Text feature extraction based on deep learning: a review.

Science.gov (United States)

Liang, Hong; Sun, Xiao; Sun, Yunlei; Gao, Yuan

2017-01-01

Selection of text feature item is a basic and important matter for text mining and information retrieval. Traditional methods of feature extraction require handcrafted features. To hand-design, an effective feature is a lengthy process, but aiming at new applications, deep learning enables to acquire new effective feature representation from training data. As a new feature extraction method, deep learning has made achievements in text mining. The major difference between deep learning and conventional methods is that deep learning automatically learns features from big data, instead of adopting handcrafted features, which mainly depends on priori knowledge of designers and is highly impossible to take the advantage of big data. Deep learning can automatically learn feature representation from big data, including millions of parameters. This thesis outlines the common methods used in text feature extraction first, and then expands frequently used deep learning methods in text feature extraction and its applications, and forecasts the application of deep learning in feature extraction.

Summarize to learn: summarization and visualization of text for ubiquitous learning

DEFF Research Database (Denmark)

Chongtay, Rocio; Last, Mark; Verbeke, Mathias

2013-01-01

Visualizations can stand in many relations to texts – and, as research into learning with pictures has shown, they can become particularly valuable when they transform the contents of the text (rather than just duplicate its message or structure it). But what kinds of transformations can...... be particularly helpful in the learning process? In this paper, we argue that interacting with, and creating, summaries of texts is a key transformation technique, and we investigate how textual and graphical summarization approaches, as well as automatic and manual summarization, can complement one another...... to support effective learning....

Learning second language vocabulary: neural dissociation of situation-based learning and text-based learning.

Science.gov (United States)

Jeong, Hyeonjeong; Sugiura, Motoaki; Sassa, Yuko; Wakusawa, Keisuke; Horie, Kaoru; Sato, Shigeru; Kawashima, Ryuta

2010-04-01

Second language (L2) acquisition necessitates learning and retrieving new words in different modes. In this study, we attempted to investigate the cortical representation of an L2 vocabulary acquired in different learning modes and in cross-modal transfer between learning and retrieval. Healthy participants learned new L2 words either by written translations (text-based learning) or in real-life situations (situation-based learning). Brain activity was then measured during subsequent retrieval of these words. The right supramarginal gyrus and left middle frontal gyrus were involved in situation-based learning and text-based learning, respectively, whereas the left inferior frontal gyrus was activated when learners used L2 knowledge in a mode different from the learning mode. Our findings indicate that the brain regions that mediate L2 memory differ according to how L2 words are learned and used. Copyright 2009 Elsevier Inc. All rights reserved.

Lifelong Learning: Policies, Practices, and Programs.

Science.gov (United States)

Hatton, Michael J., Ed.

The 26 articles in this book focus on lifelong learning policies, practices, and programs in 13 Asia Pacific countries. The following papers are included: "Half a Revolution: A Brief Survey of Lifelong Learning in New Zealand" (P. Methven and J. Hansen); "HRD in a Multicultural Workplace: The Need for Lifelong Learning" (M.…

Can Music Foster Learning - Effects of Different Text Modalities on Learning and Information Retrieval.

Science.gov (United States)

Lehmann, Janina A M; Seufert, Tina

2017-01-01

This study investigates the possibilities of fostering learning based on differences in recall and comprehension after learning with texts which were presented in one of three modalities: either in a spoken, written, or sung version. All three texts differ regarding their processing, especially when considering working memory. Overall, we assume the best recall performance after learning with the written text and the best comprehension performance after learning with the sung text, respectively, compared to both other text modalities. We also analyzed whether the melody of the sung material functions as a mnemonic aid for the learners in the sung text condition. If melody and text of the sung version are closely linked, presentation of the melody during the post-test phase could foster text retrieval. 108 students either learned from a sung text performed by a professional singer, a printed text, or the same text read out loud. Half of the participants worked on the post-test while listening to the melody used for the musical learning material and the other half did not listen to a melody. The written learning modality led to significantly better recall than with the spoken ( d = 0.97) or sung text ( d = 0.78). However, comprehension after learning with the sung modality was significantly superior compared to when learning with the written learning modality ( d = 0.40). Reading leads to more focus on details, which is required to answer recall questions, while listening fosters a general understanding of the text, leading to higher levels of comprehension. Listening to the melody during the post-test phase negatively affected comprehension, irrespective of the modality during the learning phase. This can be explained by the seductive detail effect, as listening to the melody during the post-test phase may distract learners from their main task. In closing, theoretical and practical implications are discussed.

Policy Review on Adult Learning: The Adult Non-Formal Education Policy of Mali, West Africa

Science.gov (United States)

Gadio, Moussa

2011-01-01

This article focuses on the issue of policy development for adult learning in Mali, West Africa. On January 2007, the Malian government adopted the "Adult Non-formal Education Policy Document," which was intended to regulate the adult learning sector and federate the actions of policy makers, adult education providers, and adult…

Active Learning for Text Classification

OpenAIRE

Hu, Rong

2011-01-01

Text classification approaches are used extensively to solve real-world challenges. The success or failure of text classification systems hangs on the datasets used to train them, without a good dataset it is impossible to build a quality system. This thesis examines the applicability of active learning in text classification for the rapid and economical creation of labelled training data. Four main contributions are made in this thesis. First, we present two novel selection strategies to cho...

An Imagination Effect in Learning from Scientific Text

Science.gov (United States)

Leopold, Claudia; Mayer, Richard E.

2015-01-01

Asking students to imagine the spatial arrangement of the elements in a scientific text constitutes a learning strategy intended to foster deep processing of the instructional material. Two experiments investigated the effects of mental imagery prompts on learning from scientific text. Students read a computer-based text on the human respiratory…

Stochastic abstract policies: generalizing knowledge to improve reinforcement learning.

Science.gov (United States)

Koga, Marcelo L; Freire, Valdinei; Costa, Anna H R

2015-01-01

Reinforcement learning (RL) enables an agent to learn behavior by acquiring experience through trial-and-error interactions with a dynamic environment. However, knowledge is usually built from scratch and learning to behave may take a long time. Here, we improve the learning performance by leveraging prior knowledge; that is, the learner shows proper behavior from the beginning of a target task, using the knowledge from a set of known, previously solved, source tasks. In this paper, we argue that building stochastic abstract policies that generalize over past experiences is an effective way to provide such improvement and this generalization outperforms the current practice of using a library of policies. We achieve that contributing with a new algorithm, AbsProb-PI-multiple and a framework for transferring knowledge represented as a stochastic abstract policy in new RL tasks. Stochastic abstract policies offer an effective way to encode knowledge because the abstraction they provide not only generalizes solutions but also facilitates extracting the similarities among tasks. We perform experiments in a robotic navigation environment and analyze the agent's behavior throughout the learning process and also assess the transfer ratio for different amounts of source tasks. We compare our method with the transfer of a library of policies, and experiments show that the use of a generalized policy produces better results by more effectively guiding the agent when learning a target task.

Tracing policy movements: methods for studying learning and policy circulation

OpenAIRE

Wood, Astrid

2016-01-01

Policy flows are not quantifiable and calculating processes but part of the uneven movement of ideas and experiences that involves power and personalities. Processes of learning and policy circulation have thus proven difficult to study especially as the exchanges taking place between actors and localities rarely lead directly to uptake. This paper outlines a conceptual and methodological framework for conducting policy mobilities research by attending to the plethora of ordinary practices – ...

Maximising policy learning in international committees

DEFF Research Database (Denmark)

Nedergaard, Peter

In spite of their long history and extensive activities, the international committees of the Nordic Council of Ministers have not hitherto been subject to scholarly examination. This paper demonstrates that valuable lessons can be learned about policy learning in practise and theoretically...

Wind power, policy learning and paradigm change

International Nuclear Information System (INIS)

Szarka, Joseph

2006-01-01

The aim of this article is to study how policy learning has led to new understandings of ways to support renewable energies, based on experience in the wind power sector. Drawing on analysis of the literature and informed by field-work in the wind power sector in Denmark, France and the UK, it explores the extent to which policy learning over the medium term has brought us closer to models that integrate economic, environmental and societal desiderata into renewables policy in a manner congruent with the sustainable development aspirations espoused by the European Union and its constituent states. It contributes to policy theory development by arguing in favour of a new policy paradigm that reaches beyond measures to increase production capacity per se to embrace both the institutional dynamics of innovation processes and the fostering of societal engagement in implementation processes

How Different Forms of Policy Learning Influence Each Other: Case Studies from Austrian Innovation Policy-Making

OpenAIRE

Biegelbauer, Peter

2016-01-01

This paper investigates the question whether different forms of policy learning influence each other. The focus is on relationships between different forms of policy learning, which are explored on the basis of case study research in the field of research, technology and innovation policy-making in Austria. Methods utilised are expert interviews and document analysis besides literature and media recherché. With the goal to better understand the mechanisms behind learning processes, different ...

Can Music Foster Learning – Effects of Different Text Modalities on Learning and Information Retrieval

Directory of Open Access Journals (Sweden)

Janina A. M. Lehmann

2018-01-01

Full Text Available This study investigates the possibilities of fostering learning based on differences in recall and comprehension after learning with texts which were presented in one of three modalities: either in a spoken, written, or sung version. All three texts differ regarding their processing, especially when considering working memory. Overall, we assume the best recall performance after learning with the written text and the best comprehension performance after learning with the sung text, respectively, compared to both other text modalities. We also analyzed whether the melody of the sung material functions as a mnemonic aid for the learners in the sung text condition. If melody and text of the sung version are closely linked, presentation of the melody during the post-test phase could foster text retrieval. 108 students either learned from a sung text performed by a professional singer, a printed text, or the same text read out loud. Half of the participants worked on the post-test while listening to the melody used for the musical learning material and the other half did not listen to a melody. The written learning modality led to significantly better recall than with the spoken (d = 0.97 or sung text (d = 0.78. However, comprehension after learning with the sung modality was significantly superior compared to when learning with the written learning modality (d = 0.40. Reading leads to more focus on details, which is required to answer recall questions, while listening fosters a general understanding of the text, leading to higher levels of comprehension. Listening to the melody during the post-test phase negatively affected comprehension, irrespective of the modality during the learning phase. This can be explained by the seductive detail effect, as listening to the melody during the post-test phase may distract learners from their main task. In closing, theoretical and practical implications are discussed.

Can Strategies Facilitate Learning from Illustrated Science Texts?

Science.gov (United States)

Iding, Marie K.

2000-01-01

Examines the effectiveness of schema training in illustration types and text-illustration relations for learning from college level physiology texts and discusses findings that are consistent with prior research on learning from illustrated materials and with dual coding theory. Considers future directions for strategy training research and…

Researcher Creations? The Positioning of Policy Texts in Higher Education Research

Science.gov (United States)

Ashwin, Paul; Smith, Karen

2015-01-01

In this article we explore the way in which policy texts are positioned in a selection of higher education journal articles. Previous research has suggested that policy implementation studies have taken an uncritical approach to researching policies. Based on an analysis of articles published in higher education and policy journals in 2011, we…

Who makes European Cohesion Policy: a practitioners’ learning perspective

Directory of Open Access Journals (Sweden)

Fanny Sbaraglia

2016-01-01

Full Text Available Through the European Social Fund (ESF, the European Union subsidizes social inclusion and occupational trainee projects. This policy instrument is formulated by European Union institutions and implemented by regions through a call for projects which requires innovative actions and a result-oriented strategy. It is a key vantage point to observe sub-national implementation of an European Union policy instrument in a sub-national practitioner’s perspective, a topic under-investigated in the literature. For a project to receive funding, sub-national practitioners must take the European Union requirements (accounting standards, evidence of innovation etc. and their social needs into account. Against this backdrop, this research tackles an original question: how can local practitioners adapt their policy actions to fit with European Union requirements? Taking the region of Wallonia in Belgium as a case study, the ESF implementation is considered as a specific policy process in sub-national policy sectors. Adopting an in-depth qualitative perspective, this research contends that it depends on practitioners’ learning, practices and experience of past applications, their specific socio-economic context and income maximization.

Policy learning in the Eurozone crisis: modes, power and functionality.

Science.gov (United States)

Dunlop, Claire A; Radaelli, Claudio M

In response to the attacks on the sovereign debt of some Eurozone countries, European Union (EU) leaders have created a set of preventive and corrective policy instruments to coordinate macro-economic policies and reforms. In this article, we deal with the European Semester, a cycle of information exchange, monitoring and surveillance. Countries that deviate from the targets are subjected to increasing monitoring and more severe 'corrective' interventions, in a pyramid of responsive exchanges between governments and EU institutions. This is supposed to generate coordination and convergence towards balanced economies via mechanisms of learning. But who is learning what? Can the EU learn in the 'wrong' mode? We contribute to the literature on theories of the policy process by showing how modes of learning can be operationalized and used in empirical analysis. We use policy learning as theoretical framework to establish empirically the prevalent mode of learning and its implications for both the power of the Commission and the normative question of whether the EU is learning in the 'correct' mode.

Can Music Foster Learning – Effects of Different Text Modalities on Learning and Information Retrieval

OpenAIRE

Lehmann, Janina A. M.; Seufert, Tina

2018-01-01

This study investigates the possibilities of fostering learning based on differences in recall and comprehension after learning with texts which were presented in one of three modalities: either in a spoken, written, or sung version. All three texts differ regarding their processing, especially when considering working memory. Overall, we assume the best recall performance after learning with the written text and the best comprehension performance after learning with the sung text, respective...

Politics of policy learning: Evaluating an experiment on free pricing arrangements in Dutch dental care.

Science.gov (United States)

Felder, Martijn; van de Bovenkamp, Hester; de Bont, Antoinette

2018-01-01

In Dutch healthcare, new market mechanisms have been introduced on an experimental basis in an attempt to contain costs and improve quality. Informed by a constructivist approach, we demonstrate that such experiments are not neutral testing grounds. Drawing from semi-structured interviews and policy texts, we reconstruct an experiment on free pricing in dental care that turned into a critical example of market failure, influencing developments in other sectors. Our analysis, however, shows that (1) different market logics and (2) different experimental logics were reproduced simultaneously during the course of the experiment. We furthermore reveal how (3) evaluation and political life influenced which logics were reproduced and became taken as the lessons learned. We use these insights to discuss the role of evaluation in learning from policy experimentation and close with four questions that evaluators could ask to better understand what is learned from policy experiments, how , and why .

Off-Policy Reinforcement Learning for Synchronization in Multiagent Graphical Games.

Science.gov (United States)

Li, Jinna; Modares, Hamidreza; Chai, Tianyou; Lewis, Frank L; Xie, Lihua

2017-10-01

This paper develops an off-policy reinforcement learning (RL) algorithm to solve optimal synchronization of multiagent systems. This is accomplished by using the framework of graphical games. In contrast to traditional control protocols, which require complete knowledge of agent dynamics, the proposed off-policy RL algorithm is a model-free approach, in that it solves the optimal synchronization problem without knowing any knowledge of the agent dynamics. A prescribed control policy, called behavior policy, is applied to each agent to generate and collect data for learning. An off-policy Bellman equation is derived for each agent to learn the value function for the policy under evaluation, called target policy, and find an improved policy, simultaneously. Actor and critic neural networks along with least-square approach are employed to approximate target control policies and value functions using the data generated by applying prescribed behavior policies. Finally, an off-policy RL algorithm is presented that is implemented in real time and gives the approximate optimal control policy for each agent using only measured data. It is shown that the optimal distributed policies found by the proposed algorithm satisfy the global Nash equilibrium and synchronize all agents to the leader. Simulation results illustrate the effectiveness of the proposed method.

Innovating Everything: Examining Teacher Learning of Unfamiliar Texts

Science.gov (United States)

Goff, Maria Hernandez

2017-01-01

This dissertation explored how a teacher learned to teach with and about unfamiliar (to her) media texts in her high school English classroom. This study also examined my role as the researcher/mentor in the teacher's learning and development process. Through situated learning theories (Lave & Wenger, 1991) and discourse through identities…

Analysis on policies text of air pollution control in Beijing

Science.gov (United States)

ZHANG, Yujuan; WANG, Wen; ZHANG, Wei

2017-04-01

Air pollution is one of the most serious environmental problems, and it is also the inevitable result of the extensive economic development mode. The matter of air pollution in Beijing is becoming more and more serious since 2010, which has a great impact on the normal social production, living and human health. These hazards have been highly valued by the whole society. More than 30 years have been pasted since controlling the air pollution and the system of policies was relatively complete. These policies have improved the quality of atmospheric and prevented environment further deterioration. The policies performance is not obvious. It is urgent trouble to improve policy performance. This paper analyzes the 103 policies text of air pollution control in Beijing, and researches status, history and problems, and put forward suggestions on policy improvement and innovation at last.

Attendance Policies, Instructor Communication, Student Attendance, and Learning

Science.gov (United States)

Snyder, Jason; Frank, Lisa A. C.

2016-01-01

The authors utilized a quasiexperimental design across five sections of a managerial communication course (N = 150) to test the role of course policies and student perceptions of the instructor in influencing student absenteeism and three indicators of student learning: grades, affective learning, and cognitive learning. The experimental group…

Empirical Studies On Machine Learning Based Text Classification Algorithms

OpenAIRE

Shweta C. Dharmadhikari; Maya Ingle; Parag Kulkarni

2011-01-01

Automatic classification of text documents has become an important research issue now days. Properclassification of text documents requires information retrieval, machine learning and Natural languageprocessing (NLP) techniques. Our aim is to focus on important approaches to automatic textclassification based on machine learning techniques viz. supervised, unsupervised and semi supervised.In this paper we present a review of various text classification approaches under machine learningparadig...

Learning history by composing synthesis texts: Effects of an instructional programme on learning, reading and writing processes, and text quality

NARCIS (Netherlands)

Martínez, I.; Mateos, M.; Martín, E.; Rijlaarsdam, G.

2015-01-01

The aim of the present study was to improve learning from texts via strategies that train students how to process synthesis texts. Processing such texts requires goal-oriented interaction between reading and writing activities. The participants were 62 sixth-grade students, 33 in the experimental

Effects of incidental pictorial and verbal adjuncts on text learning.

Science.gov (United States)

Terry, W S; Howe, D C

1988-01-01

In this study, college students read and studied texts on historical figures in psychology, which were supplemented by drawings and/or brief biographies of these persons. In Experiment 1, a 2 x 2 between-groups design was conducted in which students received one adjunct with each text, both adjuncts, or neither. In Experiment 2, a single group of students received a within-subjects manipulation of the same adjunct conditions. In the between-groups comparison, students receiving biographies learned less of the target text passages, with the group receiving illustrations and biographies performing least accurately. In the within-subject conditions, texts accompanied by an illustration were better learned, with these students doing best on the text with both picture and biography. The results suggest that adjuncts may emphasize some texts, at the expense of learning from the other texts, but that too much adjunct material interferes with the learning of the target passages.

Early Learning and Educational Technology Policy Brief

Science.gov (United States)

Lee, Joan

2016-01-01

Recognizing the growth of technology use in early learning settings, the U.S. Department of Education and U.S. Department of Health and Human Services collaborated in the development of the "Early Learning and Educational Technology Policy Brief" to promote developmentally appropriate use of technology in homes and early learning…

Learning from Conflicting Texts: The Role of Intertextual Conflict Resolution in Between-Text Integration

Science.gov (United States)

Kobayashi, Keiichi

2015-01-01

The present study examined the effect of intertextual conflict resolution on learning from conflicting texts. In two experiments, participants read sets of two texts under the condition of being encouraged either to resolve a conflict between the texts' arguments (the resolution condition) or to comprehend the arguments (the comprehension…

Peer Review in a Social Policy Course: Lessons Learned

Directory of Open Access Journals (Sweden)

Shauna P. Acquavita

2013-04-01

Full Text Available Peer review is a tool that provides students with a sense of how their work is perceived by others. Built on refection and feedback, peer review assesses the quality of academic processes and products based on well-understood criteria. Peer review was implemented in a baccalaureate social work policy course to enhance writing and critical thinking skills. Students were surveyed on their experiences and indicated that peer review activities provided beneficial learning exercises. The information gathered suggests methods for future implementation of peer review in social work education.

