance results as a result of this selection. This is achieved using a novel, resampling-based experiment design that effectively simulates the optimisation of pipeline specifications by individuals or collectives of researchers using cross validation with limited data. Our findings indicate that bias can plausibly account for an appreciable fraction (often greater than half of the apparent performance improvement associated with the pipeline optimisation, particularly in small samples. We discuss the consistency of our findings with patterns observed in the literature and consider strategies for bias reduction and mitigation.
Srinivasan, Mahesh; Barner, David
How does world knowledge interact with syntax to constrain linguistic interpretation? We explored this question by testing children's acquisition of verbs like weed and water, which have opposite meanings despite occurring in the same syntactic frames. Whereas "weed the garden" treats "the garden" as a source, "water the garden" treats it as a goal. In five experiments, we asked how children learn these verbs. Previous theories predict that verbs which describe the transfer of an object with respect to its natural origin (e.g., "weed the garden") should receive source interpretations, whereas verbs that describe the transfer of an object with respect to something it is functionally related to (e.g., "water the garden") should receive goal interpretations. Therefore, acquiring world knowledge - about the natural origins and functional uses of objects - should be sufficient for differentiating between source and goal meanings. Experiments 1 and 2 casted doubt on this hypothesis, as 4- and 5-year-olds failed to use their world knowledge when interpreting these verbs and instead overextended goal interpretations. For example, children interpreted "weed the garden" to mean "put weeds onto a garden", even when they knew the natural origin of weeds. Experiment 3 tested children's interpretation of novel verbs and directly manipulated their access to relevant world knowledge. While younger children continued to exhibit a goal bias and failed to use world knowledge, older children generalized goal and source interpretations to novel verbs according to world knowledge. In Experiments 4 and 5, we confirmed that adults use world knowledge to guide their interpretation of novel verbs, but also showed that even adults prefer goal interpretations when they are made contextually plausible. We argue that children ultimately overcome a goal bias by learning to use their world knowledge to weigh the plausibility of events (e.g., of putting weeds into a garden). Copyright © 2013
Erfolgreiches Lernen in einem Blended Learning-Szenario im Vergleich mit der Präsenzausbildung - am Beispiel einer MTA-Ausbildung der Fachrichtung Radiologie [Successful learning in a blended learning scenario in comparison with face-to-face instruction - illustrated by the example of the training of medical technical assistants specialising in radiology
Full Text Available [english] Purpose: This article presents partial results of an evaluation study which compared a three-year blended learning scenario with traditional face-to-face training for medical technical assistants specialising in radiology. Methods: The blended learning approach investigated here is based on an individual tutoring approach, i.e. students work on the necessary training units during self-learning periods, while a tutor is available at all times via the Internet. Following the theory of constructivism, the tutor should see him- or herself as a coach supporting the learner working on the individual training units. As the Saarland University Hospital offers both face-to-face training and the blended learning course, it was possible to perform direct comparative tests. Results: On the basis of the final state examination results, it could be shown that the participants of the blended learning course achieved equivalent or slightly better exam results. Conclusion: The positive results of the blended learning participants gain increased significance against the backdrop of the demographic data of both groups of participants: with an average age of 43 (median: 43, the blended learning participants show a significantly higher life experience compared to the face-to-face training participants, who had an average age of 28 (median: 25. That shows that the blended learning method is a good method to be used by people working in radiology. [german] Zielsetzung: Dieser Artikel stellt Teilergebnisse einer Evaluationsstudie dar, deren Zielsetzung es ist, ein dreijähriges Blended learning-Szenario mit einer klassischen Präsenzausbildung für medizinisch-technische Assistenten der Fachrichtung Radiologie zu vergleichen. Methodik: Der hier untersuchte Blended Learning-Ansatz beruht auf einem individuellen Betreuungsansatz, d. h. während die Teilnehmenden in den Selbstlernphasen die Unterrichtseinheiten bearbeiten, steht jederzeit via Internet ein
Zou, G; Skeel, R D; Subramaniam, S
An enhanced sampling method-biased Brownian dynamics-is developed for the calculation of diffusion-limited biomolecular association reaction rates with high energy or entropy barriers. Biased Brownian dynamics introduces a biasing force in addition to the electrostatic force between the reactants, and it associates a probability weight with each trajectory. A simulation loses weight when movement is along the biasing force and gains weight when movement is against the biasing force. The sampl...
Bellaera, Lauren; von Mühlenen, Adrian; Watson, Derrick G
Repeated contexts allow us to find relevant information more easily. Learning such contexts has been proposed to depend upon either global processing of the repeated contexts, or alternatively processing of the local region surrounding the target information. In this study, we measured the extent to which observers were by default biased to process towards a more global or local level. The findings showed that the ability to use context to help guide their search was strongly related to an observer's local/global processing bias. Locally biased people could use context to help improve their search better than globally biased people. The results suggest that the extent to which context can be used depends crucially on the observer's attentional bias and thus also to factors and influences that can change this bias.
Full Text Available We live almost literally immersed in an artificial visual world, especially motion pictures. In this exploratory study, we asked whether the best speed for reproducing a video is its original, shooting speed. By using adjustment and double staircase methods, we examined speed biases in viewing real-life video clips in three experiments, and assessed their robustness by manipulating visual and auditory factors. With the tested stimuli (short clips of human motion, mixed human-physical motion, physical motion and ego-motion, speed underestimation was the rule rather than the exception, although it depended largely on clip content, ranging on average from 2% (ego-motion to 32% (physical motion. Manipulating display size or adding arbitrary soundtracks did not modify these speed biases. Estimated speed was not correlated with estimated duration of these same video clips. These results indicate that the sense of speed for real-life video clips can be systematically biased, independently of the impression of elapsed time. Measuring subjective visual tempo may integrate traditional methods that assess time perception: speed biases may be exploited to develop a simple, objective test of reality flow, to be used for example in clinical and developmental contexts. From the perspective of video media, measuring speed biases may help to optimize video reproduction speed and validate “natural” video compression techniques based on sub-threshold temporal squeezing.