Bayesian policy reuse

CSIR Research Space (South Africa)

Rosman, Benjamin

2016-02-01

Full Text Available Keywords Policy Reuse · Reinforcement Learning · Online Learning · Online Bandits · Transfer Learning · Bayesian Optimisation · Bayesian Decision Theory. 1 Introduction As robots and software agents are becoming more ubiquitous in many applications.... The agent has access to a library of policies (pi1, pi2 and pi3), and has previously experienced a set of task instances (τ1, τ2, τ3, τ4), as well as samples of the utilities of the library policies on these instances (the black dots indicate the means...

The second pillar of the CAP: the role of Commission policy learning in the creation and reform of EU rural development policy (1968-1999)

DEFF Research Database (Denmark)

Steffensen, Jonny Trapp

argument advanced in this thesis is that policy learning is a multifaceted phenomenon that can most reliably be examined employing 'method pluralism' (documentary analysis, elite interviews, and survey techniques). A second theoretical assertion is that policy learning can change the beliefs - termed......This thesis examines the concept of 'policy learning' and explores its applicability to the European Commission's role in EU policymaking. Policy learning refers to 'knowledge-based' policy formulation, where content of policy proposals is shaped to a 'non-trivial' extent by administrative...... 'policy strategy' - of political actors. A third theoretical contribution is the concept of 'bureaucratic policy learning capability' (BPLC) which refers to an organisation's ability and inclination to utilise available policy-relevant knowledge. I assess the Commission's BPLC through a survey, designed...

Text-to-audiovisual speech synthesizer for children with learning disabilities.

Science.gov (United States)

Mendi, Engin; Bayrak, Coskun

2013-01-01

Learning disabilities affect the ability of children to learn, despite their having normal intelligence. Assistive tools can highly increase functional capabilities of children with learning disorders such as writing, reading, or listening. In this article, we describe a text-to-audiovisual synthesizer that can serve as an assistive tool for such children. The system automatically converts an input text to audiovisual speech, providing synchronization of the head, eye, and lip movements of the three-dimensional face model with appropriate facial expressions and word flow of the text. The proposed system can enhance speech perception and help children having learning deficits to improve their chances of success.

Relating R and D and investment policies to CCS market diffusion through two-factor learning

International Nuclear Information System (INIS)

Lohwasser, Richard; Madlener, Reinhard

2013-01-01

Carbon capture and storage (CCS) has the potential to play a major role in the stabilization of anthropogenic greenhouse gases. To develop the capture technology from its current demonstration phase towards commercial maturity, significant funding is directed to CCS, such as the EU’s €4.5 bn NER300 fund. However, we know little about how this funding relates to market diffusion of CCS. This paper addresses that question. We initially review past learning effects from both capacity installations and R and D efforts for a similar technology using the concept of two-factor learning. We apply the obtained learning-by-doing and learning-by-searching rates to CCS in the electricity market model HECTOR, which simulates 19 European countries hourly until 2040, to understand the impact of learning and associated policies on CCS market diffusion. We evaluate the effectiveness of policies addressing learning-by-doing and learning-by-searching by relating the policy budget to the realized CCS capacity and find that, at lower policy cost, both methods are about equally effective. At higher spending levels, policies promoting learning-by-doing are more effective. Overall, policy effectiveness increases in low CO 2 price scenarios, but the CO 2 price still remains the key prerequisite for the economic competitiveness, even with major policy support. - Highlights: ► Identified two-factor learning rates for CCS through empirical data from flue gas desulphurization. ► Evaluated effectiveness of CCS stimulation policies addressing learning-by-doing and learning-by-researching. ► Both policy types are about equally effective with small policy budgets. ► Policies addressing learning-by-doing, e.g., subsidies to CCS projects, are more effective with large policy budgets. ► Analysis deployed HECTOR power market model that simulates 19 European countries on hourly granularity until 2040.

Stimulating learning-by-doing in advanced biofuels: effectiveness of alternative policies

International Nuclear Information System (INIS)

Chen Xiaoguang; Khanna, Madhu; Yeh, Sonia

2012-01-01

This letter examines the effectiveness of various biofuel and climate policies in reducing future processing costs of cellulosic biofuels due to learning-by-doing. These policies include a biofuel production mandate alone and supplementing the biofuel mandate with other policies, namely a national low carbon fuel standard, a cellulosic biofuel production tax credit or a carbon price policy. We find that the binding biofuel targets considered here can reduce the unit processing cost of cellulosic ethanol by about 30% to 70% between 2015 and 2035 depending on the assumptions about learning rates and initial costs of biofuel production. The cost in 2035 is more sensitive to the speed with which learning occurs and less sensitive to uncertainty in the initial production cost. With learning rates of 5–10%, cellulosic biofuels will still be at least 40% more expensive than liquid fossil fuels in 2035. The addition of supplementary low carbon/tax credit policies to the mandate that enhance incentives for cellulosic biofuels can achieve similar reductions in these costs several years earlier than the mandate alone; the extent of these incentives differs across policies and different kinds of cellulosic biofuels. (letter)

Lifelong Learning as Social Need and as Policy Discourse

DEFF Research Database (Denmark)

Rasmussen, Palle

2009-01-01

Lifelong learning is a key concept in EU policy documents not only on education, but also on economic competitiveness and social cohesion. The discourse on lifelong learning has been strongly criticised by educational researchers, who document that it often reflects narrow notions of learning and...

Learning How to Write an Academic Text: The Effect of Instructional Method and Reflection on Text Quality

Science.gov (United States)

van der Loo, Janneke; Krahmer, Emiel; van Amelsvoort, Marije

2016-01-01

In this paper we present preliminary results on a study on the effect of instructional method (observational learning and learning by doing) and reflection (yes or no) on academic text quality and self-efficacy beliefs. 56 undergraduate students were assigned to either an observational learning or learning-by-doing condition, with or without…

The Surveillance of Learning: A Critical Analysis of University Attendance Policies

Science.gov (United States)

Macfarlane, Bruce

2013-01-01

Universities have recently strengthened their class attendance policies along with associated practices that intensify the surveillance of learning: a series of administrative and pedagogic strategies that monitor the extent to which students conform with behavioural expectations associated with learning. Drawing on university policy statements,…

Learning from text benefits from enactment.

Science.gov (United States)

Cutica, Ilaria; Ianì, Francesco; Bucciarelli, Monica

2014-10-01

Classical studies on enactment have highlighted the beneficial effects of gestures performed in the encoding phase on memory for words and sentences, for both adults and children. In the present investigation, we focused on the role of enactment for learning from scientific texts among primary-school children. We assumed that enactment would favor the construction of a mental model of the text, and we verified the derived predictions that gestures at the time of encoding would result in greater numbers of correct recollections and discourse-based inferences at recall, as compared to no gestures (Exp. 1), and in a bias to confound paraphrases of the original text with the verbatim text in a recognition test (Exp. 2). The predictions were confirmed; hence, we argue in favor of a theoretical framework that accounts for the beneficial effects of enactment on memory for texts.

Enriching Student Learning of Astronomy in Online Courses via Hybrid Texts

Science.gov (United States)

Montgomery, M.

2016-01-01

Hybrid texts such as Horizons: Exploring the Universe, Hybrid (with CengageNOW) and Universe, Hybrid (with CengageNOW) are designed for higher education learning of astronomy in undergraduate online courses. In these hybrid texts, quiz and test bank questions have been revised to minimize easy look-up of answers by students via the Internet and discussion threads have been re-designed to allow for student selection of learning and for personalized learning, for example. By establishing connections between the student and the course content, student learning is enriched, students spend more time learning the material, student copying of answers is minimized, and student social engagement on the subject matter is increased. In this presentation, we discuss how Hybrid texts in Astronomy can increase student learning in online courses.

Community Learning and University Policy: An Inner-City University Goes Back to School

Directory of Open Access Journals (Sweden)

Lloyd Axworthy

2016-05-01

Full Text Available For at least a decade now, the University of Winnipeg (U of W, an urban institution on Treaty One land in the heart of the Métis Nation, has challenged existing academic models and practices, and has incorporated strategies that address the social divide between Indigenous and non-Indigenous peoples in order to more effectively serve the learning needs of its surrounding community. This article demonstrates how an inner-city university has used internal policies and programs to help support the self-determination of Indigenous peoples. Six community learning initiatives were recently evaluated for impact. This article will provide an overview of the positive outcomes of these learning initiatives on a community of underrepresented learners.

Learning Negotiation Policies Using IB3 and Bayesian Networks

Science.gov (United States)

Nalepa, Gislaine M.; Ávila, Bráulio C.; Enembreck, Fabrício; Scalabrin, Edson E.

This paper presents an intelligent offer policy in a negotiation environment, in which each agent involved learns the preferences of its opponent in order to improve its own performance. Each agent must also be able to detect drifts in the opponent's preferences so as to quickly adjust itself to their new offer policy. For this purpose, two simple learning techniques were first evaluated: (i) based on instances (IB3) and (ii) based on Bayesian Networks. Additionally, as its known that in theory group learning produces better results than individual/single learning, the efficiency of IB3 and Bayesian classifier groups were also analyzed. Finally, each decision model was evaluated in moments of concept drift, being the drift gradual, moderate or abrupt. Results showed that both groups of classifiers were able to effectively detect drifts in the opponent's preferences.

E-learning policies, practices and challenges in two Norwegian organizations.

Science.gov (United States)

Welle-Strand, Anne; Thune, Taran

2003-05-01

This article reports a pilot study on the uses of technology to enable learning within a formal educational setting in a higher education institution and within a corporation. These two Norwegian cases were selected due to their commitment to technology-enabled learning, as expressed in policy and strategy documents. The aim was to investigate the commitment and actual use of information and communications technology (ICT) for learning as well as what key actors think are the major challenges for successful large scale implementation of ICT for learning. The findings indicate that there is insufficient follow-up on e-learning policies and that there is a general lack of strategic direction and leadership in this area. The key challenges respondents highlight relate to the need for a systematic and pedagogical approach to e-learning in which three equally important considerations must be balanced: organization, pedagogy and technology. Key perspectives of a coherent pedagogical and organizational framework for planning e-learning are discussed.

Active Ageing, Active Learning: Policy and Provision in Hong Kong

Science.gov (United States)

Tam, M.

2011-01-01

This paper discusses the relationship between ageing and learning, previous literature having confirmed that participation in continued learning in old age contributes to good health, satisfaction with life, independence and self-esteem. Realizing that learning is vital to active ageing, the Hong Kong government has implemented policies and…

Quality and Equality: The Mask of Discursive Conflation in Education Policy Texts

Science.gov (United States)

Gillies, Donald

2008-01-01

Two key themes of recent UK education policy texts have been a focus on "quality" in public sector performance, and on "equality" in the form of New Labour's stated commitment to equality of opportunity as a key policy objective. This twin approach can be seen at its most obvious in the concept of "excellence for…

Metacomprehension judgements reflect the belief that diagrams improve learning from text.

Science.gov (United States)

Serra, Michael J; Dunlosky, John

2010-10-01

In two experiments we systematically explored whether people consider the format of text materials when judging their text learning, and whether doing so might inappropriately bias their judgements. Participants studied either text with diagrams (multimedia) or text alone and made both per-paragraph judgements and global judgements of their text learning. In Experiment 1 they judged their learning to be better for text with diagrams than for text alone. In that study, however, test performance was greater for multimedia, so the judgements may reflect either a belief in the power of multimedia or on-line processing. Experiment 2 replicated this finding and also included a third group that read texts with pictures that did not improve text performance. Judgements made by this group were just as high as those made by participants who received the effective multimedia format. These results confirm the hypothesis that people's metacomprehension judgements can be influenced by their beliefs about text format. Over-reliance on this multimedia heuristic, however, might reduce judgement accuracy in situations where it is invalid.

Feed-in Tariff Pricing and Social Burden in Japan: Evaluating International Learning through a Policy Transfer Approach

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Yugo Tanaka

2017-10-01

Full Text Available Feed-in tariff (FiT policy approaches for renewable energy (RE deployment are employed in many nations around the world. Although FiTs are considered effective in boosting RE deployment, the issue of increasing energy bills and social burden is an often-reported negative impact of their use. The FiT has been employed in Japan since 2012, following after many developed countries, and, as was experienced in other nations, led to a social burden imparted on society significantly higher than initial government estimates. Although policy decision making does not necessarily reflect international policy experience, it is still prudent to ask how international policy experiences of social burden increase were considered within the Japanese approach. In this research, we analyzed the transfer process by adapting a conventional model to develop more objective observations than was previously possible, by setting a benchmark for evaluation based on prior international experiences. We identified two streams of policy transfer, each led by different actors; the government and representatives of the National Diet of Japan (Diet. Both actors were exposed to the same experiences, however the interpretation, application to policy development and priority settings employed were vastly different. Although the framework can only assess policy learning processes, we have found that the government undertook a reasonable and rational process toward learning, while, on the other hand, the modified bill developed by the Diet members did not thoroughly derive learnings in the same way, due to cognitive and political reasons, and specifically, the issue of limiting social burden was not addressed.

Focus of Attention and Choice of Text Modality in Multimedia Learning

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Schnotz, Wolfgang; Mengelkamp, Christoph; Baadte, Christiane; Hauck, Georg

2014-01-01

The term "modality effect" in multimedia learning means that students learn better from pictures combined with spoken rather than written text. The most prominent explanations refer to the split attention between visual text reading and picture observation which could affect transfer of information into working memory, maintenance of…

Two Decades of E-Learning Policy Evolution at EU Level: Motivations, Institutions and Instruments

Science.gov (United States)

Salajan, Florin D.; Roumell, Elizabeth A.

2016-01-01

This article records and documents the historical development of e-learning policies at EU level by conducting a discourse and content analysis of four key e-learning policy documents drafted and implemented by the European Commission over the past 20 years: "Learning in the Information Society: Action Plan for a European Education…

Global perpectives on adult education and learning policy

DEFF Research Database (Denmark)

on citizenship and democracy. It highlights several significant shifts: increased awareness of the role of adult education/lifelong learning in enhancing economic growth and social cohesion and mobility, challenging economic and social exclusion and inequality, and developing human and social capital; increased......Most observers regard both adult and higher education as key for citizenship and democracy yet the worldwide contexts, appearance and expression of adult education and lifelong learning have changed significantly during the past 20 years. Focusing on ten countries (Scotland, Czech Republic, USA......, Brazil, Mexico, Botswana, Ghana, Palestine, South Korea and India) and five international organisations, this book explores recent changes in their overall contexts and policies about adult education, how such policies intersect with developments in higher education and how they may contribute to debates...

Policy learning and policy networks in theory and practice: The role of policy brokers in the Indonesian biodiesel policy network

NARCIS (Netherlands)

M. Howlett (Michael); Mukherjee, I. (Ishani); J.F.M. Koppenjan (Joop)

2017-01-01

textabstractThis paper examines how learning has been treated, generally, in policy network theories and what questions have been posed, and answered, about this phenomenon to date. We examine to what extent network characteristics and especially the presence of various types of brokers impede or

Institutional policy learning and public consultation: the Canadian xenotransplantation experience.

Science.gov (United States)

Jones, Mavis; Einsiedel, Edna

2011-09-01

Attempts to evaluate public consultations, participatory technology assessment, and deliberative democracy have typically considered impacts on either policy or participants. The determination of impacts on policy institutions has been limited due to the challenges of tracing effects through the policy process, or penetrating bureaucratic walls. This paper presents findings from a retrospective study exploring the institutional lessons learned from a 2001 Canadian national public consultation on xenotransplantation. The consultation was conducted through an arm's-length process and involved the use of citizen juries in six regional sites. We conducted in-depth interviews of regulatory and policy actors who were engaged in early policy discussions and the consultation process. We reviewed evaluations of this process, both internal and external, which gave us richer insights into what institutional actors saw as the impacts of this consultative experience on their policy environment. Participants in our research identified a broader shift toward openness in policy culture which they linked specifically to the innovative consultation process employed for xenotransplantation. We argue that beyond input into policy decisions, a consultation may have an impact in terms of its contribution to overall shifts in institutional culture (related to institutional learning), such as an "opening" of technological decision processes to a broader range of actors, knowledge, and values. Copyright © 2011 Elsevier Ltd. All rights reserved.

Learning Convolutional Text Representations for Visual Question Answering

OpenAIRE

Wang, Zhengyang; Ji, Shuiwang

2017-01-01

Visual question answering is a recently proposed artificial intelligence task that requires a deep understanding of both images and texts. In deep learning, images are typically modeled through convolutional neural networks, and texts are typically modeled through recurrent neural networks. While the requirement for modeling images is similar to traditional computer vision tasks, such as object recognition and image classification, visual question answering raises a different need for textual...

Policy relevance and the valence of interests: Policy learning in the liberalization of the railways and the electricity sector in Belgium

NARCIS (Netherlands)

S. Moyson (Stéphane)

2013-01-01

markdownabstract__Abstract__ Policy learning designates the relatively enduring alterations of policymakers’ beliefs and preferences regarding policies, following new information and experience. Policy leaning being a crucial factor of policy change, the study of its factors is central. The

Toward Effective Water Pipe Tobacco Control Policy in the United States: Synthesis of Federal, State, and Local Policy Texts.

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Colditz, Jason B; Ton, Jessica N; James, A Everette; Primack, Brian A

2017-07-01

Water pipe tobacco smoking (WTS) is growing in popularity among U.S. young adults and is associated with health risks similar to those of cigarette smoking. The purpose of this study is to examine existing tobacco control policies (TCPs) in order to investigate how they engage WTS. A systematic synthesis of content and legal interactions among federal, state, and local TCP documents. Pennsylvania, which represents a politically and demographically diverse microcosm of the United States. No human subjects. Federal and state TCPs were retrieved via public legal repositories. Local policy searches were conducted via county/municipal Web sites, inclusive of 13 localities that had autonomous health departments or existing TCPs based on a National Cancer Institute report. Full-text TCPs were double coded within a grounded theory framework for health policy analysis. Emergent codes were used to compare and contrast policy texts and to examine legal interactions among TCPs. Examination of policy categories including youth access, use restrictions, and taxation revealed WTS as largely omitted from current TCPs. WTS was sometimes addressed as an "other" tobacco product under older TCPs, though ambiguities in language led to questionable enforceability. State preemptions have rolled back or prevented well-tailored reforms at the local level. Federal preemptions have likewise constrained state TCPs. Outdated, preempted, and unclear policies limit the extent to which TCPs engage WTS. Health advocates might target these aspects of TCP reform.

Off-policy integral reinforcement learning optimal tracking control for continuous-time chaotic systems

International Nuclear Information System (INIS)

Wei Qing-Lai; Song Rui-Zhuo; Xiao Wen-Dong; Sun Qiu-Ye

2015-01-01

This paper estimates an off-policy integral reinforcement learning (IRL) algorithm to obtain the optimal tracking control of unknown chaotic systems. Off-policy IRL can learn the solution of the HJB equation from the system data generated by an arbitrary control. Moreover, off-policy IRL can be regarded as a direct learning method, which avoids the identification of system dynamics. In this paper, the performance index function is first given based on the system tracking error and control error. For solving the Hamilton–Jacobi–Bellman (HJB) equation, an off-policy IRL algorithm is proposed. It is proven that the iterative control makes the tracking error system asymptotically stable, and the iterative performance index function is convergent. Simulation study demonstrates the effectiveness of the developed tracking control method. (paper)

Language and Text-to-Speech Technologies for Highly Accessible Language & Culture Learning

Directory of Open Access Journals (Sweden)

Anouk Gelan

2011-06-01

Full Text Available This contribution presents the results of the “Speech technology integrated learning modules for Intercultural Dialogue” project. The project objective was to increase the availability and quality of e-learning opportunities for less widely-used and less taught European languages using a user-friendly and highly accessible learning environment. The integration of new Text-to-Speech developments into web-based authoring software for tutorial CALL had a double goal: on the one hand increase the accessibility of e-learning packages, also for learners having difficulty reading (e.g. dyslexic learners or preferring auditory learning; on the other hand exploiting some didactic possibilities of this technology.

Evidence-based policy learning: the case of the research excellence indicat

Energy Technology Data Exchange (ETDEWEB)

Hardeman, S.; Vertesy, D.

2016-07-01

Excellence is arguably the single most important concept in academia today, especially when it comes to science policy making. At the same time, however, excellence leads to a great amount of discomfort, leading some to plea for an overall rejection of the concept. The discomfort with excellence reaches its heights whenever proposals are made for measuring it. Yet, especially given the period of professionalization science policy making finds itself in, these same metrics are frequently called upon to legitimate policy interventions. Excellence and its measurement, it seems therefore, is something we can neither life with nor without. This paper offers some middle ground in the debate on excellence and its measurement for science policy purposes. Using the case of the European Commission’s Research Excellence Indicator as an example, we show how the development and use of indicators offers an opportunity for learning in science policy making. Ultimately, therefore, we show how and in what ways measuring excellence can contribute to evidence-based science policy learning in practice. (Author)

The Impact of Irish Policy and Legislation on How Adults with Learning Disabilities Make Choices

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Carey, Eileen; Griffiths, Colin

2016-01-01

This paper reflects the impact of policy and legislation in the context of how adults with learning disabilities make choices. Following an overview of policies which have improved choice for people with learning disability in the United Kingdom, this paper reviews "choice" in current Irish policy and legislation. This paper, while…

Public policies: right to learn and formative assessment

Directory of Open Access Journals (Sweden)

Antonio Chizzotti

2016-09-01

Full Text Available This paper deals with the right to learn in school type education and considers the assessment as assurance of teaching and learning quality. It deals with the current evaluation processes and discriminatory misconceptions of merely summative assessments, which tend to qualify students. This text evaluates the punitive bias of meritocratic grading of learning and argues that only formative assessment can ensure the right to learn

Can Questions Facilitate Learning from Illustrated Science Texts?

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Iding, Marie K.

1997-01-01

Examines the effectiveness of using questions to facilitate processing of diagrams in science texts. Investigates three different elements in experiments on college students. Finds that questions about illustrations do not facilitate learning. Discusses findings with reference to cognitive load theory, the dual coding perspective, and the…

The Credibility of Policy Reporting Across Learning Disciplines

Energy Technology Data Exchange (ETDEWEB)

Carley, S.; Youtie, J.; Solomon, G.; Porter, A.

2016-07-01

The notion of a credibility map argues that everyone has a distinctive map that dictates the preference given to different types and sources of information. When seeking to influence other academic fields, scholars will likely turn to scientific and technical information though other types, such as policy reports, may also be relevant. We draw on the credibility mapping concept to understand how a major policy report is taken up by the target academic community. The report, How People Learn, was published by the US National Academies in 2000, to expose the education community (mainly educational researchers but also knowledge-seeking practitioners) to major cognitive science research findings of relevance to learning. We applied several search strings to measure the take up of this report in the target community. We used Google Scholar to evince that that How People Learn was cited in nearly 15,000 publications, these citations grew particularly steeply from 2000 to 2008, and most were in education-related journal papers. We performed a similar analysis using the Web of Science, which showed that most of the citations were substantial as opposed to perfunctory. (Author)

Children’s comprehension of informational text: Reading, engaging, and learning

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Linda BAKER

2011-11-01

Full Text Available The Reading, Engaging, and Learning project (REAL investigated whether a classroom intervention that enhanced young children's experience with informational books would increase reading achievement and engagement. Participants attended schools serving low income neighborhoods with 86% African American enrollment. The longitudinal study spanned second through fourth grades. Treatment conditions were: (1 Text Infusion/Reading for Learning Instruction -- students were given greater access to informational books in their classroom libraries and in reading instruction; (2 Text Infusion Alone -- the same books were provided but teachers were not asked to alter their instruction; (3 Traditional Instruction -- students experienced business as usual in the classroom. Children were assessed each year on measures of reading and reading engagement, and classroom instructional practices were observed. On most measures, the informational text infusion intervention did not yield differential growth over time. However, the results inform efforts to increase children’s facility with informational text in the early years in order to improve reading comprehension.

Active learning for clinical text classification: is it better than random sampling?

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Figueroa, Rosa L; Ngo, Long H; Goryachev, Sergey; Wiechmann, Eduardo P

2012-01-01

Objective This study explores active learning algorithms as a way to reduce the requirements for large training sets in medical text classification tasks. Design Three existing active learning algorithms (distance-based (DIST), diversity-based (DIV), and a combination of both (CMB)) were used to classify text from five datasets. The performance of these algorithms was compared to that of passive learning on the five datasets. We then conducted a novel investigation of the interaction between dataset characteristics and the performance results. Measurements Classification accuracy and area under receiver operating characteristics (ROC) curves for each algorithm at different sample sizes were generated. The performance of active learning algorithms was compared with that of passive learning using a weighted mean of paired differences. To determine why the performance varies on different datasets, we measured the diversity and uncertainty of each dataset using relative entropy and correlated the results with the performance differences. Results The DIST and CMB algorithms performed better than passive learning. With a statistical significance level set at 0.05, DIST outperformed passive learning in all five datasets, while CMB was found to be better than passive learning in four datasets. We found strong correlations between the dataset diversity and the DIV performance, as well as the dataset uncertainty and the performance of the DIST algorithm. Conclusion For medical text classification, appropriate active learning algorithms can yield performance comparable to that of passive learning with considerably smaller training sets. In particular, our results suggest that DIV performs better on data with higher diversity and DIST on data with lower uncertainty. PMID:22707743

THE IMPLICATION OF PRE-SERVICE TEACHERS BELIEF ABOUT GRAMMAR TEACHING AND LEARNING FOR ENGLISH LANGUAGE POLICY IN INDONESIA

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Cecilia Titiek Murniati

2016-07-01

Full Text Available Recent studies have suggested that teachers beliefs have a significant influence on actual classroom practice and, consequently, on students achievements. However, little research has been done to investigate the influence of Indonesian language policy and teachers beliefs. The study reported seeks to examine the influence of English language policy on pre-service teacher's beliefs about the teaching of English language grammar in Indonesian schools. The research participants were pre-service teachers who have taken the subjects of Structure, Teaching Methods, and Micro-teaching in three public and private universities in Central Java and Yogyakarta Special District. Due to time and scheduling limitations, the sampling method used in this study was convenient sampling. Documentation, survey schedules, interviews, focus group discussions were used to gather the data. The findings revealed that although the language policy in Indonesia has put English language teaching and learning within the framework of communicative competence since the enactment of the 2006 School-based Curriculum, the pre-service teachers still believed that traditional method of teaching grammar (explicit grammar instruction was imperative to use. The pre-service teachers tended to exclude English language policy enacted by Indonesian government in their discussion about teachers beliefs. Instead, the pre-service teachers constructed their beliefs about English language grammar teaching and learning process on their prior experiences in learning and teaching grammar.

Oral History as Complement to Place-as-Text: Approaches to Service Learning

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Pederson, JoEllen; Znosko, Jessi; Peters, Jesse; Cannata, Susan M.

2018-01-01

The purpose of this paper is to discuss the advantages of combining place-as-text curriculum with an oral history collection to act as catalysts for transformational learning. These experiential and service learning practices complement each other to enrich the encounters students are afforded. First, the nature and procedures of place-as-text and…

What Do Professional Learning Policies Say about Purposes of Teacher Education?

Science.gov (United States)

Kennedy, Aileen

2015-01-01

Enhancing teacher learning is acknowledged globally as a key route to improving student outcomes, thereby contributing to nation states' economic competitiveness. This globally accepted policy "hypernarrative" is driving reform of teacher education policy internationally. This article seeks to analyse some key features of contemporary…

Student Learning with Permissive and Restrictive Cell Phone Policies: A Classroom Experiment

Science.gov (United States)

Lancaster, Alexander L.

2018-01-01

Based on Finn and Ledbetter's (2013; 2014) work regarding classroom technology policies, this experimental study examined the implementation of a permissive and a restrictive cellular phone policy and the effect of these policies on students' cognitive and affective learning in two sections of a public speaking course. College students (N = 31)…

How Well can We Learn Interpretable Entity Types from Text?

DEFF Research Database (Denmark)

Hovy, Dirk

2014-01-01

We investigate a largely unsupervised approach to learning interpretable, domain-specific entity types from unlabeled text. It assumes that any common noun in a domain can function as potential entity type, and uses those nouns as hidden variables in a HMM. To constrain training, it extracts co......-occurrence dictionaries of entities and common nouns from the data. We evaluate the learned types by measuring their prediction accuracy for verb arguments in several domains. The results suggest that it is possible to learn domain-specific entity types from unlabeled data. We show significant improvements over...

An In-Depth Analysis of Adult Learning Policies and Their Effectiveness in Europe

Science.gov (United States)

European Union, 2015

2015-01-01

Adult learning policies, like any other policies, need to be effective: they need to reach their objectives and attain the desired impacts, which should be carefully defined. Understanding the performance of policies allows policy makers to change and improve them. A growing body of research and statistics provides important insights into how…

Distance learning education for mitigation/adaptation policy: a case study

Science.gov (United States)

Slini, T.; Giama, E.; Papadopoulou, Ch.-O.

2016-02-01

The efficient training of young environmental scientists has proven to be a challenging goal over the last years, while several dynamic initiatives have been developed aiming to provide complete and consistent education. A successful example is the e-learning course for participants mainly coming from emerging economy countries 'Development of mitigation/adaptation policy portfolios' organised in the frame of the project Promitheas4: Knowledge transfer and research needs for preparing mitigation/adaptation policy portfolios, aiming to provide knowledge transfer, enhance new skills and competencies, using modern didactic approaches and learning technologies. The present paper addresses the experience and the results of these actions, which seem promising and encouraging and were broadly welcomed by the participants.

Directed Activities Related to Text: Text Analysis and Text Reconstruction.

Science.gov (United States)

Davies, Florence; Greene, Terry

This paper describes Directed Activities Related to Text (DART), procedures that were developed and are used in the Reading for Learning Project at the University of Nottingham (England) to enhance learning from texts and that fall into two broad categories: (1) text analysis procedures, which require students to engage in some form of analysis of…

Developments in Interpreting Learning Curves and Applications to Energy Technology Policy

International Nuclear Information System (INIS)

Van der Zwaan, B.C.C.; Wene, C.O.

2011-01-01

The book 'Learning Curves: Theory, Models, and Applications' first draws a learning map that shows where learning is involved within organizations, then examines how it can be sustained, perfected, and accelerated. The book reviews empirical findings in the literature in terms of different sources for learning and partial assessments of the steps that make up the actual learning process inside the learning curve. Chapter 23 on 'Developments in Interpreting Learning Curves and Applications to Energy Technology Policy' is written by Bob van der Zwaan and Clas-Otto Wene. In this chapter they provide some interpretations of experience and learning curves starting from three different theoretical platforms. These interpretations are aimed at explaining learning rates for different energy technologies. The ultimate purpose is to find the role that experience and learning curves can legitimately play in designing efficient government deployment programs and in analyzing the implications of different energy scenarios. The 'Component Learning' section summarizes recent work by the authors that focuses on the disaggregation of technologies in their respective components and argues that traditional learning for overall technology should perhaps be replaced by a phenomenology that recognizes learning for individual components. The 'Learning and Time' section presents an approach that departs more strongly from the conventional learning curve methodology, by suggesting that exponential growth and progress may be the deeper underlying processes behind observed learning-by-doing. Contrary to this view, the cybernetic approach presented in the 'Cybernetic Approach' section sees learning curves as expressing a fundamental property of organizations in competitive markets and applies the findings from second order cybernetics to calculate the learning rates for operationally closed systems. All three interpretations find empirical support. The 'Conclusions' section summarizes the

Developments in Interpreting Learning Curves and Applications to Energy Technology Policy

Energy Technology Data Exchange (ETDEWEB)

Van der Zwaan, B.C.C. [Energy research Centre of the Netherlands, ECN Policy Studies, Petten (Netherlands); Wene, C.O. [Wenergy, Lund (Sweden)

2011-06-15

The book 'Learning Curves: Theory, Models, and Applications' first draws a learning map that shows where learning is involved within organizations, then examines how it can be sustained, perfected, and accelerated. The book reviews empirical findings in the literature in terms of different sources for learning and partial assessments of the steps that make up the actual learning process inside the learning curve. Chapter 23 on 'Developments in Interpreting Learning Curves and Applications to Energy Technology Policy' is written by Bob van der Zwaan and Clas-Otto Wene. In this chapter they provide some interpretations of experience and learning curves starting from three different theoretical platforms. These interpretations are aimed at explaining learning rates for different energy technologies. The ultimate purpose is to find the role that experience and learning curves can legitimately play in designing efficient government deployment programs and in analyzing the implications of different energy scenarios. The 'Component Learning' section summarizes recent work by the authors that focuses on the disaggregation of technologies in their respective components and argues that traditional learning for overall technology should perhaps be replaced by a phenomenology that recognizes learning for individual components. The 'Learning and Time' section presents an approach that departs more strongly from the conventional learning curve methodology, by suggesting that exponential growth and progress may be the deeper underlying processes behind observed learning-by-doing. Contrary to this view, the cybernetic approach presented in the 'Cybernetic Approach' section sees learning curves as expressing a fundamental property of organizations in competitive markets and applies the findings from second order cybernetics to calculate the learning rates for operationally closed systems. All three interpretations find empirical

The Use of Conceptual Change Text toward Students’ Argumentation Skills in Learning Sound

Science.gov (United States)

Sari, B. P.; Feranie, S.; Winarno, N.

2017-09-01

This research aim is to investigate the effect of Conceptual Change Text toward students’ argumentation skills in learning sound concept. The participant comes from one of International school in Bandung, Indonesia. The method that used in this research is a quasi-experimental design with one control group (N=21) and one experimental group (N=21) were involves in this research. The learning model that used in both classes is demonstration model which included teacher explanation and examples, the difference only in teaching materials. In experiment group learn with Conceptual Change Text, while control group learn with conventional book which is used in school. The results showed that Conceptual Change Text instruction was better than the conventional book to improved students’ argumentation skills of sound concept. Based on this results showed that Conceptual Change Text instruction can be an alternative tool to improve students’ argumentation skills significantly.

Maximizing Reading Narrative Text Ability by Probing Prompting Learning Technique

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Wiwied Pratiwi

2017-12-01

Full Text Available The objective of this research was to know whether Probing Prompting Learning Technique can be used to get the maximum effect of students’ reading narrative ability in teaching and learning process. This research was applied collaborative action reEsearch, this research was done in two cycle. The subject of this research was 23 students at tenth grade of SMA Kartikatama Metro. The result of the research showed that the Probing Prompting Learning Technique is useful and effective to help students get maximum effect of their reading. Based on the results of the questionnaire obtained an average percentage of 95%, it indicated that application of Probing Prompting Learning Technique in teaching l reading was appropriately applied. In short that students’ responses toward Probing Prompting Learning Technique in teaching reading was positive. In conclusion, Probing Prompting Learning Technique can get maximum effect of students’ reading ability. In relation to the result of the reserach, some suggestion are offered to english teacher, that  the use of Probing Prompting learning Technique in teaching reading will get the maximum effect of students’ reading abilty.

Blended learning on family planning policy requirements: key findings and implications for health professionals.

Science.gov (United States)

Limaye, Rupali J; Ahmed, Naheed; Ohkubo, Saori; Ballard, Anne

2018-04-01

To address unmet needs for family planning and advance women's rights, US federal foreign aid recipients must ensure compliance with the family planning legislative and policy requirements. Because many health providers work in rural and remote settings, blended learning, which combines in-person and online experiences, is a promising approach for strengthening their compliance knowledge. This cross-sectional study examined the effect of blended learning that included three components (online course, in-person training and conference call) on retention of family planning compliance knowledge. A total of 660 learners from 44 countries completed the online survey (8% response rate). Study participants were asked about their knowledge of family planning compliance and suggestions to improve their learning experiences. Knowledge retention was higher in the group that utilised all three learning approaches compared with the online course plus conference call group (Pblended learning training resulted in the highest gains in knowledge retention compared with online-only learning. These findings suggest that blended learning and repeat online trainings are critical to ensuring health professionals are aware of family planning compliance regulations. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Opinion Mining in Latvian Text Using Semantic Polarity Analysis and Machine Learning Approach

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Gatis Špats

2016-07-01

Full Text Available In this paper we demonstrate approaches for opinion mining in Latvian text. Authors have applied, combined and extended results of several previous studies and public resources to perform opinion mining in Latvian text using two approaches, namely, semantic polarity analysis and machine learning. One of the most significant constraints that make application of opinion mining for written content classification in Latvian text challenging is the limited publicly available text corpora for classifier training. We have joined several sources and created a publically available extended lexicon. Our results are comparable to or outperform current achievements in opinion mining in Latvian. Experiments show that lexicon-based methods provide more accurate opinion mining than the application of Naive Bayes machine learning classifier on Latvian tweets. Methods used during this study could be further extended using human annotators, unsupervised machine learning and bootstrapping to create larger corpora of classified text.

Introduction: Global Outlook on Adult Education and Learning Policies

DEFF Research Database (Denmark)

Milana, Marcella

2015-01-01

opportunities to flourish or perish. Further, it acknowledges the importance for adult education and learning policies of governance beyond and across the purview of governmental structures that operate within single countries, where state-led institutions and non-governmental international organizations play...

Learning from games: Stakeholders’ experiences involved in local health policy

DEFF Research Database (Denmark)

Spitters, Hilde; van de Goor, Ien; Juel Lau, Cathrine

2018-01-01

Since public health problems are complex and the related policies need to address a wide range of sectors, cross-sectoral collaboration is beneficial. One intervention focusing on stimulating collaboration is a ‘policy game’. The focus on specific problems facilitates relationships between...... the stakeholders and stimulates cross-sectoral policymaking. The present study explores stakeholders’ learning experiences with respect to the collaboration process in public health policymaking. This was achieved via their game participation, carried out in real-life stakeholder networks in the Netherlands...... the collaboration processes in local policymaking. Specific learning experiences were related to: (i) the stakeholder network, (ii) interaction and (iii) relationships. The game also increased participant’s understanding of group dynamics and need for a coordinator in policymaking. This exploratory study shows...

Generative Learning Strategy Use and Self-Regulatory Prompting in Digital Text

Science.gov (United States)

Reid, Alan J.; Morrison, Gary M.

2014-01-01

The digital revolution is shifting print-based textbooks to digital text, and it has afforded the opportunity to incorporate meaningful learning strategies and otherwise separate metacognitive activities directly into these texts as embedded support. A sample of 89 undergraduates read a digital, expository text on the basics of photography. The…

A Novel Text Clustering Approach Using Deep-Learning Vocabulary Network

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Junkai Yi

2017-01-01

Full Text Available Text clustering is an effective approach to collect and organize text documents into meaningful groups for mining valuable information on the Internet. However, there exist some issues to tackle such as feature extraction and data dimension reduction. To overcome these problems, we present a novel approach named deep-learning vocabulary network. The vocabulary network is constructed based on related-word set, which contains the “cooccurrence” relations of words or terms. We replace term frequency in feature vectors with the “importance” of words in terms of vocabulary network and PageRank, which can generate more precise feature vectors to represent the meaning of text clustering. Furthermore, sparse-group deep belief network is proposed to reduce the dimensionality of feature vectors, and we introduce coverage rate for similarity measure in Single-Pass clustering. To verify the effectiveness of our work, we compare the approach to the representative algorithms, and experimental results show that feature vectors in terms of deep-learning vocabulary network have better clustering performance.

Respecting Young People's Informal Learning: Circumventing Strategic Policy Evasions

Science.gov (United States)

Quinn, Jocey

2018-01-01

This paper explores experiences at the interface of research and policy through the lens of informal learning. The paper contends that in order to further social justice it is essential to value the informal learning that takes place outside the confines of educational institutions. However, it also demonstrates the difficulties in getting…

Orthographic learning and the role of text-to-speech software in Dutch disabled readers.