Malo, Aurelio F; Martinez-Pastor, Felipe; Garcia-Gonzalez, Francisco; Garde, Julián; Ballou, Jonathan D; Lacy, Robert C
Sex ratio allocation has important fitness consequences, and theory predicts that parents should adjust offspring sex ratio in cases where the fitness returns of producing male and female offspring vary. The ability of fathers to bias offspring sex ratios has traditionally been dismissed given the expectation of an equal proportion of X- and Y-chromosome-bearing sperm (CBS) in ejaculates due to segregation of sex chromosomes at meiosis. This expectation has been recently refuted. Here we used Peromyscus leucopus to demonstrate that sex ratio is explained by an exclusive effect of the father, and suggest a likely mechanism by which male-driven sex-ratio bias is attained. We identified a male sperm morphological marker that is associated with the mechanism leading to sex ratio bias; differences among males in the sperm nucleus area (a proxy for the sex chromosome that the sperm contains) explain 22% variation in litter sex ratio. We further show the role played by the sperm nucleus area as a mediator in the relationship between individual genetic variation and sex-ratio bias. Fathers with high levels of genetic variation had ejaculates with a higher proportion of sperm with small nuclei area. This, in turn, led to siring a higher proportion of sons (25% increase in sons per 0.1 decrease in the inbreeding coefficient). Our results reveal a plausible mechanism underlying unexplored male-driven sex-ratio biases. We also discuss why this pattern of paternal bias can be adaptive. This research puts to rest the idea that father contribution to sex ratio variation should be disregarded in vertebrates, and will stimulate research on evolutionary constraints to sex ratios-for example, whether fathers and mothers have divergent, coinciding, or neutral sex allocation interests. Finally, these results offer a potential explanation for those intriguing cases in which there are sex ratio biases, such as in humans. © 2017 The Author(s).
Robinson, Jessica A.
Courses: This activity can be used in a wide range of classes, including interpersonal communication, introduction to communication, and small group communication. Objectives: After completing this activity, students should be able to: (1) define attribution theory, personality attribution, situational attribution, and attribution bias; (2)…
Pedersen, Rasmus Tue
Numbers permeate modern political communication. While current scholarship on framing effects has focused on the persuasive effects of words and arguments, this article shows that framing of numbers can also substantially affect policy preferences. Such effects are caused by ratio bias, which...
Carvalho, André F; Köhler, Cristiano A; Brunoni, André R
BACKGROUND: To aid in the differentiation of individuals with major depressive disorder (MDD) from healthy controls, numerous peripheral biomarkers have been proposed. To date, no comprehensive evaluation of the existence of bias favoring the publication of significant results or inflating effect...
Since the restart of the LHC in November 2009, ATLAS has collected inelastic pp collisions to perform first measurements on charged particle densities. These measurements will help to constrain various models describing phenomenologically soft parton interactions. Understanding the trigger efficiencies for different event types are therefore crucial to minimize any possible bias in the event selection. ATLAS uses two main minimum bias triggers, featuring complementary detector components and trigger levels. While a hardware based first trigger level situated in the forward regions with 2.2 < |η| < 3.8 has been proven to select pp-collisions very efficiently, the Inner Detector based minimum bias trigger uses a random seed on filled bunches and central tracking detectors for the event selection. Both triggers were essential for the analysis of kinematic spectra of charged particles. Their performance and trigger efficiency measurements as well as studies on possible bias sources will be presented. We also highlight the advantage of these triggers for particle correlation analyses. (author)
Mengel, Friederike; Sauermann, Jan; Zölitz, Ulf Zoelitz
This paper provides new evidence on gender bias in teaching evaluations. We exploit a quasi-experimental dataset of 19,952 student evaluations of university faculty in a context where students are randomly allocated to female or male instructors. Despite the fact that neither students’ grades nor
Full Text Available Cognitive theory from the field of general anxiety suggests that the tendency to display attentional bias toward negative information results in anxiety. Accordingly, the current study aims to investigate whether attentional bias is involved in math anxiety as well (i.e., a persistent negative reaction to math. Twenty seven participants (14 with high levels of math anxiety and 13 with low levels of math anxiety were presented with a novel computerized numerical version of the well established dot probe task. One of 6 types of prime stimuli, either math related or typically neutral, were presented on one side of a computer screen. The prime was preceded by a probe (either one or two asterisks that appeared in either the prime or the opposite location. Participants had to discriminate probe identity (one or two asterisks. Math anxious individuals reacted faster when the probe was at the location of the numerical related stimuli. This suggests the existence of attentional bias in math anxiety. That is, for math anxious individuals, the cognitive system selectively favored the processing of emotionally negative information (i.e., math related words. These findings suggest that attentional bias is linked to unduly intense math anxiety symptoms.
Rubinsten, Orly; Eidlin, Hili; Wohl, Hadas; Akibli, Orly
Cognitive theory from the field of general anxiety suggests that the tendency to display attentional bias toward negative information results in anxiety. Accordingly, the current study aims to investigate whether attentional bias is involved in math anxiety (MA) as well (i.e., a persistent negative reaction to math). Twenty seven participants (14 with high levels of MA and 13 with low levels of MA) were presented with a novel computerized numerical version of the well established dot probe task. One of six types of prime stimuli, either math related or typically neutral, was presented on one side of a computer screen. The prime was preceded by a probe (either one or two asterisks) that appeared in either the prime or the opposite location. Participants had to discriminate probe identity (one or two asterisks). Math anxious individuals reacted faster when the probe was at the location of the numerical related stimuli. This suggests the existence of attentional bias in MA. That is, for math anxious individuals, the cognitive system selectively favored the processing of emotionally negative information (i.e., math related words). These findings suggest that attentional bias is linked to unduly intense MA symptoms.