Science.gov (United States)

Staels, Eva; Van den Broeck, Wim

2015-01-01

In this study, we examined whether orthographic learning can be demonstrated in disabled readers learning to read in a transparent orthography (Dutch). In addition, we tested the effect of the use of text-to-speech software, a new form of direct instruction, on orthographic learning. Both research goals were investigated by replicating Share's self-teaching paradigm. A total of 65 disabled Dutch readers were asked to read eight stories containing embedded homophonic pseudoword targets (e.g., Blot/Blod), with or without the support of text-to-speech software. The amount of orthographic learning was assessed 3 or 7 days later by three measures of orthographic learning. First, the results supported the presence of orthographic learning during independent silent reading by demonstrating that target spellings were correctly identified more often, named more quickly, and spelled more accurately than their homophone foils. Our results support the hypothesis that all readers, even poor readers of transparent orthographies, are capable of developing word-specific knowledge. Second, a negative effect of text-to-speech software on orthographic learning was demonstrated in this study. This negative effect was interpreted as the consequence of passively listening to the auditory presentation of the text. We clarify how these results can be interpreted within current theoretical accounts of orthographic learning and briefly discuss implications for remedial interventions. © Hammill Institute on Disabilities 2013.

A Deep Similarity Metric Learning Model for Matching Text Chunks to Spatial Entities

Science.gov (United States)

Ma, K.; Wu, L.; Tao, L.; Li, W.; Xie, Z.

2017-12-01

The matching of spatial entities with related text is a long-standing research topic that has received considerable attention over the years. This task aims at enrich the contents of spatial entity, and attach the spatial location information to the text chunk. In the data fusion field, matching spatial entities with the corresponding describing text chunks has a big range of significance. However, the most traditional matching methods often rely fully on manually designed, task-specific linguistic features. This work proposes a Deep Similarity Metric Learning Model (DSMLM) based on Siamese Neural Network to learn similarity metric directly from the textural attributes of spatial entity and text chunk. The low-dimensional feature representation of the space entity and the text chunk can be learned separately. By employing the Cosine distance to measure the matching degree between the vectors, the model can make the matching pair vectors as close as possible. Mearnwhile, it makes the mismatching as far apart as possible through supervised learning. In addition, extensive experiments and analysis on geological survey data sets show that our DSMLM model can effectively capture the matching characteristics between the text chunk and the spatial entity, and achieve state-of-the-art performance.

TEXT-BASED LEARNING (TBL TO ACTIVATE ADULT EFL LEARNERS IN LEARNING ENGLISH: A NARRATIVE INQUIRY

Directory of Open Access Journals (Sweden)

Erna Iftanti

2017-06-01

Full Text Available In response to the fact that college students complain on their unsuccessful story of their EFL learning experience such as the limited number of vocabulary, English Grammar confusion, low competence of English language skills, this article explores an alternative effective way of helping them to improve their English through Text-Based Learning (TBL model. This article is then intended to narrate the implementation of TBL to teach English for college students of non English Department of Post Graduate Program of State Islamic Institute of Tulungagung, Indonesia. The result of implementing this teaching model proves to be able to not only stimulate joyful learning atmosphere but to attract the students’ active participation during the EFL instructional process as well. This further brings about their better practical understanding on English language skills as their expectation. Therefore, for English lecturers, this model is pedagogically good to be implemented in their English instructional practices.

Textbooks for Content and Language Integrated Learning: policy, market and appropriate didactics?

Directory of Open Access Journals (Sweden)

María Ángeles Martín del Pozo

2015-02-01

Full Text Available The paper begins by approaching the concept of CLIL (Content and Language Integrated Learning providing a brief overview of the history of bilingual education. The influence of the linguistic policies of the European Union is discussed along with some beliefs about language teaching and how both have influenced the celerity of CLIL implementation, momentum and expansion. There are some indicators of the lack of a theoretical framework for CLIL, of insufficient teacher education and or inadequacy of materials. It is necessary to reflect systematically on to what extent commercially published textbooks match the demands of bilingual education. The second section centers on CLIL textbooks, mainly those commercialized by publishers, by referring to some recent studies which attempt to approach systematically their design and use. Since, by definition CLIL includes both content and language, our research question is if content books (in English also include content and language objectives. A corpus of 25 books from different subjects, years, and publishers is analyzed. The analysis shows an insufficient presence of linguistic objectives. Some reflections are made about this scarcity with the warning that this lack could hindrance an efficient implementation of CLIL. Thus, it could be said that these textbooks are not the product of discipline or didactic considerations but the result of the logic of market, publishers and linguistic policy.How to reference this articleMartín del Pozo, M. A., Rascón Estébanez, D. (2015. Textbooks for Content and Language Integrated Learning: policy, market and appropriate didactics?. Foro de Educación, 13(18, pp. 123-141. doi: http://dx.doi.org/10.14516/fde.2015.013.018.007 

Video- or text-based e-learning when teaching clinical procedures? A randomized controlled trial.

Science.gov (United States)

Buch, Steen Vigh; Treschow, Frederik Philip; Svendsen, Jesper Brink; Worm, Bjarne Skjødt

2014-01-01

This study investigated the effectiveness of two different levels of e-learning when teaching clinical skills to medical students. Sixty medical students were included and randomized into two comparable groups. The groups were given either a video- or text/picture-based e-learning module and subsequently underwent both theoretical and practical examination. A follow-up test was performed 1 month later. The students in the video group performed better than the illustrated text-based group in the practical examination, both in the primary test (Pvideo group performed better on the follow-up test (P=0.04). Video-based e-learning is superior to illustrated text-based e-learning when teaching certain practical clinical skills.

Optimal Control via Reinforcement Learning with Symbolic Policy Approximation

NARCIS (Netherlands)

Kubalìk, Jiřì; Alibekov, Eduard; Babuska, R.; Dochain, Denis; Henrion, Didier; Peaucelle, Dimitri

2017-01-01

Model-based reinforcement learning (RL) algorithms can be used to derive optimal control laws for nonlinear dynamic systems. With continuous-valued state and input variables, RL algorithms have to rely on function approximators to represent the value function and policy mappings. This paper

Off-policy reinforcement learning for H∞ control design.

Science.gov (United States)

Luo, Biao; Wu, Huai-Ning; Huang, Tingwen

2015-01-01

The H∞ control design problem is considered for nonlinear systems with unknown internal system model. It is known that the nonlinear H∞ control problem can be transformed into solving the so-called Hamilton-Jacobi-Isaacs (HJI) equation, which is a nonlinear partial differential equation that is generally impossible to be solved analytically. Even worse, model-based approaches cannot be used for approximately solving HJI equation, when the accurate system model is unavailable or costly to obtain in practice. To overcome these difficulties, an off-policy reinforcement leaning (RL) method is introduced to learn the solution of HJI equation from real system data instead of mathematical system model, and its convergence is proved. In the off-policy RL method, the system data can be generated with arbitrary policies rather than the evaluating policy, which is extremely important and promising for practical systems. For implementation purpose, a neural network (NN)-based actor-critic structure is employed and a least-square NN weight update algorithm is derived based on the method of weighted residuals. Finally, the developed NN-based off-policy RL method is tested on a linear F16 aircraft plant, and further applied to a rotational/translational actuator system.

More Efficient e-Learning through Design: Color of Text and Background

Science.gov (United States)

Zufic, Janko; Kalpic, Damir

2009-01-01

Background: The area of research aimed for a more efficient e-learning is slowly widening from purely technical to the areas of psychology, didactics and methodology. The question is whether the text or background color influence the efficiency of memory, i.e. learning. If the answer to that question is positive, then another question arises which…

When Do Pictures Help Learning from Expository Text? Multimedia and Modality Effects in Primary Schools

Science.gov (United States)

Herrlinger, Simone; Höffler, Tim N.; Opfermann, Maria; Leutner, Detlev

2017-06-01

Adding pictures to a text is very common in today's education and might be especially beneficial for elementary school children, whose abilities to read and understand pure text have not yet been fully developed. Our study examined whether adding pictures supports learning of a biology text in fourth grade and whether the text modality (spoken or written) plays a role. Results indicate that overall, pictures enhanced learning but that the text should be spoken rather than written. These results are in line with instructional design principles derived from common multimedia learning theories. In addition, for elementary school children, it might be advisable to read texts out to the children. Reading by themselves and looking at pictures might overload children's cognitive capacities and especially their visual channel. In this case, text and pictures would not be integrated into one coherent mental model, and effective learning would not take place.

State Digital Learning Exemplars: Highlights from States Leading Change through Policies and Funding

Science.gov (United States)

Acree, Lauren; Fox, Christine

2015-01-01

States are striving to support the expansion of technology tools and resources in K-12 education through state policies, programs, and funding in order to provide digital learning opportunities for all students. This paper highlights examples of states with policies in support of five key areas: (1) innovative funding streams and policy; (2)…

Fit, Healthy, and Ready To Learn: A School Health Policy Guide. Part II: Policies To Promote Sun Safety and Prevent Skin Cancer.

Science.gov (United States)

Fraser, Katherine

This publication is a supplementary chapter to "Fit, Healthy, and Ready to Learn: A School Health Policy Guide; Part I: General School Health Policies, Physical Activity, Healthy Eating, and Tobacco-Use Prevention." It discusses various aspects of a complete school policy and plan to promote sun safety. The first section "Purpose…

The importance of learning when supporting emergent technologies for energy efficiency-A case study on policy intervention for learning for the development of energy efficient windows in Sweden

International Nuclear Information System (INIS)

Kiss, Bernadett; Neij, Lena

2011-01-01

The role of policy instruments to promote the development and diffusion of energy efficient technologies has been repeatedly accentuated in the context of climate change and sustainable development. To better understand the impact of policy instruments and to provide insights into technology change, assessments of various kinds are needed. This study analyzes the introduction and development of energy efficient windows in Sweden and the policy incentives applied to support this process. The study focuses on the assessment of technology and market development of energy efficient windows in Sweden; and by applying the concept of learning, it assesses how conditions for learning-by-searching, learning-by-doing, learning-by-using and learning-by-interacting have been supported by different policies. The results show successful progress in technology development and an improvement in best available technology of Swedish windows from 1.8 W/m 2 K in the 1970s to 0.7 W/m 2 K in 2010; in the same time period the market share of energy efficient windows increased from 20% in 1970 (average U-value of 2.0 W/m 2 K) to 80-85% in 2010 (average U-value of 1.3-1.2 W/m 2 K). The assessment shows that various policy instruments have facilitated all four learning processes resulting in the acknowledged slow but successful development of energy efficient windows. - Highlights: → Policy instruments for learning and technology change are assessed. → The development and diffusion of energy efficient windows (EEWs) in Sweden is taken as showcase. → Learning has been supported by various policies resulting in successful development of EEWs. → The thermal performance of EEWs improved with 2/3 and their market share increased by 3/5 in 40 years. → Main policies for learning are RD and D, technology procurement, testing and voluntary initiatives.

Exploring the Complex Interplay of National Learning and Teaching Policy and Academic Development Practice

Science.gov (United States)

Smith, Karen

2016-01-01

Academic developers are important interpreters of policy, yet little research has focussed on the interplay of policy and academic development practice. Using methods from critical discourse analysis, this article analyses a national learning and teaching policy, charts its development, and explores its interpretation by the academic development…

Classroom-Based Integration of Text-Messaging in Mathematics Teaching-Learning Process

Science.gov (United States)

Aunzo, Rodulfo T., Jr.

2017-01-01

A lot of teachers are complaining that students are "texting" inside the classroom even during class hours. With this, this research study "on students' perception before the integration and the students' attitude after the integration of text messaging inside the classroom during the mathematics teaching-learning process was…

Combining Machine Learning and Natural Language Processing to Assess Literary Text Comprehension

Science.gov (United States)

Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S.

2017-01-01

This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…

Text-based Learning (Tbl) to Activate Adult Efl Learners in Learning English: a Narrative Inquiry

OpenAIRE

Iftanti, Erna

2017-01-01

In response to the fact that college students complain on their unsuccessful story of their EFL learning experience such as the limited number of vocabulary, English Grammar confusion, low competence of English language skills, this article explores an alternative effective way of helping them to improve their English through Text-Based Learning (TBL) model. This article is then intended to narrate the implementation of TBL to teach English for college students of non English Department of Po...

Recognition of prior learning policy and practice for skills learned at work : Australia, Canada, New Zealand, South Africa, United States

OpenAIRE

Dyson, Chloe

2005-01-01

Describes ways and issues of recognizing skills learned in the workplace or through non-formal activities, as opposed to learning at formal educational and training institutions. Examines policies and practices carried out in five English-speaking countries.

Two-way text messaging: an interactive mobile learning environment in higher education

Directory of Open Access Journals (Sweden)

H.K. Salinda Premadasa

2016-11-01

Full Text Available Short messaging service (SMS is perhaps the most popular mobile technology prevalent among students in higher education due to its ubiquitous nature and the capability of two-way communication. However, a major limitation in two-way text messaging is sending back a part of received data with the reply message. This limitation results in users of a mobile learning environment being unable to reply back to the correct destination. This article presents a two-way text messaging system that can be integrated into a learning management system (LMS to provide an interactive learning experience to the user community. Initially, a database is integrated into the LMS that holds message information such as recipient's phone number, message body and user data header. A specific port associated with the SMS is used to conceal and exchange data of a particular course unit. Subsequently, software in the student's mobile device captures this message and sends back the reply message to the appropriate course unit allowing both teachers and students to view messages sent and replies received pertaining to a particular course. Results indicate the educational impact of the proposed system in improving the learning environment and benefits it offers to the community in a campus-wide implementation.

Uncertainty vs. learning in climate policy: Some classical results and new directions

Energy Technology Data Exchange (ETDEWEB)

Lange, A. [Univ. of Maryland (United States); Treich, N. [Univ. of Toulouse (France)

2007-07-01

Climate policy decisions today have to be made under substantial uncertainty: the impact of accumulating greenhouse gases in the atmosphere is not perfectly known, the future economic and social consequences of climate change, in particular the valuation of possible damages, are uncertain. However, learning will change the basis of making future decisions on abatement policies. These important issues of uncertainty and learning are often presented in a colloquial sense. Two opposing effects are typically put forward: First, uncertainty about future climate damage, which is often associated with the possibility of a catastrophic scenario is said to give a premium to slow down global warming and therefore to increase abatement efforts today. Second learning opportunities will reduce scientific undertainty about climate damage over time. This is often used as an argument to postpone abatement efforts until new information is received. The effects of uncertainty and learning on the optimal design of current climate policy are still much debated both in the academic and the political arena. In this paper, the authors study and contrast the effect of uncertainty and learning in a two-decision model that encompasses most existing microeconomics models of climate change. They first consider the common expected utility framework: While uncertainty has generally no or a negative effect on welfare, learning has always a positive, and thus opposite, effect. The effects of both uncertainty and learning on decisions are less clear. Neither uncertainty nor learning can be used as an argument to increase or reduce emissions today, independently on the degree of risk aversion of the decision-marker and on the nature of irreversibility constraints. The authors then deviate from the expected utility framework and consider a model with ambiguity aversion. The model accounts well for situations of imprecise or multiple probability distributions, as present in the context of climate

Social learning in a policy-mandated collaboration: Community wildfire protection planning in the eastern United States

Science.gov (United States)

Rachel F. Brummel; Kristen C. Nelson; Pamela J. Jakes; Daniel R. Williams

2010-01-01

Policies such as the US Healthy Forests Restoration Act (HFRA) mandate collaboration in planning to create benefits such as social learning and shared understanding among partners. However, some question the ability of top-down policy to foster successful local collaboration. Through in-depth interviews and document analysis, this paper investigates social learning and...

The role of adult education and learning policy in fostering societal sustainability

Science.gov (United States)

Milana, Marcella; Rasmussen, Palle; Holford, John

2016-10-01

The idea of "sustainability" as a core value has slowly permeated policy and practice at governmental and institutional levels, in public and private policy. However, at times when social and economic crises have revealed the fragility of existing institutions and policies, it is important to consider how sustainability is - and could be - integrated into educational policies. In this theoretical contribution to a special issue on "Societal sustainability", the authors draw on available literature and knowledge. They begin their paper by summarising the conditions under which the concept of "sustainability" entered political discourse in the early 1970s and outline how it has influenced educational research. They then introduce the longstanding debate about the relative role of tradition (in terms of traditional cultural and social order) and change (in terms of efforts to provide learning opportunities for everyone) in adult education. Finally, they argue for a rethinking of the ontology of sustainability: this, they suggest, can shed new light on its relationships with adult education and learning and social justice.

The role of adult education and learning policy in fostering societal sustainability

DEFF Research Database (Denmark)

Milana, Marcella; Rasmussen, Palle Damkjær; Holford, John

2016-01-01

The idea of “sustainability” as a core value has slowly permeated policy and practice at governmental and institutional levels, in public and private policy. However, at times when social and economic crises have revealed the fragility of existing institutions and policies, it is important to con...... opportunities for everyone) in adult education. Finally, they argue for a rethinking of the ontology of sustainability: this, they suggest, can shed new light on its relationships with adult education and learning and social Justice....... to consider how sustainability is – and could be – integrated into educational policies. In this theoretical contribution to a special issue on “Societal sustainability”, the authors draw on available literature and knowledge. They begin their paper by summarising the conditions under which the concept...... of “sustainability” entered political discourse in the early 1970s and outline how it has influenced educational research. They then introduce the longstanding debate about the relative role of tradition (in terms of traditional cultural and social order) and change (in terms of efforts to provide learning...

Open Learning for Smart Education: Open educational policies, strategies & access for all

NARCIS (Netherlands)

Stracke, Christian M.

2016-01-01

keynote on Open Learning at the International IEEE EDUCON Conference 2016: I will speak about “Open Learning for Smart Education: Open educational policies, strategies and access for all”. This year EDUCON is taking place from 10th to 13th of April 2016 in Abu Dhabi. My questions of the keynote

Video- or text-based e-learning when teaching clinical procedures? A randomized controlled trial

Directory of Open Access Journals (Sweden)

Buch SV

2014-08-01

Full Text Available Steen Vigh Buch,1 Frederik Philip Treschow,2 Jesper Brink Svendsen,3 Bjarne Skjødt Worm4 1Department of Vascular Surgery, Rigshospitalet, Copenhagen, Denmark; 2Department of Anesthesia and Intensive Care, Herlev Hospital, Copenhagen, Denmark; 3Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; 4Department of Anesthesia and Intensive Care, Bispebjerg Hospital, Copenhagen, Denmark Background and aims: This study investigated the effectiveness of two different levels of e-learning when teaching clinical skills to medical students. Materials and methods: Sixty medical students were included and randomized into two comparable groups. The groups were given either a video- or text/picture-based e-learning module and subsequently underwent both theoretical and practical examination. A follow-up test was performed 1 month later. Results: The students in the video group performed better than the illustrated text-based group in the practical examination, both in the primary test (P<0.001 and in the follow-up test (P<0.01. Regarding theoretical knowledge, no differences were found between the groups on the primary test, though the video group performed better on the follow-up test (P=0.04. Conclusion: Video-based e-learning is superior to illustrated text-based e-learning when teaching certain practical clinical skills. Keywords: e-learning, video versus text, medicine, clinical skills

Learning Disabilities: Implications for Policy regarding Research and Practice--A Report by the National Joint Committee on Learning Disabilities, March 2011

Science.gov (United States)

Learning Disabilities: A Multidisciplinary Journal, 2012

2012-01-01

The National Joint Committee on Learning Disabilities (NJCLD) affirms that the construct of learning disabilities represents a valid, unique, and heterogeneous group of disorders, and that recognition of this construct is essential for sound policy and practice. An extensive body of scientific research on learning disabilities continues to support…

Armed To Learn: Aiming At California K 12 School Gun Policy

Science.gov (United States)

2016-03-01

AIMING AT CALIFORNIA K-12 SCHOOL GUN POLICY by Catherine Wilson Jones March 2016 Thesis Co-Advisors: Kathleen Kiernan John Rollins...Master’s thesis 4. TITLE AND SUBTITLE ARMED TO LEARN: AIMING AT CALIFORNIA K-12 SCHOOL GUN POLICY 5. FUNDING NUMBERS 6. AUTHOR(S) Catherine...gap in viewpoints between gun control advocates who want tighter gun control and constitutionalists who believe as strongly in the Second Amendment

Experiments on Supervised Learning Algorithms for Text Categorization

Science.gov (United States)

Namburu, Setu Madhavi; Tu, Haiying; Luo, Jianhui; Pattipati, Krishna R.