Vreeswijk, Jacob Dirk; Thomas, Tom; van Berkum, Eric C.; van Arem, Bart
Travel time is probably one of the most studied attributes in route choice. Recently, perception of travel time received more attention as several studies have shown its importance in explaining route choice behavior. In particular, travel time estimates by travelers appear to be biased against
Allen, Brenda J; Garg, Kavita
To meet challenges related to changing demographics, and to optimize the promise of diversity, radiologists must bridge the gap between numbers of women and historically underrepresented minorities in radiology and radiation oncology as contrasted with other medical specialties. Research reveals multiple ways that women and underrepresented minorities can benefit radiology education, research, and practice. To achieve those benefits, promising practices promote developing and implementing strategies that support diversity as an institutional priority and cultivate shared responsibility among all members to create inclusive learning and workplace environments. Strategies also include providing professional development to empower and equip members to accomplish diversity-related goals. Among topics for professional development about diversity, unconscious bias has shown positive results. Unconscious bias refers to ways humans unknowingly draw upon assumptions about individuals and groups to make decisions about them. Researchers have documented unconscious bias in a variety of contexts and professions, including health care, in which they have studied differential treatment, diagnosis, prescribed care, patient well-being and compliance, physician-patient interactions, clinical decision making, and medical school education. These studies demonstrate unfavorable impacts on members of underrepresented groups and women. Learning about and striving to counteract unconscious bias points to promising practices for increasing the numbers of women and underrepresented minorities in the radiology and radiation oncology workforce. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.
Full Text Available Současné trendy ve světě i v EU vykazují zvyšující se počet skupin, vzdělávajících se prostřednictvím e-learningu, tzv. e-learningových komunit. Tento příspěvek představuje první takovouto e-learningovou komunitu ve Slovinsku, a to v oblasti pedagogické praxe studentů – "Sportfolio.si".Pedagogové, studenti sportu, profesoři a mentoři na školách v rámci e-learningové komunity spolupracují a propojují tak "teorii a praxi". V rámci e-komunity a pomocí blogů (weblogů mohou uživatelé sdílet příklady nejlepších postupů a získávat, rozvíjet a sdílet tak profesní kompetence v oblasti tělesné výchovy. Potvrzují tak myšlenku, že "vlastní vědomosti lze rozvíjet tím, že je sdílíme s ostatními".Takové jsou rovněž trendy v EU, která od pedagogů požaduje neustále přejímat nové role (kompetence a měnit či opouštět některé role dřívější. Pedagogové se tudíž musí neustále starat o vlastní osobnostní a profesní rozvoj. Pomocí tzv. celoživotního vzdělávání se pedagogové stávají nedílnou součástí "učící se společnosti" neboli společnosti vědomostní, která představuje jeden ze zásadních cílů evropské politiky v oblasti výchovy a vzdělávání, kterého má být dosaženo do roku 2010.V budoucnosti by e-learningové komunity mohly představovat účinnou oporu při celoživotním vzdělávání učitelů tělesné výchovy a podpořit rozvoj sportů všech typů a měřítek. The contemporary trends in the world and in the EU indicate an increase in the number of e-learning communities. This paper presents an example of the first learning community in Slovenia in the field of practical pedagogical training for students, the "Sportfolio.si".The Faculty, sport students, professors, and the mentors at schools cooperate within the e-learning community and in this way interconnect "theory and practice". Within the e-community and by using blogs (web
Zhang, Kaihua; Liu, Qingshan; Song, Huihui; Li, Xuelong
This paper presents a novel variational approach for simultaneous estimation of bias field and segmentation of images with intensity inhomogeneity. We model intensity of inhomogeneous objects to be Gaussian distributed with different means and variances, and then introduce a sliding window to map the original image intensity onto another domain, where the intensity distribution of each object is still Gaussian but can be better separated. The means of the Gaussian distributions in the transformed domain can be adaptively estimated by multiplying the bias field with a piecewise constant signal within the sliding window. A maximum likelihood energy functional is then defined on each local region, which combines the bias field, the membership function of the object region, and the constant approximating the true signal from its corresponding object. The energy functional is then extended to the whole image domain by the Bayesian learning approach. An efficient iterative algorithm is proposed for energy minimization, via which the image segmentation and bias field correction are simultaneously achieved. Furthermore, the smoothness of the obtained optimal bias field is ensured by the normalized convolutions without extra cost. Experiments on real images demonstrated the superiority of the proposed algorithm to other state-of-the-art representative methods.
Pergamin-Hight, Lee; Naim, Reut; Bakermans-Kranenburg, Marian J; van IJzendoorn, Marinus H; Bar-Haim, Yair
Despite the established evidence for threat-related attention bias in anxiety, the mechanisms underlying this bias remain unclear. One important unresolved question is whether disorder-congruent threats capture attention to a greater extent than do more general or disorder-incongruent threat stimuli. Evidence for attention bias specificity in anxiety would implicate involvement of previous learning and memory processes in threat-related attention bias, whereas lack of content specificity would point to perturbations in more generic attention processes. Enhanced clarity of mechanism could have clinical implications for the stimuli types used in Attention Bias Modification Treatments (ABMT). Content specificity of threat-related attention bias in anxiety and potential moderators of this effect were investigated. A systematic search identified 37 samples from 29 articles (N=866). Relevant data were extracted based on specific coding rules, and Cohen's d effect size was used to estimate bias specificity effects. The results indicate greater attention bias toward disorder-congruent relative to disorder-incongruent threat stimuli (d=0.28, pattention tasks, or type of disorder-incongruent stimuli. No evidence of publication bias was observed. Implications for threat bias in anxiety and ABMT are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.
Bergen, K.; Beroza, G. C.
In recent years, advances in machine learning have transformed fields such as image recognition, natural language processing and recommender systems. Many of these performance gains have relied on the availability of large, labeled data sets to train high-accuracy models; labeled data sets are those for which each sample includes a target class label, such as waveforms tagged as either earthquakes or noise. Earthquake seismologists are increasingly leveraging machine learning and data mining techniques to detect and analyze weak earthquake signals in large seismic data sets. One of the challenges in applying machine learning to seismic data sets is the limited labeled data problem; learning algorithms need to be given examples of earthquake waveforms, but the number of known events, taken from earthquake catalogs, may be insufficient to build an accurate detector. Furthermore, earthquake catalogs are known to be incomplete, resulting in training data that may be biased towards larger events and contain inaccurate labels. This challenge is compounded by the class imbalance problem; the events of interest, earthquakes, are infrequent relative to noise in continuous data sets, and many learning algorithms perform poorly on rare classes. In this work, we investigate the use of active learning for automatic earthquake detection. Active learning is a type of semi-supervised machine learning that uses a human-in-the-loop approach to strategically supplement a small initial training set. The learning algorithm incorporates domain expertise through interaction between a human expert and the algorithm, with the algorithm actively posing queries to the user to improve detection performance. We demonstrate the potential of active machine learning to improve earthquake detection performance with limited available training data.
Caixinha, Miguel; Nunes, Sandrina
This review presents and discusses the contribution of machine learning techniques for diagnosis and disease monitoring in the context of clinical vision science. Many ocular diseases leading to blindness can be halted or delayed when detected and treated at its earliest stages. With the recent developments in diagnostic devices, imaging and genomics, new sources of data for early disease detection and patients' management are now available. Machine learning techniques emerged in the biomedical sciences as clinical decision-support techniques to improve sensitivity and specificity of disease detection and monitoring, increasing objectively the clinical decision-making process. This manuscript presents a review in multimodal ocular disease diagnosis and monitoring based on machine learning approaches. In the first section, the technical issues related to the different machine learning approaches will be present. Machine learning techniques are used to automatically recognize complex patterns in a given dataset. These techniques allows creating homogeneous groups (unsupervised learning), or creating a classifier predicting group membership of new cases (supervised learning), when a group label is available for each case. To ensure a good performance of the machine learning techniques in a given dataset, all possible sources of bias should be removed or minimized. For that, the representativeness of the input dataset for the true population should be confirmed, the noise should be removed, the missing data should be treated and the data dimensionally (i.e., the number of parameters/features and the number of cases in the dataset) should be adjusted. The application of machine learning techniques in ocular disease diagnosis and monitoring will be presented and discussed in the second section of this manuscript. To show the clinical benefits of machine learning in clinical vision sciences, several examples will be presented in glaucoma, age-related macular degeneration
Andre; C. R. Martins
Full Text Available In this article, I will show how several observed biases in human probabilistic reasoning can be partially explained as good heuristics for making inferences in an environment where probabilities have uncertainties associated to them. Previous results show that the weight functions and the observed violations of coalescing and stochastic dominance can be understood from a Bayesian point of view. We will review those results and see that Bayesian methods should also be used as part of the explanation behind other known biases. That means that, although the observed errors are still errors under the be understood as adaptations to the solution of real life problems. Heuristics that allow fast evaluations and mimic a Bayesian inference would be an evolutionary advantage, since they would give us an efficient way of making decisions. %XX In that sense, it should be no surprise that humans reason with % probability as it has been observed.
Chowdhry, D P
This article identifies gender bias against female children and youth in India. Gender bias is based on centuries-old religious beliefs and sayings from ancient times. Discrimination is reflected in denial or ignorance of female children's educational, health, nutrition, and recreational needs. Female infanticide and selective abortion of female fetuses are other forms of discrimination. The task of eliminating or reducing gender bias will involve legal, developmental, political, and administrative measures. Public awareness needs to be created. There is a need to reorient the education and health systems and to advocate for gender equality. The government of India set the following goals for the 1990s: to protect the survival of the girl child and practice safe motherhood; to develop the girl child in general; and to protect vulnerable girl children in different circumstances and in special groups. The Health Authorities should monitor the laws carefully to assure marriage after the minimum age, ban sex determination of the fetus, and monitor the health and nutrition of pre-school girls and nursing and pregnant mothers. Mothers need to be encouraged to breast feed, and to breast feed equally between genders. Every village and slum area needs a mini health center. Maternal mortality must decline. Primary health centers and hospitals need more women's wards. Education must be universally accessible. Enrollments should be increased by educating rural tribal and slum parents, reducing distances between home and school, making curriculum more relevant to girls, creating more female teachers, and providing facilities and incentives for meeting the needs of girl students. Supplementary income could be provided to families for sending girls to school. Recreational activities must be free of gender bias. Dowry, sati, and devdasi systems should be banned.
Blasco, Andrea; Sobbrio, Francesco
This paper reviews the empirical evidence on commercial media bias (i.e., advertisers influence over media accuracy) and then introduces a simple model to summarize the main elements of the theoretical literature. The analysis provides three main policy insights for media regulators: i) Media regulators should target their monitoring efforts towards news contents upon which advertisers are likely to share similar preferences; ii) In advertising industries characterized by high correlation in ...
Turcan Ciprian Sebastian
Full Text Available The main thesis of this paper represents the importance and the effects that human behavior has over capital markets. It is important to see the link between the asset valuation and investor sentiment that motivate to pay for an asset a certain prices over/below the intrinsic value. The main behavioral aspects discussed are emotional factors such as: fear of regret, overconfidence, perseverance, loss aversion ,heuristic biases, misinformation and thinking errors, herding and their consequences.
M. Tomasello, A. Kruger, and H. Ratner (1993) proposed a theory of cultural learning comprising imitative learning, instructed learning, and collaborative learning. Empirical and theoretical advances in the past 20 years suggest modifications to the theory; for example, children do not just imitate but overimitate in order to identify and…
I have developed two highly efficient codes to automate analyses of emission line nebulae. The tools place particular emphasis on the propagation of uncertainties. The first tool, ALFA, uses a genetic algorithm to rapidly optimise the parameters of gaussian fits to line profiles. It can fit emission line spectra of arbitrary resolution, wavelength range and depth, with no user input at all. It is well suited to highly multiplexed spectroscopy such as that now being carried out with instruments such as MUSE at the VLT. The second tool, NEAT, carries out a full analysis of emission line fluxes, robustly propagating uncertainties using a Monte Carlo technique.Using these tools, I have found that considerable biases can be introduced into abundance determinations if the uncertainty distribution of emission lines is not well characterised. For weak lines, normally distributed uncertainties are generally assumed, though it is incorrect to do so, and significant biases can result. I discuss observational evidence of these biases. The two new codes contain routines to correctly characterise the probability distributions, giving more reliable results in analyses of emission line nebulae.