2005-01-01

Modern information society is facing the challenge of handling massive volume of online documents, news, intelligence reports, and so on. How to use the information accurately and in a timely manner becomes a major concern in many areas. While the general information may also include images and voice, we focus on the categorization of text data in this paper. We provide a brief overview of the information processing flow for text categorization, and discuss two supervised learning algorithms, viz., support vector machines (SVM) and partial least squares (PLS), which have been successfully applied in other domains, e.g., fault diagnosis [9]. While SVM has been well explored for binary classification and was reported as an efficient algorithm for text categorization, PLS has not yet been applied to text categorization. Our experiments are conducted on three data sets: Reuter's- 21578 dataset about corporate mergers and data acquisitions (ACQ), WebKB and the 20-Newsgroups. Results show that the performance of PLS is comparable to SVM in text categorization. A major drawback of SVM for multi-class categorization is that it requires a voting scheme based on the results of pair-wise classification. PLS does not have this drawback and could be a better candidate for multi-class text categorization.

Boosting solar investment with limited subsidies: Rent management and policy learning in India

International Nuclear Information System (INIS)

Altenburg, Tilman; Engelmeier, Tobias

2013-01-01

In order to avoid irreversible damage to global ecosystems, new ‘green’ technologies are needed, some of which are nowhere near commercial maturity. In these cases, governments may create temporary rents to make investments ‘artificially’ attractive, but the creation of such rents involves risks of faulty allocation and political capture. This article first highlights the importance of managing rents effectively in promoting ‘green’ technologies; it then shows how India's National Solar Mission has been remarkably effective in triggering solar investments and managing the necessary subsidies, e.g. through a process of competitive reverse bidding for tariffs. Policy design and implementation also reflect considerable experimentation and learning. Some risks remain, especially regarding the enforceability of renewable energy quotas at the level of Indian states. - Highlights: • India's National Solar Mission effectively triggered solar investments. • Reverse bidding substantially decreased policy costs. • Sequenced implementation allowed for policy learning. • India's solar policy is a good example of green rent management

The Only Safe SMS Texting Is No SMS Texting.

Science.gov (United States)

Toth, Cheryl; Sacopulos, Michael J

2015-01-01

Many physicians and practice staff use short messaging service (SMS) text messaging to communicate with patients. But SMS text messaging is unencrypted, insecure, and does not meet HIPAA requirements. In addition, the short and abbreviated nature of text messages creates opportunities for misinterpretation, and can negatively impact patient safety and care. Until recently, asking patients to sign a statement that they understand and accept these risks--as well as having policies, device encryption, and cyber insurance in place--would have been enough to mitigate the risk of using SMS text in a medical practice. But new trends and policies have made SMS text messaging unsafe under any circumstance. This article explains these trends and policies, as well as why only secure texting or secure messaging should be used for physician-patient communication.

Exposing the impact of opp(reg)ressive policies on teacher development and on student learning

Science.gov (United States)

Rodriguez, Alberto J.

2010-12-01

This case study draws attention to Pedro's story, a Grade 6 Latino teacher who, along with other grade 4-6 teachers, participated in a three-year professional development research project. By using data analyzed from multiple ethnographic interviews with teachers and students, and by drawing from the quantitative analyzes of concept map unit tests, we illustrate how Pedro's significant professional growth and his students' learning were truncated by top-down school district policies. These policies were implemented because of the punitive nature of the No Child Left Behind Act. Simply put, this case study exposes the impact of opp(reg)ressive policies on learning, that is, policies simultaneously oppressive and regressive. The critical perspective of the project, and its emphasis on assisting teachers to make their pedagogy and curriculum more culturally and socially relevant, was informed by sociotransformative constructivism (sTc). This is a theoretical framework that affords equal importance to cross-cultural education (learning about and acting on socially/culturally relevant issues) and social constructivism (learning to critically produce and consume knowledge). We hope that this case study will provide additional insights into the slow progress we continue to make in science teacher professional development and in closing the achievement gap.

Learning nanotechnology with texts and comics: the impacts on students of different achievement levels

Science.gov (United States)

Lin, Shu-Fen; Lin, Huann-shyang

2016-05-01

Comics are popular with adolescents because of their features of humor, narrative, and visual imagery. The purposes of this study were to examine the learning outcomes and emotional perceptions of reading a science comic book and a science text booklet for students of different levels of achievement, and to explore the main factors of the two media which attract high-school students to learn science. A mixed-method quasi-experimental design was adopted. The participants were 697 grade ten students from eight schools with different levels of academic achievement. Two similar classes in each of the eight schools were assigned as the comic group or the text group. The results indicated that the science comic book benefited medium achievers more than the science text booklet did, but the contrary result was found for the high achievers. In comparison, the two media benefited the low achievers equally, but both had only a limited effect due to the students' lack of prior knowledge. We conclude four kinds of evidence, including perceived difficulty of comprehension, reasons for interest/disinterest, emotional perceptions of learning science, and learning time, to support the phenomenon of the learning benefit of media specific to certain achievers' science learning.

Reading Multimodal Texts for Learning – a Model for Cultivating Multimodal Literacy

Directory of Open Access Journals (Sweden)

Kristina Danielsson

2016-08-01

Full Text Available The re-conceptualisation of texts over the last 20 years, as well as the development of a multimodal understanding of communication and representation of knowledge, has profound consequences for the reading and understanding of multimodal texts, not least in educational contexts. However, if teachers and students are given tools to “unwrap” multimodal texts, they can develop a deeper understanding of texts, information structures, and the textual organisation of knowledge. This article presents a model for working with multimodal texts in education with the intention to highlight mutual multimodal text analysis in relation to the subject content. Examples are taken from a Singaporean science textbook as well as a Chilean science textbook, in order to demonstrate that the framework is versatile and applicable across different cultural contexts. The model takes into account the following aspects of texts: the general structure, how different semiotic resources operate, the ways in which different resources are combined (including coherence, the use of figurative language, and explicit/implicit values. Since learning operates on different dimensions – such as social and affective dimensions besides the cognitive ones – our inclusion of figurative language and values as components for textual analysis is a contribution to multimodal text analysis for learning.

Social learning and public policy: Lessons from an energy-conscious village

International Nuclear Information System (INIS)

Darby, Sarah

2006-01-01

Social learning is a prerequisite for sustainable energy use. This paper sets out some considerations from learning theory that offer a useful way of looking at domestic energy awareness and at actions to improve energy efficiency and conserve energy. Findings from a survey of residents of an English village that had won an 'energy-conscious village' competition are used to illustrate how individual and social learning can occur over a period of time, and how a 'top down' initiative may relate to other more informal sources of motivation and information. A model of learning about domestic energy use that incorporates awareness, action and feedback is proposed, and the implications for policy and further research are discussed

Combining Correlation-Based and Reward-Based Learning in Neural Control for Policy Improvement

DEFF Research Database (Denmark)

Manoonpong, Poramate; Kolodziejski, Christoph; Wörgötter, Florentin

2013-01-01

Classical conditioning (conventionally modeled as correlation-based learning) and operant conditioning (conventionally modeled as reinforcement learning or reward-based learning) have been found in biological systems. Evidence shows that these two mechanisms strongly involve learning about...... associations. Based on these biological findings, we propose a new learning model to achieve successful control policies for artificial systems. This model combines correlation-based learning using input correlation learning (ICO learning) and reward-based learning using continuous actor–critic reinforcement...... learning (RL), thereby working as a dual learner system. The model performance is evaluated by simulations of a cart-pole system as a dynamic motion control problem and a mobile robot system as a goal-directed behavior control problem. Results show that the model can strongly improve pole balancing control...

Policy, Personalities and Pedagogy: The Use of Simulation Games to Teach and Learn about Development Policy

Science.gov (United States)

Prinsen, Gerard; Overton, John

2011-01-01

Simulation games have a long history in education and are well suited to learning about negotiation, power, relationships and uncertain outcomes. This paper reflects on the experience of using a semester-long simulation game to introduce postgraduate students to development policy. It focuses on three issues identified in the literature--realism,…

Time to Engage? Texting to Support and Enhance First Year Undergraduate Learning

Directory of Open Access Journals (Sweden)

Geraldine Jones

2009-04-01

Full Text Available In this paper we discuss a case study investigating how the academic and personal development of first year students on an undergraduate sports education degree can be supported and enhanced with mobile SMS communication. SMS-based technologies were introduced in response to students’ particular needs (in transition to Higher Education and characteristics (‘digital natives’. Despite being unaccustomed to using their mobile phones for academic study, students willingly participated in SMS communication with their tutor via a texting management service. Drawing on evidence from two student surveys, focus groups and a tutor’s journal, we illustrate the potential that mobile SMS communication has to link and establish continuity between face to face teaching sessions and online learning activities in the Virtual Learning Environment (VLE. Many students perceived the SMS communication to have had a positive impact on their management of study time. We link our findings with the existing literature and argue that mobile text based communication has the potential to support the development of time management skills, an important component of self regulatory learning, a skill which has been shown to be key in making a successful transition.

Multimedia Glosses and Their Effect on L2 Text Comprehension and Vocabulary Learning

Directory of Open Access Journals (Sweden)

Iñigo Yanguas

2009-06-01

Full Text Available The present study investigates the effects that different types of multimedia glosses, namely textual, pictorial, and textual + pictorial, have on text comprehension and vocabulary learning when the goal is exclusively comprehension of a computerized text. This study is based on the theoretical framework of attention, which maintains that attention is critical in the acquisition process of an L2 (Robinson, 1995; Schmidt, 1995, 2001; Tomlin and Villa, 1994. Ninety-four participants read a text under one of four gloss conditions while asked to think aloud. This study investigated whether any of the conditions promoted noticing and whether this noticing led to better comprehension of the text and learning of the target vocabulary words. Reading comprehension, recognition, and production measures were utilized in a pre-post test design. Results of quantitative and qualitative analyses of the data gathered showed first that all multimedia gloss groups noticed and recognized significantly more of the target words than the control group. Second, no significant differences were found among any of the groups in production of the target vocabulary items. Finally, regarding comprehension, results showed that the combination gloss group significantly outperformed all other groups. These results confirm that the multimedia glosses under investigation have a different effect on comprehension and vocabulary learning respectively.

Read-Aloud Accommodations, Expository Text, and Adolescents with Learning Disabilities

Science.gov (United States)

Meyer, Nancy K.; Bouck, Emily C.

2017-01-01

Adolescents with learning disabilities in reading have difficulties with reading and understanding difficult gradelevel curricular material. One frequently used method of support is using read-aloud accommodations, which can be live read-alouds or text-to-speech (TTS) read-alouds. A single case alternating treatment design was used to examine the…

Research translation to inform national health policies: learning from multiple perspectives in Uganda

Directory of Open Access Journals (Sweden)

Glass Nancy

2011-03-01

Full Text Available Abstract Background Research and evidence can have an impact on policy and practice, resulting in positive outcomes. However, research translation is a complex, dynamic and non-linear process. Although universities in Africa play a major role in generating research evidence, their strategic approaches to influence health policies and decision making are weak. This study was conducted with the aim of understanding the process of translating research into policy in order to guide the strategic direction of Makerere University College of Health Sciences (MakCHS and similar institutions in their quest to influence health outcomes nationally and globally. Methods A case study approach using 30 in-depth interviews with stakeholders involved in two HIV prevention research project was purposively selected. The study sought to analyze the research-to-policy discourses for the prevention of mother-to-child transmission (PMTCT and safe male circumcision (SMC. The analysis sought to identify entry points, strengths and challenges for research-to-policy processes by interviewing three major groups of stakeholders in Uganda – researchers (8, policy makers (12 and media practitioners (12. Results Among the factors that facilitated PMTCT policy uptake and continued implementation were: shared platforms for learning and decision making among stakeholders, implementation pilots to assess feasibility of intervention, the emerging of agencies to undertake operations research and the high visibility of policy benefits to child survival. In contrast, SMC policy processes were stalled for over two years after the findings of the Uganda study was made public. Among other factors, policy makers demanded additional research to assess implementation feasibility of SMC within ordinary health system context. High level leaders also publicly contested the SMC evidence and the underlying values and messages – a situation that reduced the coalition of policy champions

Why Learning Not Education?--Analysis of Transnational Education Policies in the Age of Globalization

Science.gov (United States)

Mandal, Sayantan

2012-01-01

The profound influence of globalization seems helping outshine the concept of "education" with the more flexible notion of "learning" in the education policies of major transnational organizations. With considerable differences in concepts, all of them are promoting "learning", more specifically LLL (lifelong…

Why Sketching May Aid Learning From Science Texts: Contrasting Sketching With Written Explanations.

Science.gov (United States)

Scheiter, Katharina; Schleinschok, Katrin; Ainsworth, Shaaron

2017-10-01

The goal of this study was to explore two accounts for why sketching during learning from text is helpful: (1) sketching acts like other constructive strategies such as self-explanation because it helps learners to identify relevant information and generate inferences; or (2) that in addition to these general effects, sketching has more specific benefits due to the pictorial representation that is constructed. Seventy-three seventh-graders (32 girls, M = 12.82 years) were first taught how to either create sketches or self-explain while studying science texts. During a subsequent learning phase, all students were asked to read an expository text about the greenhouse effect. Finally, they were asked to write down everything they remembered and then answer transfer questions. Strategy quality during learning was assessed as the number of key concepts that had either been sketched or mentioned in the self-explanations. The results showed that at an overall performance level there were only marginal group differences. However, a more in-depth analysis revealed that whereas no group differences emerged for students implementing either strategy poorly, the sketching group clearly outperformed the self-explanation group for students who applied the strategies with higher quality. Furthermore, higher sketching quality was strongly related to better learning outcomes. Thus, the study's results are more in line with the second account: Sketching can have a beneficial effect on learning above and beyond generating written explanations; at least, if well deployed. Copyright © 2017 Cognitive Science Society, Inc.

Free Education for Open Learning: Open educational policies, strategies & access for all

NARCIS (Netherlands)

Stracke, Christian M.

2016-01-01

Invited Speech at the Moscow International Education Fair 2016, Moscow, Russian Federation, by Stracke, C. M. (2016, 15 April): "Free Education for Open Learning: Open educational policies, strategies & access for all"

PEMIKIRAN TOKOH PENDIDIKAN DALAM BUKU LIFELONG LEARNING: POLICIES, PRACTICES, AND PROGRAMS (Perspektif Peningkatan Mutu Pendidikan di Indonesia

Directory of Open Access Journals (Sweden)

I Ketut Sudarsana

2016-08-01

Full Text Available The substances of the views of the some figures depicted in the Lifelong Learning Policies, Practices, And Programs, especially the ones found on Chapter  11 to 15 mostly describe the relation between the school education, families, and society. They are in accordance with the Indonesian Government Regulation No20/2003 on the national system of Indonesian education that regulate its informal, formal and nonformal sectors. The least attended nonformal one has actually equal charge, namely providing the best education to the society.

Applying Active Learning to Assertion Classification of Concepts in Clinical Text

Science.gov (United States)

Chen, Yukun; Mani, Subramani; Xu, Hua

2012-01-01

Supervised machine learning methods for clinical natural language processing (NLP) research require a large number of annotated samples, which are very expensive to build because of the involvement of physicians. Active learning, an approach that actively samples from a large pool, provides an alternative solution. Its major goal in classification is to reduce the annotation effort while maintaining the quality of the predictive model. However, few studies have investigated its uses in clinical NLP. This paper reports an application of active learning to a clinical text classification task: to determine the assertion status of clinical concepts. The annotated corpus for the assertion classification task in the 2010 i2b2/VA Clinical NLP Challenge was used in this study. We implemented several existing and newly developed active learning algorithms and assessed their uses. The outcome is reported in the global ALC score, based on the Area under the average Learning Curve of the AUC (Area Under the Curve) score. Results showed that when the same number of annotated samples was used, active learning strategies could generate better classification models (best ALC – 0.7715) than the passive learning method (random sampling) (ALC – 0.7411). Moreover, to achieve the same classification performance, active learning strategies required fewer samples than the random sampling method. For example, to achieve an AUC of 0.79, the random sampling method used 32 samples, while our best active learning algorithm required only 12 samples, a reduction of 62.5% in manual annotation effort. PMID:22127105

Impact assessment and policy learning in the European Commission

International Nuclear Information System (INIS)

Ruddy, Thomas F.; Hilty, Lorenz M.

2008-01-01

Governance for sustainable development requires policy coherence and Environmental Policy Integration, which are being hindered by difficulties coordinating the two separate impact assessment processes being conducted in the European Commission. One of them, the Commission-wide Impact Assessment process, looks primarily at EU-internal impacts, whereas the other one, Sustainability Impact Assessment (SIA) in DG Trade, looks outward to other countries and intergovernmental organizations. Ideally, the two processes should complement one another, especially as the two are set to continue being done in parallel. The paper uses a case study of the reform of the European sugar regime under a World Trade Organization ruling to demonstrate how the two impact assessment processes could better complement one another. Feedback from the experience had with existing trade agreements could then promote policy learning and inform the negotiations on new agreements. The number of new bilateral and Regional Trade Agreements is expected to continue rising, thus increasing the importance of the Commission-wide Impact Assessment process required for them

Axiomatic Ontology Learning Approaches for English Translation of the Meaning of Quranic Texts

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Saad Saidah

2017-01-01

Full Text Available Ontology learning (OL is the computational task of generating a knowledge base in the form of an ontology, given an unstructured corpus in natural language (NL. While most works in the field of ontology learning have been primarily based on a statistical approach to extract lightweight OL, very few attempts have been made to extract axiomatic OL (called heavyweight OL from NL text documents. Axiomatic OL supports more precise formal logic-based reasoning when compared to lightweight OL. Lexico-syntactic pattern matching and statisticsal one cannot lead to very accurate learning, mostly because of several linguistic nuances in the NL. Axiomatic OL is an alternative methodology that has not been explored much, where a deep linguistics analysis in computational linguistics is used to generate formal axioms and definitions instead of simply inducing a taxonomy. The ontology that is created not only stores the information about the application domain in explicit knowledge, but also can deduce the implicit knowledge from this ontology. This research will explore the English translation of the meaning of Quranic texts.

NetiNeti: discovery of scientific names from text using machine learning methods

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Akella Lakshmi

2012-08-01

Full Text Available Abstract Background A scientific name for an organism can be associated with almost all biological data. Name identification is an important step in many text mining tasks aiming to extract useful information from biological, biomedical and biodiversity text sources. A scientific name acts as an important metadata element to link biological information. Results We present NetiNeti (Name Extraction from Textual Information-Name Extraction for Taxonomic Indexing, a machine learning based approach for recognition of scientific names including the discovery of new species names from text that will also handle misspellings, OCR errors and other variations in names. The system generates candidate names using rules for scientific names and applies probabilistic machine learning methods to classify names based on structural features of candidate names and features derived from their contexts. NetiNeti can also disambiguate scientific names from other names using the contextual information. We evaluated NetiNeti on legacy biodiversity texts and biomedical literature (MEDLINE. NetiNeti performs better (precision = 98.9% and recall = 70.5% compared to a popular dictionary based approach (precision = 97.5% and recall = 54.3% on a 600-page biodiversity book that was manually marked by an annotator. On a small set of PubMed Central’s full text articles annotated with scientific names, the precision and recall values are 98.5% and 96.2% respectively. NetiNeti found more than 190,000 unique binomial and trinomial names in more than 1,880,000 PubMed records when used on the full MEDLINE database. NetiNeti also successfully identifies almost all of the new species names mentioned within web pages. Conclusions We present NetiNeti, a machine learning based approach for identification and discovery of scientific names. The system implementing the approach can be accessed at http://namefinding.ubio.org.

Policies for Industrial Learning in China and Mexico

OpenAIRE

Kevin P. Gallagher; Mehdi Shafaeddin

2009-01-01

Previous work has shown that the results of both China and Mexicos export-led market reforms over the past quarter century have been strikingly different. In contrast to China, Mexico has not managed to increase the value added of its exports of manufactured goods and has subsequently had a difficult time competing with China in world markets. Building on this previous work, in this paper we conduct a comparative analysis of the role of government policies in industrial learning and the devel...