Cen, Renyue; Ostriker, Jeremiah P.
We have supplemented our code, which computes the evolution of the physical state of a representative piece of the universe to include, not only the dynamics of dark matter (with a standard PM code), and the hydrodynamics of the gaseous component (including detailed collisional and radiative processes), but also galaxy formation on a heuristic but plausible basis. If, within a cell the gas is Jeans' unstable, collapsing, and cooling rapidly, it is transformed to galaxy subunits, which are then followed with a collisionless code. After grouping them into galaxies, we estimate the relative distributions of galaxies and dark matter and the relative velocities of galaxies and dark matter. In a large scale CDM run of 80/h Mpc size with 8 x 10 exp 6 cells and dark matter particles, we find that physical bias b is on the 8/h Mpc scale is about 1.6 and increases towards smaller scales, and that velocity bias is about 0.8 on the same scale. The comparable HDM simulation is highly biased with b = 2.7 on the 8/h Mpc scale. Implications of these results are discussed in the light of the COBE observations which provide an accurate normalization for the initial power spectrum. CDM can be ruled out on the basis of too large a predicted small scale velocity dispersion at greater than 95 percent confidence level.
Armen E Allahverdyan
Full Text Available Confirmation bias is the tendency to acquire or evaluate new information in a way that is consistent with one's preexisting beliefs. It is omnipresent in psychology, economics, and even scientific practices. Prior theoretical research of this phenomenon has mainly focused on its economic implications possibly missing its potential connections with broader notions of cognitive science.We formulate a (non-Bayesian model for revising subjective probabilistic opinion of a confirmationally-biased agent in the light of a persuasive opinion. The revision rule ensures that the agent does not react to persuasion that is either far from his current opinion or coincides with it. We demonstrate that the model accounts for the basic phenomenology of the social judgment theory, and allows to study various phenomena such as cognitive dissonance and boomerang effect. The model also displays the order of presentation effect-when consecutively exposed to two opinions, the preference is given to the last opinion (recency or the first opinion (primacy -and relates recency to confirmation bias. Finally, we study the model in the case of repeated persuasion and analyze its convergence properties.The standard Bayesian approach to probabilistic opinion revision is inadequate for describing the observed phenomenology of persuasion process. The simple non-Bayesian model proposed here does agree with this phenomenology and is capable of reproducing a spectrum of effects observed in psychology: primacy-recency phenomenon, boomerang effect and cognitive dissonance. We point out several limitations of the model that should motivate its future development.
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We will see that to develop and update preventive and therapeutic interventions, a critical, unbiased approach is essential to deliver professional veterinary support to patients and owners coherent with the rapidly-evolving state of art.
Full Text Available The empirical research investigates the orientation and learning processes of adolescents concerning global issues in different educational settings. How do adolescents create their knowledge about the world? What worldviews and ideas do adolescents have about global perspectives? How do they deal with the complexity of world society? The qualitative-empirical research focuses on the comparative analysis of learning processes in different educational settings, such as school lessons in different subjects, school-based extra-curricular activities and non-formal youth work outside school. The main topic of the paper is a case study of a group of female students who run World Shop as student company. The objective is to describe a specific learning culture at a gymnasium, a German grammar school, and the learning processes which occur within a certain learning arrangement. In this context, the student company is important both as an extra-curricular project and because issues which occur in its work setting are integrated into different school lessons. The integration of Global Education in school culture results from the presence of the student company in everyday life at school and the combination of informal learning processes within the peer milieu and formal systematic instruction in school lessons. The research reveals the great potential for the desired acquisition of competencies and knowledge. This in turn demonstrates the extent that student learning is encouraged by a particular school and learning culture. A investigação empirica investiga a orientação e o processo de aprendizagem de adolescentes referente a questões globais em diferentes contextos educacionais. Como adolescentes criam seu conhecimento do mundo? Quais as visões de mundo e as ideias que os adolescentes tem a partir da perspectiva global? Como lidam com a complexidade da sociedade mundial? A pesquisa qualitativa-empirica foca na análise comparativa dos processos em
Full Text Available Children receive more care and resources from their maternal grandmothers than from their paternal grandmothers. This asymmetry is the “matrilateral bias” in grandmaternal investment. Here, we synopsize the evolutionary theories that predict such a bias, and review evidence of its cross-cultural generality and magnitude. Evolutionists have long maintained that investing in a daughter’s child yields greater fitness returns, on average, than investing in a son’s child because of paternity uncertainty: the son’s putative progeny may have been sired by someone else. Recent theoretical work has identified an additional natural selective basis for the matrilateral bias that may be no less important: supporting grandchildren lightens the load on their mother, increasing her capacity to pursue her fitness in other ways, and if she invests those gains either in her natal relatives or in children of a former or future partner, fitness returns accrue to the maternal, but not the paternal, grandmother. In modern democracies, where kinship is reckoned bilaterally and no postmarital residence norms restrict grandmaternal access to grandchildren, many studies have found large matrilateral biases in contact, childcare, and emotional closeness. In other societies, patrilineal ideology and postmarital residence with the husband’s kin (virilocality might be expected to have produced a patrilateral bias instead, but the available evidence refutes this hypothesis. In hunter-gatherers, regardless of professed norms concerning kinship and residence, mothers get needed help at and after childbirth from their mothers, not their mothers-in-law. In traditional agricultural and pastoral societies, patrilineal and virilocal norms are common, but young mothers still turn to their natal families for crucial help, and several studies have documented benefits, including reduced child mortality, associated with access to maternal, but not paternal, grandmothers. Even
Kwan, Johnny S. H.; Kung, Annie W. C.; Sham, Pak C.
Selective genotyping can increase power in quantitative trait association. One example of selective genotyping is two-tail extreme selection, but simple linear regression analysis gives a biased genetic effect estimate. Here, we present a simple correction for the bias. © The Author(s) 2011.