Self-Regulated Learning from Illustrated Text: Eye Movement Modelling to Support Use and Regulation of Cognitive Processes during Learning from Multimedia

Science.gov (United States)

Scheiter, Katharina; Schubert, Carina; Schüler, Anne

2018-01-01

Background: When learning with text and pictures, learners often fail to adequately process the materials, which can be explained as a failure to self-regulate one's learning by choosing adequate cognitive learning processes. Eye movement modelling examples (EMME) showing how to process multimedia instruction have improved elementary school…

Cognitive diffusion model with user-oriented context-to-text recognition for learning to promote high level cognitive processes

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Wu-Yuin Hwang

2014-03-01

Full Text Available There is a large number of studies on how to promote students’ cognitive processes and learning achievements through various learning activities supported by advanced learning technologies. However, not many of them focus on applying the knowledge that students learn in school to solve authentic daily life problems. This study aims to propose a cognitive diffusion model called User-oriented Context-to-Text Recognition for Learning (U-CTRL to facilitate and improve students’ learning and cognitive processes from lower levels (i.e., Remember and Understand to higher levels (i.e., Apply and above through an innovative approach, called User-Oriented Context-to-Text Recognition for Learning (U-CTRL. With U-CTRL, students participate in learning activities in which they capture the learning context that can be scanned and recognized by a computer application as text. Furthermore, this study proposes the use of an innovative model, called Cognitive Diffusion Model, to investigate the diffusion and transition of students’ cognitive processes in different learning stages including pre-schooling, after-schooling, crossing the chasm, and higher cognitive processing. Finally, two cases are presented to demonstrate how the U-CTRL approach can be used to facilitate student cognition in their learning of English and Natural science.

From Policy to Guidelines: Metamorphosis of Lifelong Learning in India

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Mandal, Sayantan

2013-01-01

In this era of globalisation, the present perception of lifelong learning (LLL) in the Indian policy domain has been going through major changes in an attempt to make it nationally realistic yet globally viable. In this process, all facets of the concept of LLL are constantly metamorphosing, and this in many ways outperforms the older perception…

Public and state responses to high-level nuclear waste disposal: Learning from policy failure

International Nuclear Information System (INIS)

Kraft, M.E.

1991-01-01

Nuclear waste policy in the United States has faded in large part because of public and state opposition to repository siting. However, that outcome was not inevitable. This paper argues that better policy design and greater attention to the crucial tasks of policy legitimation both by the U.S. Congress and by the Department of Energy might have significantly increased the chances for successful implementation. Even though the program now has a highly uncertain future, suggestions are offered for policy learning and change that may increase the probability of success

Lifelong Learning Policy for the Elderly People: A Comparative Experience between Japan and Thailand

Science.gov (United States)

Dhirathiti, Nopraenue

2014-01-01

This study examined and compared the legal inputs, structural settings and implementation process of lifelong learning policy in Thailand and Japan focusing on street-level agents. The findings demonstrated that while both countries had legal frameworks that provided a legislative platform to promote lifelong learning among the elderly based on a…

Teacher Verbal Aggressiveness and Credibility Mediate the Relationship between Teacher Technology Policies and Perceived Student Learning

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Finn, Amber N.; Ledbetter, Andrew M.

2014-01-01

In this study, we extend previous work on teacher technology policies by refining the teacher technology policies instrument to account for the technology purpose (social, academic) and type (cell phone, laptop/tablet), and examine a model of teacher technology policies and perceived learning. We found that students are more sensitive to policies…

Deep Learning to Classify Radiology Free-Text Reports.

Science.gov (United States)

Chen, Matthew C; Ball, Robyn L; Yang, Lingyao; Moradzadeh, Nathaniel; Chapman, Brian E; Larson, David B; Langlotz, Curtis P; Amrhein, Timothy J; Lungren, Matthew P

2018-03-01

Purpose To evaluate the performance of a deep learning convolutional neural network (CNN) model compared with a traditional natural language processing (NLP) model in extracting pulmonary embolism (PE) findings from thoracic computed tomography (CT) reports from two institutions. Materials and Methods Contrast material-enhanced CT examinations of the chest performed between January 1, 1998, and January 1, 2016, were selected. Annotations by two human radiologists were made for three categories: the presence, chronicity, and location of PE. Classification of performance of a CNN model with an unsupervised learning algorithm for obtaining vector representations of words was compared with the open-source application PeFinder. Sensitivity, specificity, accuracy, and F1 scores for both the CNN model and PeFinder in the internal and external validation sets were determined. Results The CNN model demonstrated an accuracy of 99% and an area under the curve value of 0.97. For internal validation report data, the CNN model had a statistically significant larger F1 score (0.938) than did PeFinder (0.867) when classifying findings as either PE positive or PE negative, but no significant difference in sensitivity, specificity, or accuracy was found. For external validation report data, no statistical difference between the performance of the CNN model and PeFinder was found. Conclusion A deep learning CNN model can classify radiology free-text reports with accuracy equivalent to or beyond that of an existing traditional NLP model. © RSNA, 2017 Online supplemental material is available for this article.

Improving Students' Science Text Comprehension through Metacognitive Self-Regulation When Applying Learning Strategies

Science.gov (United States)

Leopold, Claudia; Leutner, Detlev

2015-01-01

In three experiments, students were trained to use strategies for learning from scientific texts: text highlighting (Experiment 1), knowledge mapping (Experiment 2), and visualizing (Experiment 3). Each experiment compared a control condition, cognitive strategy training, and a combined cognitive strategy plus metacognitive self-regulation…

Balancing Tensions in Educational Policy Reforms: Large-Scale Implementation of Assessment for Learning in Norway

Science.gov (United States)

Hopfenbeck, Therese N.; Flórez Petour, María Teresa; Tolo, Astrid

2015-01-01

This study investigates how different stakeholders in Norway experienced a government-initiated, large-scale policy implementation programme on "Assessment for Learning" ("AfL"). Data were collected through 58 interviews with stakeholders in charge of the policy; Ministers of Education and members of the Directorate of…

Next step in policy transitions: Diffusion of pilot projects

CSIR Research Space (South Africa)

Vreugdenhil, H

2009-04-01

Full Text Available communication across actors and domains, to set the agenda and to streamline resources (Pahl-Wostl, 2006, Pawson and Tilley, 1997). Social and policy learning are realized within the pilot projects. Social learning as one outcome of pilot project.... These ask for new approaches that are first to be tested on a small scale to prevent larger policy flaws and second, are designed to allow the system for remaining adaptable (Pahl-Wostl, 2006; Pawson and Tilley, 1997). Despite these promising...

Optimal monetary policy rules: the problem of stability under heterogeneous learning

Czech Academy of Sciences Publication Activity Database

Bogomolova, Anna; Kolyuzhnov, Dmitri

-, č. 379 (2008), s. 1-34 ISSN 1211-3298 R&D Projects: GA MŠk LC542 Institutional research plan: CEZ:AV0Z70850503 Keywords : monetary policy rules * New Keynesian model * adaptive learning Subject RIV: AH - Economics http://www.cerge-ei.cz/pdf/wp/Wp379.pdf

Effects of Picture Labeling on Science Text Processing and Learning: Evidence from Eye Movements

Science.gov (United States)

Mason, Lucia; Pluchino, Patrik; Tornatora, Maria Caterina

2013-01-01

This study investigated the effects of reading a science text illustrated by either a labeled or unlabeled picture. Both the online process of reading the text and the offline conceptual learning from the text were examined. Eye-tracking methodology was used to trace text and picture processing through indexes of first- and second-pass reading or…

A Text Mining Approach for Extracting Lessons Learned from Project Documentation: An Illustrative Case Study

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Benjamin Matthies

2017-12-01

Full Text Available Lessons learned are important building blocks for continuous learning in project-based organisations. Nonetheless, the practical reality is that lessons learned are often not consistently reused for organisational learning. Two problems are commonly described in this context: the information overload and the lack of procedures and methods for the assessment and implementation of lessons learned. This paper addresses these problems, and appropriate solutions are combined in a systematic lesson learned process. Latent Dirichlet Allocation is presented to solve the first problem. Regarding the second problem, established risk management methods are adapted. The entire lessons learned process will be demonstrated in a practical case study

Monetary Policy Rules, Learning and Stability: a Survey of the Recent Literature (In French)

OpenAIRE

Martin ZUMPE (GREThA UMR CNRS 5113)

2010-01-01

This paper presents the literature about econometric learning and its impact on the performances of monetary policy rules in the framework of the new canonical macroeconomic model. Rational expectations which are a building block of the original model can thus be replaced by expectations based on estimation algorithms. The permanent updating of these estimations can be interpreted as a learning proces of the model’s agents. This learning proces induces additional dynamics into the model. The ...

The learning potential of photovoltaics: implications for energy policy

International Nuclear Information System (INIS)

Zwaan, Bob van der; Rabl, Ari

2004-01-01

This article examines the prospects for cost reductions of flat panel photovoltaic (PV) electricity. Current PV production cost ranges are presented, in terms of cost per peak W and cost per kWh, for single crystalline and multi-crystalline silicon, as well as for thin-film technologies. Possible decreases of these costs are assessed, as expected based on learning curves. The cumulative production needed to reach 'breakeven' (at which PV is competitive with conventional alternatives) is estimated for a range of values of the learning curve parameter. The cost of this cumulative production is calculated, and the question is posed whether and how the 'cost cap' can be bridged, the latter being the difference between what this cumulative production will cost and what it would cost if it could be produced at a currently competitive level. We also estimate how much PV could gain if external costs (due to environmental and health damage) of energy were internalised, for example by an energy tax. The conclusions are: (1) mainly due its high costs, PV electricity is unlikely to play a major role in global energy supply and carbon emissions abatement before 2020, (2) extrapolating past learning curves, one can expect its costs to decrease significantly, so that a considerable PV electricity share world-wide could materialise after 2020, (3) niche-market applications, e.g. using stand-alone systems in remote areas, are crucial for continuing 'the ride along the learning curve', (4) damage costs of conventional (fossil) power sources are considerable, and they could provide an important part of the rationale behind major policy efforts to encourage increased use of PV. The costs involved with such policies would be elevated, but a considerable share of these costs could be justified by the fact that conventional power damage costs constitute a significant fraction of the cost gap, although probably not enough to close it

From "Learning Disability to Intellectual Disability"--Perceptions of the Increasing Use of the Term "Intellectual Disability" in Learning Disability Policy, Research and Practice

Science.gov (United States)

Cluley, Victoria

2018-01-01

Background: The term "intellectual disability" is increasingly used to refer to people with learning disabilities in British learning disability policy, practice and research. This change is undoubtedly a reflection of the changing international context. The inclusion of the term "intellectual disability" has been particularly…

From Policies to Implementation of Open Distance Learning in Rwanda: A Genealogical and Governmentality Analysis

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Mukama, Evode

2018-01-01

The purpose of this paper is to analyse the interplay between policy formulation and implementation in terms of the historical practices of open distance learning (ODL) in Rwanda. This paper draws on the Foucauldian genealogical and governmentality analysis. The paper examines government aspirations as depicted in policy statements starting from…

On Health Policy and Management (HPAM: Mind the Theory-Policy-Practice Gap

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David Chinitz

2014-12-01

Full Text Available We argue that the field of Health Policy and Management (HPAM ought to confront the gap between theory, policy, and practice. Although there are perennial efforts to reform healthcare systems, the conceptual barriers are considerable and reflect the theory-policy-practice gap. We highlight four dimensions of the gap: 1 the dominance of microeconomic thinking in health policy analysis and design; 2 the lack of learning from management theory and comparative case studies; 3 the separation of HPAM from the rank and file of healthcare; and 4 the failure to expose medical students to issues of HPAM. We conclude with suggestions for rethinking the field of HPAM by embracing broader perspectives, e.g. ethics, urban health, systems analysis and cross-national analyses of healthcare systems.

An Eye-Tracking Study of Learning from Science Text with Concrete and Abstract Illustrations

Science.gov (United States)

Mason, Lucia; Pluchino, Patrik; Tornatora, Maria Caterina; Ariasi, Nicola

2013-01-01

This study investigated the online process of reading and the offline learning from an illustrated science text. The authors examined the effects of using a concrete or abstract picture to illustrate a text and adopted eye-tracking methodology to trace text and picture processing. They randomly assigned 59 eleventh-grade students to 3 reading…

Decoding ClassDojo: Psycho-Policy, Social-Emotional Learning and Persuasive Educational Technologies

Science.gov (United States)

Williamson, Ben

2017-01-01

ClassDojo is one of the world's most successful educational technologies, currently used by over 3 million teachers and 35 million children globally. It reinforces and enacts emerging governmental "psycho-policies" around the measurement and modification of children's social and emotional learning in schools. This article focuses…

Learning Disabilities: Current Policy and Directions for Community Involvement among the Arab Community in Israel

Science.gov (United States)

Jabareen-Taha, Samaher; Taha, Haitham

2016-01-01

This article seeks to identify and review the basic characteristics of learning disability which are specifically mentioned in the literature. In addition, the article intends to conduct a brief analysis on learning disability policy in Israel and the differentiation problems at the level of awareness among the Arab society in Israel. Despite the…

DEEP LEARNING MODEL FOR BILINGUAL SENTIMENT CLASSIFICATION OF SHORT TEXTS

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Y. B. Abdullin

2017-01-01

Full Text Available Sentiment analysis of short texts such as Twitter messages and comments in news portals is challenging due to the lack of contextual information. We propose a deep neural network model that uses bilingual word embeddings to effectively solve sentiment classification problem for a given pair of languages. We apply our approach to two corpora of two different language pairs: English-Russian and Russian-Kazakh. We show how to train a classifier in one language and predict in another. Our approach achieves 73% accuracy for English and 74% accuracy for Russian. For Kazakh sentiment analysis, we propose a baseline method, that achieves 60% accuracy; and a method to learn bilingual embeddings from a large unlabeled corpus using a bilingual word pairs.

Lifelong Learning Policy Agenda in the European Union: A Bi-Level Analysis

Science.gov (United States)

Panitsides, Eugenia A.; Anastasiadou, Sofia

2015-01-01

The Lisbon European Summit in 2000 has been a milestone in reframing education policies to foster a "knowledge economy", whilst amid the challenges of the new decennium Lifelong Learning (LLL) has been propounded as a powerful lever for attaining "sustainable growth". The present article aims to elucidate the development of an…

Sustainability indicator system and policy processes in Malaysia: a framework for utilisation and learning.

Science.gov (United States)

Hezri, A A

2004-12-01

Formulation of effective sustainability indicators for national assessment demands a comprehensive understanding of the utilisation, diffusion and dissemination of information in policy processes. To illustrate the dynamic of sustainability assessment within the context of policy processes, this paper uses a case study of national sustainability indicators development in Malaysia. Subsequently, this paper ascribes the limited achievement of national sustainability assessment in Malaysia to four types of constraints: meta-policy issues; technical capacities; communication concerns; and the inherent knowledge gaps within the indicator developer community vis-a-vis their theoretical limitations. It is proposed that such constraints will be encountered in many countries. Drawing from the literature on public policy, this paper outlines a framework for investigating indicator behaviour within policy processes based on well-established concepts such as knowledge utilisation and policy learning. I conclude this paper by elaborating on the corresponding future challenges that must be addressed before effective integration of sustainability indicators within policy systems can occur.

Democratic population decisions result in robust policy-gradient learning: a parametric study with GPU simulations.

Directory of Open Access Journals (Sweden)

Paul Richmond

2011-05-01

Full Text Available High performance computing on the Graphics Processing Unit (GPU is an emerging field driven by the promise of high computational power at a low cost. However, GPU programming is a non-trivial task and moreover architectural limitations raise the question of whether investing effort in this direction may be worthwhile. In this work, we use GPU programming to simulate a two-layer network of Integrate-and-Fire neurons with varying degrees of recurrent connectivity and investigate its ability to learn a simplified navigation task using a policy-gradient learning rule stemming from Reinforcement Learning. The purpose of this paper is twofold. First, we want to support the use of GPUs in the field of Computational Neuroscience. Second, using GPU computing power, we investigate the conditions under which the said architecture and learning rule demonstrate best performance. Our work indicates that networks featuring strong Mexican-Hat-shaped recurrent connections in the top layer, where decision making is governed by the formation of a stable activity bump in the neural population (a "non-democratic" mechanism, achieve mediocre learning results at best. In absence of recurrent connections, where all neurons "vote" independently ("democratic" for a decision via population vector readout, the task is generally learned better and more robustly. Our study would have been extremely difficult on a desktop computer without the use of GPU programming. We present the routines developed for this purpose and show that a speed improvement of 5x up to 42x is provided versus optimised Python code. The higher speed is achieved when we exploit the parallelism of the GPU in the search of learning parameters. This suggests that efficient GPU programming can significantly reduce the time needed for simulating networks of spiking neurons, particularly when multiple parameter configurations are investigated.

Two-way text messaging: an interactive mobile learning environment in higher education

OpenAIRE

Premadasa, H. K. Salinda; Meegama, R. G. N.

2016-01-01

Short messaging service (SMS) is perhaps the most popular mobile technology prevalent among students in higher education due to its ubiquitous nature and the capability of two-way communication. However, a major limitation in two-way text messaging is sending back a part of received data with the reply message. This limitation results in users of a mobile learning environment being unable to reply back to the correct destination. This article presents a two-way text messaging system that can ...

Policies on and Practices of Cultural Inclusivity in Learning Management Systems: Perspectives of Indigenous Holistic Pedagogies

Science.gov (United States)

Dreamson, Neal; Thomas, Gary; Lee Hong, Anita; Kim, Soyoung

2017-01-01

Online learning has become a conventional term and practice in Australian higher education, yet cultural inclusivity for Indigenous (Indigenous for the purposes of this paper refers to Australian Aboriginal and Torres Strait Islander peoples) students is insufficiently reflected in learning management system (LMS) policies and design. This study…

Exploring the Effects of Multimedia Learning on Pre-Service Teachers' Perceived and Actual Learning Performance: The Use of Embedded Summarized Texts in Educational Media

Science.gov (United States)

Wu, Leon Yufeng; Yamanaka, Akio

2013-01-01

In light of the increased usage of instructional media for teaching and learning, the design of these media as aids to convey the content for learning can be crucial for effective learning outcomes. In this vein, the literature has given attention to how concurrent on-screen text can be designed using these media to enhance learning performance.…

How do students navigate and learn from nonlinear science texts: Can metanavigation support promote science learning?

Science.gov (United States)

Stylianou, Agni

2003-06-01

Digital texts which are based on hypertext and hypermedia technologies are now being used to support science learning. Hypertext offers certain opportunities for learning as well as difficulties that challenge readers to become metacognitively aware of their navigation decisions in order to trade both meaning and structure while reading. The goal of this study was to investigate whether supporting sixth grade students to monitor and regulate their navigation behavior while reading from hypertext would lead to better navigation and learning. Metanavigation support in the form of prompts was provided to groups of students who used a hypertext system called CoMPASS to complete a design challenge. The metanavigation prompts aimed at encouraging students to understand the affordances of the navigational aids in CoMPASS and use them to guide their navigation. The study was conducted in a real classroom setting during the implementation of CoMPASS in sixth grade science classes. Multiple sources of group and individual data were collected and analyzed. Measures included student's individual performance in a pre-science knowledge test, the Metacognitive Awareness of Reading Strategies Inventory (MARSI), a reading comprehension test and a concept map test. Process measures included log file information that captured group navigation paths during the use of CoMPASS. The results suggested that providing metanavigation support enabled the groups to make coherent transitions among the text units. Findings also revealed that reading comprehension, presence of metanavigation support and prior domain knowledge significantly predicted students' individual understanding of science. Implications for hypertext design and literacy research fields are discussed.

Learning Multirobot Hose Transportation and Deployment by Distributed Round-Robin Q-Learning.

Directory of Open Access Journals (Sweden)

Borja Fernandez-Gauna

Full Text Available Multi-Agent Reinforcement Learning (MARL algorithms face two main difficulties: the curse of dimensionality, and environment non-stationarity due to the independent learning processes carried out by the agents concurrently. In this paper we formalize and prove the convergence of a Distributed Round Robin Q-learning (D-RR-QL algorithm for cooperative systems. The computational complexity of this algorithm increases linearly with the number of agents. Moreover, it eliminates environment non sta tionarity by carrying a round-robin scheduling of the action selection and execution. That this learning scheme allows the implementation of Modular State-Action Vetoes (MSAV in cooperative multi-agent systems, which speeds up learning convergence in over-constrained systems by vetoing state-action pairs which lead to undesired termination states (UTS in the relevant state-action subspace. Each agent's local state-action value function learning is an independent process, including the MSAV policies. Coordination of locally optimal policies to obtain the global optimal joint policy is achieved by a greedy selection procedure using message passing. We show that D-RR-QL improves over state-of-the-art approaches, such as Distributed Q-Learning, Team Q-Learning and Coordinated Reinforcement Learning in a paradigmatic Linked Multi-Component Robotic System (L-MCRS control problem: the hose transportation task. L-MCRS are over-constrained systems with many UTS induced by the interaction of the passive linking element and the active mobile robots.

Trends of E-Learning Research from 2000 to 2008: Use of Text Mining and Bibliometrics

Science.gov (United States)

Hung, Jui-long

2012-01-01

This study investigated the longitudinal trends of e-learning research using text mining techniques. Six hundred and eighty-nine (689) refereed journal articles and proceedings were retrieved from the Science Citation Index/Social Science Citation Index database in the period from 2000 to 2008. All e-learning publications were grouped into two…

The EC Discourse on Vocational Training: How a "Common Vocational Training Policy" Turned into a Lifelong Learning Strategy

Science.gov (United States)

Cort, Pia

2009-01-01

This article traces the EC vocational training policy historically and describes the discursive alignments which brought the policy from a "common vocational training policy" as laid down in Article 128, in the Treaty of Rome to the Lisbon Lifelong Learning strategy. The argument is that vocational training has served as a lever for the…

Europeanization in VET Policy as a Process of Reshaping the Educational Space

Directory of Open Access Journals (Sweden)

Krista Loogma

2016-04-01

Full Text Available The EU represents a transforming educational space, where national and supranational boundaries in educational governance are becoming blurred. The EU has become an  important actor in educational governance and an important arena for policy learning and transfer. This paper explores how the process of reshaping the educational space manifests itself in the process of the Europeanization of VET policy in the case of Estonia. In Estonia, this process was followed by the growth of executive VET institutions and has developed from rather uncritical initial policy transfer to more active learning from the EU, although conformism can still be seen in cases of the introduction of standardizing policy tools.

English for University Administrative Work: English Officialization Policy and Foreign Language Learning Motivation

Science.gov (United States)

Kim, Jeongyeon; Choi, Jinsook

2014-01-01

This study examines how the English officialization policy of higher education in an EFL context interplays with administrative workers' motivational orientations towards English learning. The data consisted of questionnaire responses of 117 administrative members with undergraduate degrees and qualitative interviews with 9 who answered the…

Evaluating mobile-centric readiness of higher education institutions: the case of institutional policies and information systems students

CSIR Research Space (South Africa)

Chipangura, B

2015-12-01

Full Text Available . To investigate this question from a policy perspective, nine policies from the open and distance learning (ODL) university in South Africa were analysed for providing institutional mobile-centric support. Policy document analysis was used to evaluate five...

Climate policies and learning by doing: Impacts and timing of technology subsidies

International Nuclear Information System (INIS)

Kverndokk, Snorre; Rosendahl, Knut Einar

2007-01-01

We study the role of technology subsidies in climate policies, using a simple dynamic equilibrium model with learning by doing. The optimal subsidy rate of a carbon-free technology is high when the technology is first adopted, but falls significantly over the next decades. However, the efficiency costs of uniform instead of optimal subsidies, may be low if there are adjustment costs for a new technology. Finally, supporting existing energy technologies only, may lead to technology lock-in, and the impacts of lock-in increase with the learning potential of new technologies as well as the possibilities for early entry. (author)

Crossing the Chasm – Introducing Flexible Learning into the Botswana Technical Education Programme: From Policy to Action

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Alison Mead Richardson

2009-09-01

Full Text Available This paper reports on a longitudinal, ethnomethodological case study of the development towards flexible delivery of the Botswana Technical Education Programme (BTEP, offered by Francistown College of Technical & Vocational Education (FCTVE. Data collection methods included documentary analysis, naturalistic participant observation, and semi-structured interviews. The author identifies and analyses the technical, staffing, and cultural barriers to change when introducing technology-enhanced, flexible delivery methods. The study recommends that strategies to advance flexible learning should focus on the following goals: establish flexible policy and administration systems, change how staff utilization is calculated when flexible learning methodologies are used, embed flexible delivery in individual performance development and department/college strategic plans, ensure managerial leadership, hire and support permanent specialists, identify champions and share success stories, and address issues of inflexible organisational culture. This study may be of value in developing countries where mass-based models are sought to expand access to vocational education and training.

Effects of image-based and text-based active learning exercises on student examination performance in a musculoskeletal anatomy course.

Science.gov (United States)

Gross, M Melissa; Wright, Mary C; Anderson, Olivia S

2017-09-01

Research on the benefits of visual learning has relied primarily on lecture-based pedagogy, but the potential benefits of combining active learning strategies with visual and verbal materials on learning anatomy has not yet been explored. In this study, the differential effects of text-based and image-based active learning exercises on examination performance were investigated in a functional anatomy course. Each class session was punctuated with an average of 12 text-based and image-based active learning exercises. Participation data from 231 students were compared with their examination performance on 262 questions associated with the in-class exercises. Students also rated the helpfulness and difficulty of the in-class exercises on a survey. Participation in the active learning exercises was positively correlated with examination performance (r = 0.63, P active learning exercises were helpful for seeing images of key ideas (94%) and clarifying key course concepts (80%), and that the image-based exercises were significantly less demanding, less hard and required less effort than text-based exercises (P active learning strategies on student learning, and suggest that integrating them may be especially beneficial for learning anatomy. Anat Sci Educ 10: 444-455. © 2017 American Association of Anatomists. © 2017 American Association of Anatomists.

Effects of Text Illustration on Children's Learning of a School Science Topic.

Science.gov (United States)

Reid, D. J.; Beveridge, M.

1986-01-01

This study of 272 13-year-old science students in England focuses on the effect of varied text and picture content on learning. A criterion-referenced objective items test was used to measure the effect of pictures on students of varying abilities and compare the effectiveness of traditional worksheet presentation and microcomputer presentation.…

Using supervised machine learning to code policy issues: Can classifiers generalize across contexts?

NARCIS (Netherlands)

Burscher, B.; Vliegenthart, R.; de Vreese, C.H.

2015-01-01

Content analysis of political communication usually covers large amounts of material and makes the study of dynamics in issue salience a costly enterprise. In this article, we present a supervised machine learning approach for the automatic coding of policy issues, which we apply to news articles

Summary of State Policy on Online Learning. White Paper. Version 1.0

Science.gov (United States)

Kim, Kellie; Schiller, Ellen; Meinders, Dona; Nadkarni, Swati; Bull, Bruce; Crain, Danielle; Huennekens, Bill; O'Hara, Nancy; Thacker, Christopher

2015-01-01

This white paper provides a snapshot of available policies and guidance related to online learning and students with disabilities from a small group of states that require online experience as part of high school graduation or report a higher number of online course enrollments. The Appendix allows for a quick scan of the following 12 elements…

Rollout sampling approximate policy iteration

NARCIS (Netherlands)

Dimitrakakis, C.; Lagoudakis, M.G.

2008-01-01

Several researchers have recently investigated the connection between reinforcement learning and classification. We are motivated by proposals of approximate policy iteration schemes without value functions, which focus on policy representation using classifiers and address policy learning as a

Learning to Queer Text: Epiphanies from a Family Critical Literacy Practice

Science.gov (United States)

McClung, Nicola A.

2018-01-01

Critical literacy provides the opportunity to queer picture books and challenge normative depictions of family. In this autoethnography, the author describes her 4-year-old's journey of learning to talk back to texts as she actively constructs a better, more just world. The author argues that a critical literacy tool kit is vital to every child's…

Using Machine Learning for Sentiment and Social Influence Analysis in Text

OpenAIRE

Kolog, Emmanuel Awuni; Montero, Calkin Suero; Toivonen, Tapani

2017-01-01

Students’ academic achievement is largely driven by their social phenomena, which is shaped by social influence and opinion dynamics. In this paper, we employed a machine learning technique to detect social influence and sentiment in text-based students’ life stories. The life stories were first pre-processed and clustered using k-means with euclidean distance. After that, we identified domestic, peer and school staff as the main influences on students’ academic development. The various influ...

Adversarial Advantage Actor-Critic Model for Task-Completion Dialogue Policy Learning

OpenAIRE

Peng, Baolin; Li, Xiujun; Gao, Jianfeng; Liu, Jingjing; Chen, Yun-Nung; Wong, Kam-Fai

2017-01-01

This paper presents a new method --- adversarial advantage actor-critic (Adversarial A2C), which significantly improves the efficiency of dialogue policy learning in task-completion dialogue systems. Inspired by generative adversarial networks (GAN), we train a discriminator to differentiate responses/actions generated by dialogue agents from responses/actions by experts. Then, we incorporate the discriminator as another critic into the advantage actor-critic (A2C) framework, to encourage the...

Applying reinforcement learning to the weapon assignment problem in air defence

CSIR Research Space (South Africa)

Mouton, H

2011-12-01

Full Text Available . The techniques investigated in this article were two methods from the machine-learning subfield of reinforcement learning (RL), namely a Monte Carlo (MC) control algorithm with exploring starts (MCES), and an off-policy temporal-difference (TD) learning...

Keeping Pace with K-12 Digital Learning: An Annual Review of Policy and Practice. Eleventh Edition

Science.gov (United States)

Watson, John; Pape, Larry; Murin, Amy; Gemin, Butch; Vashaw, Lauren

2014-01-01

"Keeping Pace with K-12 Digital Learning" (2014) is the 11th in a series of annual reports that began in 2004 that examine the status of K-12 online education across the country. The report provides an overview of the latest policies, practices, and trends affecting online learning programs across all 50 states. It summarizes that at a…

Policy learning for flood mitigation: a longitudinal assessment of the community rating system in Florida.

Science.gov (United States)

Brody, Samuel D; Zahran, Sammy; Highfield, Wesley E; Bernhardt, Sarah P; Vedlitz, Arnold

2009-06-01

Floods continue to inflict the most damage upon human communities among all natural hazards in the United States. Because localized flooding tends to be spatially repetitive over time, local decisionmakers often have an opportunity to learn from previous events and make proactive policy adjustments to reduce the adverse effects of a subsequent storm. Despite the importance of understanding the degree to which local jurisdictions learn from flood risks and under what circumstances, little if any empirical, longitudinal research has been conducted along these lines. This article addresses the research gap by examining the change in local flood mitigation policies in Florida from 1999 to 2005. We track 18 different mitigation activities organized into four series of activities under the Federal Emergency Management Agency's (FEMA) Community Rating System (CRS) for every local jurisdiction in Florida participating in the FEMA program on a yearly time step. We then identify the major factors contributing to policy changes based on CRS scores over the seven-year study period. Using multivariate statistical models to analyze both natural and social science data, we isolate the effects of several variables categorized into the following groups: hydrologic conditions, flood disaster history, socioeconomic and human capital controls. Results indicate that local jurisdictions do in fact learn from histories of flood risk and this process is expedited under specific conditions.

From lifelong education to lifelong learning Discussion of some effects of today's neoliberal policies

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Rosanna Barros

2012-10-01

Full Text Available When we think about current adult education in the context of the uneven and contradictory social and economic mpact of globalization, it necessarily implies thinking about the transfer from the paradigm of lifelong education to the paradigm of lifelong learning. We shall examine the essential quality involved in the social significance and the political dimension of each of these paradigms, because, since the post-war period, both became innovative educational policy strategies capable of mobilizing and transforming society. We would like to stress the importance of rethinking the role of adult education today in the light of the responsibilities shifting from the state to individuals, arising from the implications of this transition of paradigms: we do this by framing it in the context of the socio-productive restructuring movement, which speeded up the move from the so-called model of qualification, associated to social emancipation, to what is known as the model of competence (later competences, which is associated with individual empowerment. Therefore in this article we intend to question this new policy direction, which is associated with a conceptual and methodological shift in adult education practices, by using the prism of a critical sociology of education.

The 3R study strategy to improve text retention and text comprehension

NARCIS (Netherlands)

Reijners, Pauline; Kester, Liesbeth; Wetzels, Sandra; Kirschner, Paul A.

2013-01-01

Reijners, P. B. G., Kester, L., Wetzels, S. A. J., & Kirschner, P. A. (2013, 27 August). The 3R study strategy to improve text retention and text comprehension. In B. Klein (Chair), Effective Learning Strategies and their Usage in Self-regulated Training Programs and Computer-Based Learning.

Healthy kids: Making school health policy a participatory learning process

DEFF Research Database (Denmark)

Stjernqvist, Nanna Wurr; Bruselius-Jensen, Maria; Høstgaard Bonde, Ane

enjoyed having a voice in school matters and to deal with real life during health education. Teachers were very positive towards the integration of school health policy work into teaching the curriculum in Danish, Maths and Biology. However, the transferring from the classroom to the organizational levels....... Methods The presented model works at two levels - the classroom and the organizational level – and is based on four phases, namely: Investigation – Vision – Action – Change, viewed as an iterative process. Pupil perspectives and learning is the basis in all four phases based on a set of health education...... was weakhindering sustainable health changes. Conclusion Findings indicate that integrating school policy processes into the teaching of curriculum might pave the way for schools to engage in health promotion. But further knowledge on how to likewise engage the staff on an organisational level is needed....

Investigating the Use of Text Messages in Mobile Learning

Science.gov (United States)

Geng, Gretchen

2013-01-01

Nowadays, teaching and learning have been shifted from traditional classrooms to technology-supported learning environment. By offering a convenient, efficient and financially affordable information technology learning environment, mobile learning is a topic that is of considerable interest for education audiences owing to the pervasive nature of…

Improving learning with science and social studies text using computer-based concept maps for students with disabilities.

Science.gov (United States)

Ciullo, Stephen; Falcomata, Terry S; Pfannenstiel, Kathleen; Billingsley, Glenna

2015-01-01

Concept maps have been used to help students with learning disabilities (LD) improve literacy skills and content learning, predominantly in secondary school. However, despite increased access to classroom technology, no previous studies have examined the efficacy of computer-based concept maps to improve learning from informational text for students with LD in elementary school. In this study, we used a concurrent delayed multiple probe design to evaluate the interactive use of computer-based concept maps on content acquisition with science and social studies texts for Hispanic students with LD in Grades 4 and 5. Findings from this study suggest that students improved content knowledge during intervention relative to a traditional instruction baseline condition. Learning outcomes and social validity information are considered to inform recommendations for future research and the feasibility of classroom implementation. © The Author(s) 2014.

Can a policy program influence policy change? The case of the Swiss EnergieSchweiz program

International Nuclear Information System (INIS)

Sager, Fritz; Bürki, Marietta; Luginbühl, Jennifer

2014-01-01

This paper investigates the interrelation of policy implementation and policy change by addressing the question of whether and how the Swiss energy program “EnergieSchweiz” influenced policy decisions. We discuss different ways in which a policy program may influence policy change: by negative and positive learning, by coalition building and by policy community building. Respective assumptions are tested in two case studies from the “EnergieSchweiz” program, which was in place from 2000 to 2010. We find that, while the policy program was not critical for the policy change itself, it nevertheless played a role as an agenda setter, as an initiator of learning processes as well as through its policy community. - Highlights: • We investigate how energy policy implementation impacts policy change. • We analyse the Swiss energy program “EnergieSchweiz” in place from 2000 to 2010. • Policy programs alone do not deliver policy change. • But they can influence it by agenda setting and by negative learning. • Expert networks have an influence if there are shared goals

Sentiment analysis: a comparison of deep learning neural network algorithm with SVM and naϊve Bayes for Indonesian text

Science.gov (United States)

Calvin Frans Mariel, Wahyu; Mariyah, Siti; Pramana, Setia

2018-03-01

Deep learning is a new era of machine learning techniques that essentially imitate the structure and function of the human brain. It is a development of deeper Artificial Neural Network (ANN) that uses more than one hidden layer. Deep Learning Neural Network has a great ability on recognizing patterns from various data types such as picture, audio, text, and many more. In this paper, the authors tries to measure that algorithm’s ability by applying it into the text classification. The classification task herein is done by considering the content of sentiment in a text which is also called as sentiment analysis. By using several combinations of text preprocessing and feature extraction techniques, we aim to compare the precise modelling results of Deep Learning Neural Network with the other two commonly used algorithms, the Naϊve Bayes and Support Vector Machine (SVM). This algorithm comparison uses Indonesian text data with balanced and unbalanced sentiment composition. Based on the experimental simulation, Deep Learning Neural Network clearly outperforms the Naϊve Bayes and SVM and offers a better F-1 Score while for the best feature extraction technique which improves that modelling result is Bigram.

Continuing professional development for teachers in South Africa and social learning systems: conflicting conceptual frameworks of learning

Directory of Open Access Journals (Sweden)

G.M. Steyn

2008-07-01

Full Text Available To transform education in this country, South African teachers need to be appropriately equipped to meet the evolving challenges and needs of the country. The national policy framework for teacher education and development is an attempt to address the need for suitably qualified teachers in South Africa. Its aim is to improve the quality of education by focusing on the professional development of teachers. This article attempts to address the following research problem: Does continuing professional development for teachers (CPDT, as stipulated by the national policy framework, have the potential to contribute to the development of teachers as proposed by social learning systems? The answer to this question has the potential to inform and influence the policy and its implementation. The answer also describes how conceptual frameworks for learning in Wenger’s social learning systems conflict with effective professional development (PD programmes and CPDT.

Does the Arrangement of Embedded Text versus Linked Text in Homework Systems Make a Difference in Students Impressions, Attitudes, and Perceived Learning?

Science.gov (United States)

Zumalt, Caitlin J.; Williamson, Vickie M.

2016-01-01

Students in a first-semester general chemistry course at a large southwestern university completed a 3-week homework assignment using MindTap, a Cengage Learning product. MindTap is the first major electronic system that has homework questions embedded in the text, such that students read a short section of the textbook and then answer a question…

Effects of Image-Based and Text-Based Active Learning Exercises on Student Examination Performance in a Musculoskeletal Anatomy Course

Science.gov (United States)

Gross, M. Melissa; Wright, Mary C.; Anderson, Olivia S.

2017-01-01

Research on the benefits of visual learning has relied primarily on lecture-based pedagogy, but the potential benefits of combining active learning strategies with visual and verbal materials on learning anatomy has not yet been explored. In this study, the differential effects of text-based and image-based active learning exercises on examination…

Text mining from ontology learning to automated text processing applications

CERN Document Server

Biemann, Chris

2014-01-01

This book comprises a set of articles that specify the methodology of text mining, describe the creation of lexical resources in the framework of text mining and use text mining for various tasks in natural language processing (NLP). The analysis of large amounts of textual data is a prerequisite to build lexical resources such as dictionaries and ontologies and also has direct applications in automated text processing in fields such as history, healthcare and mobile applications, just to name a few. This volume gives an update in terms of the recent gains in text mining methods and reflects

An Introduction to Topic Modeling as an Unsupervised Machine Learning Way to Organize Text Information

Science.gov (United States)

Snyder, Robin M.

2015-01-01

The field of topic modeling has become increasingly important over the past few years. Topic modeling is an unsupervised machine learning way to organize text (or image or DNA, etc.) information such that related pieces of text can be identified. This paper/session will present/discuss the current state of topic modeling, why it is important, and…

Adaptive Trajectory Tracking Control using Reinforcement Learning for Quadrotor

Directory of Open Access Journals (Sweden)

Wenjie Lou

2016-02-01

Full Text Available Inaccurate system parameters and unpredicted external disturbances affect the performance of non-linear controllers. In this paper, a new adaptive control algorithm under the reinforcement framework is proposed to stabilize a quadrotor helicopter. Based on a command-filtered non-linear control algorithm, adaptive elements are added and learned by policy-search methods. To predict the inaccurate system parameters, a new kernel-based regression learning method is provided. In addition, Policy learning by Weighting Exploration with the Returns (PoWER and Return Weighted Regression (RWR are utilized to learn the appropriate parameters for adaptive elements in order to cancel the effect of external disturbance. Furthermore, numerical simulations under several conditions are performed, and the ability of adaptive trajectory-tracking control with reinforcement learning are demonstrated.