Engsted, Tom; Pedersen, Thomas Quistgaard
We analyze the properties of various methods for bias-correcting parameter estimates in both stationary and non-stationary vector autoregressive models. First, we show that two analytical bias formulas from the existing literature are in fact identical. Next, based on a detailed simulation study......, we show that when the model is stationary this simple bias formula compares very favorably to bootstrap bias-correction, both in terms of bias and mean squared error. In non-stationary models, the analytical bias formula performs noticeably worse than bootstrapping. Both methods yield a notable...... improvement over ordinary least squares. We pay special attention to the risk of pushing an otherwise stationary model into the non-stationary region of the parameter space when correcting for bias. Finally, we consider a recently proposed reduced-bias weighted least squares estimator, and we find...
This article advocates biased spinners as an engaging context for statistics students. Calculating the probability of a biased spinner landing on a particular side makes valuable connections between probability and other areas of mathematics. (Contains 2 figures and 1 table.)
Short Communication: Gender Bias and Stigmatization against Women Living with ... In Ethiopia, HIV/AIDS is highly stigmatized due to the fact that sexual ... bias, socio-economic situations and traditional beliefs contribute, individually and in ...
Nature has recently published a Correspondence claiming the absence of fame biases in the editorial choice. The topic is interesting and deserves a deeper analysis than it was presented because the reported brief analysis and its conclusion are somewhat biased for many reasons, some of them are discussed here. Since the editorial assessment is a form of peer-review, the biases reported on external peer-reviews would, thus, apply to the editorial assessment, too. The biases would be proportion...
Keefe, G. E.
Magnetoresistive Perm-alloy sensor monitors bias field required to maintain bubble memory. Sensor provides error signal that, in turn, corrects magnitude of bias field. Error signal from sensor can be used to control magnitude of bias field in either auxiliary set of bias-field coils around permanent magnet field, or current in small coils used to remagnetize permanent magnet by infrequent, short, high-current pulse or short sequence of pulses.
The author argues that the college textbook market provides a clear example of monopoly seeking as described by Tullock (1967, 1980). This behavior is also known as rent seeking. Because this market is important to students, this example of rent seeking will be of particular interest to them. (Contains 24 notes.)
Olkkonen, Maria; McCarthy, Patrice F; Allred, Sarah R
Perceptual estimates can be biased by previously seen stimuli in delayed estimation tasks. These biases are often toward the mean of the whole stimulus set. Recently, we demonstrated such a central tendency bias in delayed color estimation. In the Bayesian framework of perceptual inference, perceptual biases arise when noisy sensory measurements are combined with prior information about the world. Here, we investigate this idea in color perception by manipulating stimulus range and stimulus noise while characterizing delayed color estimates. First, we manipulated the experimental prior for stimulus color by embedding stimuli in collections with different hue ranges. Stimulus range affected hue bias: Hue estimates were always biased toward the mean of the current set. Next, we studied the effect of internal and external noise on the amount of hue bias. Internal noise was manipulated by increasing the delay between the reference and test from 0.4 to 4 s. External noise was manipulated by increasing the amount of chromatic noise in the reference stimulus, while keeping the delay between the reference and test constant at 2 s. Both noise manipulations had a reliable effect on the strength of the central tendency bias. Furthermore, there was a tendency for a positive relationship between variability of the estimates and bias in both noise conditions. In conclusion, observers are able to learn an experimental hue prior, and the weight on the prior can be manipulated by introducing noise in the estimation process. © 2014 ARVO.
W. Vanhouche (Wouter); S.M.J. van Osselaer (Stijn)
textabstractExtrinsic cues such as price and irrelevant attributes have been shown to bias consumers’ product judgments. Results in this article replicate those findings in pretrial judgments but show that such biasing cues can improve quality judgments at a later point in time. Initially biasing
Moreira, Humberto Ataíde; Costa, Cristiano Machado; Ferreira, Daniel Bernardo Soares
Rio de Janeiro We model the tradeoff between the balance and the strength of incentives implicit in the choice between hierarchical and matrix organizational structures. We show that managerial biases determine which structure is optimal: hierarchical forms are preferred when biases are low, while matrix structures are preferred when biases are high.
Merino, Yesenia; Adams, Leslie; Hall, William J
This Open Forum explores the role of implicit bias along the mental health care continuum, which may contribute to mental health disparities among vulnerable populations. Emerging research shows that implicit bias is prevalent among service providers. These negative or stigmatizing attitudes toward population groups are held at a subconscious level and are automatically activated during practitioner-client encounters. The authors provide examples of how implicit bias may impede access to care, clinical screening and diagnosis, treatment processes, and crisis response. They also discuss how implicit attitudes may manifest at the intersection between mental health and criminal justice institutions. Finally, they discuss the need for more research on the impact of implicit bias on health practices throughout the mental health system, including the development of interventions to address implicit bias among mental health professionals.
Rindorf, Anna; Lewy, Peter
This study presents an analysis of the bias introduced by using simplified methods to calculate food intake of fish from stomach contents. Three sources of bias were considered: (1) the effect of estimating consumption based on a limited number of stomach samples, (2) the effect of using average......, a serious positive bias was introduced by estimating food intake from the contents of pooled stomach samples. An expression is given that can be used to correct analytically for this bias. A new method, which takes into account the distribution and evacuation of individual prey types as well as the effect...... of other food in the stomach on evacuation, is suggested for estimating the intake of separate prey types. Simplifying the estimation by ignoring these factors biased estimates of consumption of individual prey types by up to 150% in a data example....
Keenan, Michael R.
Bias plays an important role in factor analysis and is often implicitly made use of, for example, to constrain solutions to factors that conform to physical reality. However, when components are collinear, a large range of solutions may exist that satisfy the basic constraints and fit the data equally well. In such cases, the introduction of mathematical bias through the application of constraints may select solutions that are less than optimal. The biased alternating least squares algorithm of the present invention can offset mathematical bias introduced by constraints in the standard alternating least squares analysis to achieve factor solutions that are most consistent with physical reality. In addition, these methods can be used to explicitly exploit bias to provide alternative views and provide additional insights into spectral data sets.
Full Text Available Introduction Spontaneous speech samples in individuals with aphasia (IWA have been analyzed to examine many different psycholinguistic features. The present study focused on how IWA use verbs in spontaneous speech. Some verbs can occur in more than one argument structure, but are biased to occur more frequently in one frame than another. For example, "watch" appears in transitive and intransitive structures, but is usually used transitively. This is known as a transitivity bias. It is unknown whether IWA show the same transitivity biases in production as those reported in previous corpus studies with unimpaired individuals. Studies of sentence comprehension have shown that IWA are sensitive to verb biases (e.g., DeDe, 2013. In addition, IWA have shown an overall preference for transitive structures, which are the most frequent structures in English (Roland, Dick, & Elman, 2007. The present study investigated whether IWA show the same pattern of transitive and intransitive biases in spontaneous speech as unimpaired individuals. Method Participants: 278 interviews with IWA were taken from AphasiaBank. The IWA represented a range of aphasia types. Participants were omitted if they spoke English as a second language. Materials: 54 verbs were coded. We chose verbs with the goal of representing different bias types (e.g., transitive, intransitive, sentential complement. Of these, data from 11 transitively biased and 11 intransitively biased verbs (matched for frequency of use and number of syllables are presented here. Coding: All productions of the 54 verbs were coded. The coding protocol was based on Gahl, Jurafsky, and Roland (2004. We implemented an additional level of coding to indicate erroneous verb productions, such as ungrammatical structures and verb agreement errors. Results The (intransitivity biases for IWA were compared to biases from a previously published corpus study (Gahl et al., 2004. The IWA used transitively biased verbs in
Tuckett, David K.; Bartlett, Stephen D.; Flammia, Steven T.
We show that a simple modification of the surface code can exhibit an enormous gain in the error correction threshold for a noise model in which Pauli Z errors occur more frequently than X or Y errors. Such biased noise, where dephasing dominates, is ubiquitous in many quantum architectures. In the limit of pure dephasing noise we find a threshold of 43.7(1)% using a tensor network decoder proposed by Bravyi, Suchara, and Vargo. The threshold remains surprisingly large in the regime of realistic noise bias ratios, for example 28.2(2)% at a bias of 10. The performance is, in fact, at or near the hashing bound for all values of the bias. The modified surface code still uses only weight-4 stabilizers on a square lattice, but merely requires measuring products of Y instead of Z around the faces, as this doubles the number of useful syndrome bits associated with the dominant Z errors. Our results demonstrate that large efficiency gains can be found by appropriately tailoring codes and decoders to realistic noise models, even under the locality constraints of topological codes.
Verdery, Ashton M; Mouw, Ted; Bauldry, Shawn; Mucha, Peter J
This paper explores bias in the estimation of sampling variance in Respondent Driven Sampling (RDS). Prior methodological work on RDS has focused on its problematic assumptions and the biases and inefficiencies of its estimators of the population mean. Nonetheless, researchers have given only slight attention to the topic of estimating sampling variance in RDS, despite the importance of variance estimation for the construction of confidence intervals and hypothesis tests. In this paper, we show that the estimators of RDS sampling variance rely on a critical assumption that the network is First Order Markov (FOM) with respect to the dependent variable of interest. We demonstrate, through intuitive examples, mathematical generalizations, and computational experiments that current RDS variance estimators will always underestimate the population sampling variance of RDS in empirical networks that do not conform to the FOM assumption. Analysis of 215 observed university and school networks from Facebook and Add Health indicates that the FOM assumption is violated in every empirical network we analyze, and that these violations lead to substantially biased RDS estimators of sampling variance. We propose and test two alternative variance estimators that show some promise for reducing biases, but which also illustrate the limits of estimating sampling variance with only partial information on the underlying population social network.
Gulley, Lauren D; Oppenheimer, Caroline W; Hankin, Benjamin L
Theories of affective learning suggest that early experiences contribute to emotional disorders by influencing the development of processing biases for negative emotional stimuli. Although studies have shown that physically abused children preferentially attend to angry faces, it is unclear whether youth exposed to more typical aspects of negative parenting exhibit the same type of bias. The current studies extend previous research by linking observed negative parenting styles (e.g., authoritarian) and behaviors (e.g., criticism and negative affect) to attention bias for angry faces in both a psychiatrically enriched (ages 11-17 years; N = 60) and a general community (ages 9-15 years; N = 75) sample of youth. In addition, the association between observed negative parenting (e.g., authoritarian style and negative affect) and youth social anxiety was mediated by attention bias for angry faces in the general community sample. Overall, findings provide preliminary support for theories of affective learning and risk for psychopathology among youth.
Lai, Patrick; Biggs, John
Data from 95 educationally disadvantaged Hong Kong students placed in mastery-learning classes were compared with 64 control students in expository-learning classes. Results indicate that under mastery learning, deep- and surface-biased learners increasingly diverge in performance and attitude, with surface learners doing better unit to unit, and…
Heinerman, J.V.; Stork, J.; Rebolledo Coy, M.A.; Hubert, J.G.; Eiben, A.E.; Bartz-Beielstein, Thomas; Haasdijk, Evert
Social learning enables multiple robots to share learned experiences while completing a task. The literature offers contradicting examples of its benefits; robots trained with social learning reach a higher performance, an increased learning speed, or both, compared to their individual learning
Higham, Philip A; Neil, Greg J; Bernstein, Daniel M
We report 4 experiments investigating auditory hindsight bias-the tendency to overestimate the intelligibility of distorted auditory stimuli after learning their identity. An associative priming manipulation was used to vary the amount of processing fluency independently of prior target knowledge. For hypothetical designs, in which hindsight judgments are made for peers in foresight, we predicted that judgments would be based on processing fluency and that hindsight bias would be greater in the unrelated- compared to related-prime context (differential-fluency hypothesis). Conversely, for memory designs, in which foresight judgments are remembered in hindsight, we predicted that judgments would be based on memory reconstruction and that there would be independent effects of prime relatedness and prior target knowledge (recollection hypothesis). These predictions were confirmed. Specifically, we found support for the differential-fluency hypothesis when a hypothetical design was used in Experiments 1 and 2 (hypothetical group). Conversely, when a memory design was used in Experiments 2 (memory group), 3A, and 3B, we found support for the recollection hypothesis. Together, the results suggest that qualitatively different mechanisms create hindsight bias in the 2 designs. The results are discussed in terms of fluency misattributions, memory reconstruction, anchoring-and-adjustment, sense making, and a multicomponent model of hindsight bias. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
Full Text Available This paper overviews the theoretical and empirical research on behavioral biases and their influence in the literature. To provide a systematic exposition, we present a unified framework that takes the reader through an original taxonomy, based on the reviews of relevant authors in the field. In particular, we establish three broad categories that may be distinguished: heuristics and biases; choices, values and frames; and social factors. We then describe the main biases within each category, and revise the main theoretical and empirical developments, linking each bias with other biases and anomalies that are related to them, according to the literature.
Jesús Miranda Izquierdo
Full Text Available Thi is article analyzes the potentialities and weaknesses that non directive Pedagogy presents, an example of the so called self managed pedagogy, whose postulates are good to analyze for the contributions that this position can make to the search of new ways of learning.
Several examples of extended asymptotic functions of two variables are given. This type of asymptotic functions has been introduced as an extension of continuous ordinary functions. The presented examples are realizations of some Schwartz distributions delta(x), THETA(x), P(1/xsup(n)) and can be multiplied in the class of the asymptotic functions as opposed to the theory of Schwartz distributions. The examples illustrate the method of construction of extended asymptotic functions similar to the distributions. The set formed by the extended asymptotic functions is also considered. It is shown, that this set is not closed with respect to addition and multiplication
Meier, Debra K.; Reinhard, Karl J.; Carter, David O.; Brooks, David W.
Worked examples have been effective in enhancing learning outcomes, especially with novice learners. Most of this research has been conducted in laboratory settings. This study examined the impact of embedding elaborated worked example modeling in a computer simulation practice activity on learning achievement among 39 undergraduate students…
Full Text Available Gender biases persist in forestry research and practice. These biases result in reduced scientific rigor and inequitable, ineffective, and less efficient policies, programs, and interventions. Drawing from a two-volume collection of current and classic analyses on gender in forests, we outline five persistent and inter-related themes: gendered governance, tree tenure, forest spaces, division of labor, and ecological knowledge. Each emerges across geographic regions in the northern and southern hemisphere and reflects inequities in women’s and men’s ability to make decisions about and benefit from trees, forests, and their products. Women’s ability to participate in community-based forest governance is typically less than men’s, causing concern for social equity and forest stewardship. Women’s access to trees and their products is commonly more limited than men’s, and mediated by their relationship with their male counterparts. Spatial patterns of forest use reflect gender norms and taboos, and men’s greater access to transportation. The division of labor results in gender specialization in the collection of forest products, with variations in gender roles across regions. All these gender differences result in ecological knowledge that is distinct but also complementary and shifting across the genders. The ways gender plays out in relation to each theme may vary across cultures and contexts, but the influence of gender, which intersects with other factors of social differentiation in shaping forest landscapes, is global.
Malinen, Sanna; Johnston, Lucy
BACKGROUND/STUDY CONTEXT: Research largely shows no performance differences between older and younger employees, or that older workers even outperform younger employees, yet negative attitudes towards older workers can underpin discrimination. Unfortunately, traditional "explicit" techniques for assessing attitudes (i.e., self-report measures) have serious drawbacks. Therefore, using an approach that is novel to organizational contexts, the authors supplemented explicit with implicit (indirect) measures of attitudes towards older workers, and examined the malleability of both. This research consists of two studies. The authors measured self-report (explicit) attitudes towards older and younger workers with a survey, and implicit attitudes with a reaction-time-based measure of implicit associations. In addition, to test whether attitudes were malleable, the authors measured attitudes before and after a mental imagery intervention, where the authors asked participants in the experimental group to imagine respected and valued older workers from their surroundings. Negative, stable implicit attitudes towards older workers emerged in two studies. Conversely, explicit attitudes showed no age bias and were more susceptible to change intervention, such that attitudes became more positive towards older workers following the experimental manipulation. This research demonstrates the unconscious nature of bias against older workers, and highlights the utility of implicit attitude measures in the context of the workplace. In the current era of aging workforce and skill shortages, implicit measures may be necessary to illuminate hidden workplace ageism.
Anderson, D.R.; Pospahala, R.S.
Unless a correction is made, population estimates derived from a sample of belt transects will be biased if a fraction of, the individuals on the sample transects are not counted. An approach, useful for correcting this bias when sampling immotile populations using transects of a fixed width, is presented. The method assumes that a searcher's ability to find objects near the center of the transect is nearly perfect. The method utilizes a mathematical equation, estimated from the data, to represent the searcher's inability to find all objects at increasing distances from the center of the transect. An example of the analysis of data, formation of the equation, and application is presented using waterfowl nesting data collected in Colorado.
Losert, Harald; Vogel, Karl; Schleich, Wolfgang P. [Institut fuer Quantenphysik and Center for Integrated Quantum Science and Technology (IQST), Universitaet Ulm, D-89069 Ulm (Germany)
Josephson junctions are one of the best examples for the observation of macroscopic quantum tunneling. The phase difference in a current-biased Josephson junction behaves like the position of a particle in a tilted washboard potential. The escape of this phase-particle corresponds to the voltage switching of the associated junction. Quantum mechanically, the escape from the washboard potential can be explained as tunneling from the ground state, or an excited state. However, it has been shown, that in the case of periodic driving the experimental data for quantum mechanical key features, e.g. Rabi oscillations or energy level quantization, can be reproduced by a completely classical description. Motivated by this discussion, we investigate a swept-bias Josephson junction in the case of a large critical current. In particular, we contrast the switching current distributions resulting from a quantum mechanical and classical description of the time evolution.