A Coterminous Collaborative Learning Model: Interconnectivity of Leadership and Learning

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Ilana Margolin

2012-05-01

Full Text Available This qualitative ethnographic study examines a collaborative leadership model focused on learning and socially just practices within a change context of a wide educational partnership. The study analyzes a range of perspectives of novice teachers, mentor teachers, teacher educators and district superintendents on leadership and learning. The findings reveal the emergence of a coalition of leaders crossing borders at all levels of the educational system: local school level, district level and teacher education level who were involved in coterminous collaborative learning. Four categories of learning were identified as critical to leading a change in the educational system: learning in professional communities, learning from practice, learning through theory and research and learning from and with leaders. The implications of the study for policy makers as well as for practitioners are to adopt a holistic approach to the educational environment and plan a collaborative learning continuum from initial pre-service programs through professional development learning at all levels.

Enabling physical teaching and learning environment for South African public schools

CSIR Research Space (South Africa)

Motsatsi, L

2012-04-01

Full Text Available This presentation investigates the typology of learning environments that enable effective school teaching and learning. According to the National Education Policy Act (27/1996),research show that there is a direct link between the physical...

Edufare for the Future Precariat: The Moral Agenda in Australia's "Earning or Learning" Policy

Science.gov (United States)

Doherty, Catherine

2017-01-01

This paper considers the educational experience constructed under Australia's policy decision in 2009 to extend compulsory education by requiring that students must be "earning or learning" till 17 years of age. The discussion draws on an empirical project that explored the moral order operating in classrooms for students retained under…

Entrepreneurship Learning Ecosystem for Smart Cities through MOOCs

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Carmen Holotescu

2017-07-01

Full Text Available Abstract Started in 2008, the new Massive Open Online Courses (MOOCs paradigm has brought challenges and innovation at all levels of education, aiming to respond to the most pressing learning needs, generated by the new development policies and the rapid evolution of technology. This paper reports on a project proposed by a group of universities and organizations specialized in training, research and consultancy with a view to develop and implement a learning ecosystem in entrepreneurship. The project is built on a package of MOOCs targeting the learning needs of young entrepreneurs in the context of „Smart cities and specializations” policies. The article presents the project concepts and the development and implementation steps, from MOOCs design, pilot phase, consultancy activities, impact study to proposals for national policies and accreditation. This work could be a starting point for developing new programmes and customized training courses on specific learning needs to support the „Smart cities” interventions.

Policy Design and Non-Design: Towards a Spectrum of Policy Formulation Types

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Michael Howlett

2014-11-01

Full Text Available Public policies are the result of efforts made by governments to alter aspects of behaviour—both that of their own agents and of society at large—in order to carry out some end or purpose. They are comprised of arrangements of policy goals and policy means matched through some decision-making process. These policy-making efforts can be more, or less, systematic in attempting to match ends and means in a logical fashion or can result from much less systematic processes. “Policy design” implies a knowledge-based process in which the choice of means or mechanisms through which policy goals are given effect follows a logical process of inference from known or learned relationships between means and outcomes. This includes both design in which means are selected in accordance with experience and knowledge and that in which principles and relationships are incorrectly or only partially articulated or understood. Policy decisions can be careful and deliberate in attempting to best resolve a problem or can be highly contingent and driven by situational logics. Decisions stemming from bargaining or opportunism can also be distinguished from those which result from careful analysis and assessment. This article considers both modes and formulates a spectrum of policy formulation types between “design” and “non-design” which helps clarify the nature of each type and the likelihood of each unfolding.

Twenty years of energy policy: What should we have learned?

International Nuclear Information System (INIS)

Greene, D.L.

1994-07-01

This report examines the past twenty years of energy market events and energy policies to determine what may be useful for the future. The author focuses on two important lessons that should have been learned but which the author feels have been seriously misunderstood. The first is that oil price shocks were a very big and very real problem for oil importing countries, a problem the has not gone away. The second is that automobile fuel economy regulation has worked and worked effectively to reduce oil consumption and the externalities associated with it, and can still work effectively in the future

Twenty years of energy policy: What should we have learned?

Energy Technology Data Exchange (ETDEWEB)

Greene, D.L. [Oak Ridge National Lab., TN (United States). Center for Transportation Analysis

1994-07-01

This report examines the past twenty years of energy market events and energy policies to determine what may be useful for the future. The author focuses on two important lessons that should have been learned but which the author feels have been seriously misunderstood. The first is that oil price shocks were a very big and very real problem for oil importing countries, a problem the has not gone away. The second is that automobile fuel economy regulation has worked and worked effectively to reduce oil consumption and the externalities associated with it, and can still work effectively in the future.

Teachers' Beliefs, Instructional Behaviors, and Students' Engagement in Learning from Texts with Instructional Pictures

Science.gov (United States)

Schroeder, Sascha; Richter, Tobias; McElvany, Nele; Hachfeld, Axinja; Baumert, Jurgen; Schnotz, Wolfgang; Horz, Holger; Ullrich, Mark

2011-01-01

This study investigated the relations between teachers' pedagogical beliefs and students' self-reported engagement in learning from texts with instructional pictures. Participants were the biology, geography, and German teachers of 46 classes (Grades 5-8) and their students. Teachers' instructional behaviors and students' engagement in learning…

Policy learning through strategic intelligence: the American small business innovation research program (SBIR) and British small business research initiative (SBRI)

NARCIS (Netherlands)

Padilla, P.C.A.

2016-01-01

Innovation policy involves using policy instruments to achieve societal goals. In order to learn from both past and foreign experiences, scholars and practitioners very often value sources of knowledge about these instruments. This dissertation deals with the role of Strategic Intelligence in both

Learning Semantic Tags from Big Data for Clinical Text Representation.

Science.gov (United States)

Li, Yanpeng; Liu, Hongfang

2015-01-01

In clinical text mining, it is one of the biggest challenges to represent medical terminologies and n-gram terms in sparse medical reports using either supervised or unsupervised methods. Addressing this issue, we propose a novel method for word and n-gram representation at semantic level. We first represent each word by its distance with a set of reference features calculated by reference distance estimator (RDE) learned from labeled and unlabeled data, and then generate new features using simple techniques of discretization, random sampling and merging. The new features are a set of binary rules that can be interpreted as semantic tags derived from word and n-grams. We show that the new features significantly outperform classical bag-of-words and n-grams in the task of heart disease risk factor extraction in i2b2 2014 challenge. It is promising to see that semantics tags can be used to replace the original text entirely with even better prediction performance as well as derive new rules beyond lexical level.

Supervised Machine Learning Algorithms Can Classify Open-Text Feedback of Doctor Performance With Human-Level Accuracy

Science.gov (United States)

2017-01-01

Background Machine learning techniques may be an effective and efficient way to classify open-text reports on doctor’s activity for the purposes of quality assurance, safety, and continuing professional development. Objective The objective of the study was to evaluate the accuracy of machine learning algorithms trained to classify open-text reports of doctor performance and to assess the potential for classifications to identify significant differences in doctors’ professional performance in the United Kingdom. Methods We used 1636 open-text comments (34,283 words) relating to the performance of 548 doctors collected from a survey of clinicians’ colleagues using the General Medical Council Colleague Questionnaire (GMC-CQ). We coded 77.75% (1272/1636) of the comments into 5 global themes (innovation, interpersonal skills, popularity, professionalism, and respect) using a qualitative framework. We trained 8 machine learning algorithms to classify comments and assessed their performance using several training samples. We evaluated doctor performance using the GMC-CQ and compared scores between doctors with different classifications using t tests. Results Individual algorithm performance was high (range F score=.68 to .83). Interrater agreement between the algorithms and the human coder was highest for codes relating to “popular” (recall=.97), “innovator” (recall=.98), and “respected” (recall=.87) codes and was lower for the “interpersonal” (recall=.80) and “professional” (recall=.82) codes. A 10-fold cross-validation demonstrated similar performance in each analysis. When combined together into an ensemble of multiple algorithms, mean human-computer interrater agreement was .88. Comments that were classified as “respected,” “professional,” and “interpersonal” related to higher doctor scores on the GMC-CQ compared with comments that were not classified (P.05). Conclusions Machine learning algorithms can classify open-text feedback

Supervised Machine Learning Algorithms Can Classify Open-Text Feedback of Doctor Performance With Human-Level Accuracy.

Science.gov (United States)

Gibbons, Chris; Richards, Suzanne; Valderas, Jose Maria; Campbell, John

2017-03-15

Machine learning techniques may be an effective and efficient way to classify open-text reports on doctor's activity for the purposes of quality assurance, safety, and continuing professional development. The objective of the study was to evaluate the accuracy of machine learning algorithms trained to classify open-text reports of doctor performance and to assess the potential for classifications to identify significant differences in doctors' professional performance in the United Kingdom. We used 1636 open-text comments (34,283 words) relating to the performance of 548 doctors collected from a survey of clinicians' colleagues using the General Medical Council Colleague Questionnaire (GMC-CQ). We coded 77.75% (1272/1636) of the comments into 5 global themes (innovation, interpersonal skills, popularity, professionalism, and respect) using a qualitative framework. We trained 8 machine learning algorithms to classify comments and assessed their performance using several training samples. We evaluated doctor performance using the GMC-CQ and compared scores between doctors with different classifications using t tests. Individual algorithm performance was high (range F score=.68 to .83). Interrater agreement between the algorithms and the human coder was highest for codes relating to "popular" (recall=.97), "innovator" (recall=.98), and "respected" (recall=.87) codes and was lower for the "interpersonal" (recall=.80) and "professional" (recall=.82) codes. A 10-fold cross-validation demonstrated similar performance in each analysis. When combined together into an ensemble of multiple algorithms, mean human-computer interrater agreement was .88. Comments that were classified as "respected," "professional," and "interpersonal" related to higher doctor scores on the GMC-CQ compared with comments that were not classified (P.05). Machine learning algorithms can classify open-text feedback of doctor performance into multiple themes derived by human raters with high

Text conception(s in context of semi-present Distance Learning (DL

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Fabiana Komesu

2013-02-01

Full Text Available By following the example proposed by Corrêa (2011 in the investigation of texts produced by undergraduate and pre-undergraduate students in two different assessment, this work aims to approach “hidden” aspects in the teaching of writing at the university (Street, 2009, to reflections produced in the language field, in particular the ones referred as “socially assumed”, proposed by Voloshinov/Bakhtin (s/d: 1926. It is particularly important to investigate the conception of text in digital context, by means of the study of updated semiotic resources in the production of undergraduate students using a computer with internet access in the process of semi-present Distance Learning (DL. The collected material comprises 29 (twenty nine texts which were produced by students of the semi-present Pedagogy Course from Univesp (Universidade Virtual do Estado de São Paulo – Virtual University from the state of São Paulo, who were studying “Education and Language”, in 2010. This qualitative analysis aims to show that regarding the institution there is a prevalence of structural and procedural aspects for the accomplishment of the proposed activity and, regarding the undergraduate student it is noticed that the production is characterized by a traditional conception of text, mainly recognized by written verbal text, although the proposal prioritized the relation between verbal and non verbal language. Regarding discursive-linguistic studies, it is important to reflect about a text conception that privileges the integration of multiple semiosis by taking into account the socio-historical interlocution character established within utterances of others.

Joint Extraction of Entities and Relations Using Reinforcement Learning and Deep Learning

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Yuntian Feng

2017-01-01

Full Text Available We use both reinforcement learning and deep learning to simultaneously extract entities and relations from unstructured texts. For reinforcement learning, we model the task as a two-step decision process. Deep learning is used to automatically capture the most important information from unstructured texts, which represent the state in the decision process. By designing the reward function per step, our proposed method can pass the information of entity extraction to relation extraction and obtain feedback in order to extract entities and relations simultaneously. Firstly, we use bidirectional LSTM to model the context information, which realizes preliminary entity extraction. On the basis of the extraction results, attention based method can represent the sentences that include target entity pair to generate the initial state in the decision process. Then we use Tree-LSTM to represent relation mentions to generate the transition state in the decision process. Finally, we employ Q-Learning algorithm to get control policy π in the two-step decision process. Experiments on ACE2005 demonstrate that our method attains better performance than the state-of-the-art method and gets a 2.4% increase in recall-score.

The Interrelations between Diagrammatic Representations and Verbal Explanations in Learning from Social Science Texts.

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Guri-Rozenblit, Sarah

1988-01-01

Describes study that examined the instructional effectiveness of abstract diagrams and verbal explanations in learning from social science texts. The control and treatment groups of adult learners at Everyman's University (Israel) are described, verbal and visual aptitude tests are explained, and results are analyzed. (25 references) (Author/LRW)

Time-Contrastive Learning Based DNN Bottleneck Features for Text-Dependent Speaker Verification

DEFF Research Database (Denmark)

Sarkar, Achintya Kumar; Tan, Zheng-Hua

2017-01-01

In this paper, we present a time-contrastive learning (TCL) based bottleneck (BN) feature extraction method for speech signals with an application to text-dependent (TD) speaker verification (SV). It is well-known that speech signals exhibit quasi-stationary behavior in and only in a short interval......, and the TCL method aims to exploit this temporal structure. More specifically, it trains deep neural networks (DNNs) to discriminate temporal events obtained by uniformly segmenting speech signals, in contrast to existing DNN based BN feature extraction methods that train DNNs using labeled data...... to discriminate speakers or pass-phrases or phones or a combination of them. In the context of speaker verification, speech data of fixed pass-phrases are used for TCL-BN training, while the pass-phrases used for TCL-BN training are excluded from being used for SV, so that the learned features can be considered...

Investigating an Application of Speech-to-Text Recognition: A Study on Visual Attention and Learning Behaviour

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Huang, Y-M.; Liu, C-J.; Shadiev, Rustam; Shen, M-H.; Hwang, W-Y.

2015-01-01

One major drawback of previous research on speech-to-text recognition (STR) is that most findings showing the effectiveness of STR for learning were based upon subjective evidence. Very few studies have used eye-tracking techniques to investigate visual attention of students on STR-generated text. Furthermore, not much attention was paid to…

Technologies, Democracy and Digital Citizenship: Examining Australian Policy Intersections and the Implications for School Leadership

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Kathryn Moyle

2014-01-01

Full Text Available There are intersections that can occur between the respective peak Australian school education policy agendas. These policies include the use of technologies in classrooms to improve teaching and learning as promoted through the Melbourne Declaration on Educational Goals for Young Australians and the Australian Curriculum; and the implementation of professional standards as outlined in the Australian Professional Standard for Principals and the Australian Professional Standards for Teachers. These policies create expectations of school leaders to bring about change in classrooms and across their schools, often described as bringing about ‘quality teaching’ and ‘school improvement’. These policies indicate that Australian children should develop ‘democratic values’, and that school principals should exercise ‘democratic values’ in their schools. The national approaches to the implementation of these policies however, is largely silent on promoting learning that fosters democracy through education, or about making connections between teaching and learning with technologies, school leadership and living in a democracy. Yet the policies promote these connections and alignments. Furthermore, understanding democratic values, knowing what is a democracy, and being able to use technologies in democratic ways, has to be learned and practiced. Through the lens of the use of technologies to build digital citizenship and to achieve democratic processes and outcomes in schools, these policy complexities are examined in order to consider some of the implications for school leadership.

Policies of Adult Education in Portugal and France: The European Agenda of Validation of Non-Formal and Informal Learning

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Cavaco, C.; Lafont, P.; Pariat, M.

2014-01-01

This article analyses the influence of the European Union's educational policies on the implementation of devices for the recognition and the validation of informal and non-formal learning within public policies on education and training for adults in European Union Member States. Portugal and France are taken as examples. The European Union's…

Translanguaging in Self-Access Language Advising: Informing Language Policy

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Naoki Fujimoto-Adamson

2012-03-01

Full Text Available This study investigates language advising in a self-access center (SAC with the purpose of informing language policy. This center is located in a new Japanese university and has shifted from an initially teacher-imposed ‘English-only’ language policy into one which encourages “translanguaging” (Blackledge & Creese, 2010, p. 105 between the students’ and center advisors’ (termed as mentors in this center L1 (Japanese and their L2 (English. Data from audio-recordings of interaction with advisors and students and between students themselves, interviews with mentors, and student questionnaires all reveal how translanguaging occurs in practice and how it helps to create a learning space in which the “local, pragmatic coping tactics” (Lin, 2005, p. 46 of code-switching offer a more viable approach for learning than under its initial monolingual policy. Mentor interviews and student questionnaires indicate generally positive attitudes towards translanguaging; however, some students still favor an ‘English-only’ policy. Conclusions reveal that a looser language policy in the center is emerging in which mentors now guide students towards their own individualized language policies. It is argued in this paper that this “code choice” (Levine, 2011 in language use is therefore aligned more closely to the principles of student-direction in self-access use.

The teaching of Education Policy and Administration in pre-service teacher education courses

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Ranilce Guimarães-Iosif

2018-01-01

Full Text Available This article discusses the teaching of education policy and administration in pre-service teacher education courses from a theoretical-critical and non-linear perspective of education policy study. The data was collected during a semester in two mixed classes totaling 65 students from the Physical Education, Literature, Biology, Chemistry, Mathematics and Physics undergraduate courses. As part of the integration project of the graduate program in education with the undergraduate program, the professor of the policy line of the program in education began using methodologies focused on research activities in their undergraduate classes, aiming to broaden learning and to familiarize students with themes related to education policies. The research results indicate that the learning process in the area goes from the initial rejection to the construction of a critical position on political and governance issues surrounding Brazilian education.

The Intersection of Afterschool and Competency-Based Learning: Emerging Trends, Policy Considerations, and Questions for the Future. AYPF White Paper

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Lerner, Jennifer Brown; Tomasello, Jenna; Brand, Betsy; Knowles, George

2016-01-01

Afterschool and competency-based learning are increasingly emerging as student-centered, supportive learning models to prepare students for college and career. This white paper explores the intersection and relationship between these two fields, recommends ideal policy environments for implementing successful programs, provides real-world…

A Review of Cash Management Policies, Procedures and Practices of Mississippi's Institutions of Higher Learning.

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Mississippi State Legislature, Jackson. Performance Evaluation and Expenditure Review Committee.

This report to the Mississippi Legislature presents the findings of a review of the cash management policies, procedures, and practices of the State Board of Trustees of Institutions of Higher Learning (IHL). The methodology involved review of: applicable Mississippi statutes; standards promulgated by the National Association of College and…

Learning about Probability from Text and Tables: Do Color Coding and Labeling through an Interactive-User Interface Help?

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Clinton, Virginia; Morsanyi, Kinga; Alibali, Martha W.; Nathan, Mitchell J.

2016-01-01

Learning from visual representations is enhanced when learners appropriately integrate corresponding visual and verbal information. This study examined the effects of two methods of promoting integration, color coding and labeling, on learning about probabilistic reasoning from a table and text. Undergraduate students (N = 98) were randomly…

Managing energy demand through transport policy: What can South Africa learn from Europe?

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Vanderschuren, Marianne; Lane, T.E.; Korver, W.

2010-01-01

For years, the world has enjoyed the luxury of inexpensive transport fuels, resulting in the continuous expansion of transport demand and vast improvements in mobility levels. The threat of peak oil and other environmental concerns, however, are forcing a paradigm shift in terms of transport planning. In recent times, many developed nations have been investigating alternative ways and means of weaning themselves off oil as the main transport energy source and managing transport energy demand. South Africa is a developing nation that, in terms of transportation technology and policy, lags behind developed countries. This presents South Africa with the opportunity to learn from other countries' triumphs and mistakes and to skip over obsolete investment patterns and ineffective policy. It needs to be determined what South Africa can do to bend the stream of continuously growing transport (energy) demand, without hampering growth in mobility. Solutions can potentially be found by looking at the European Union's past and present situation and responses. This paper summarises various European energy management transport policies. These policies are translated into a South African context-pros, cons and implementation viability are identified.

Managing energy demand through transport policy. What can South Africa learn from Europe?

Energy Technology Data Exchange (ETDEWEB)

Vanderschuren, Marianne [Centre for Transport Studies, Faculty of Engineering and the Built Environment, University of Cape Town, Private Bag, 7701 Rondebosch (South Africa); Lane, T.E. [Centre for Transport Studies, University of Cape Town (South Africa); Korver, W. [Goudappel Coffeng BV (Netherlands)

2010-02-15

For years, the world has enjoyed the luxury of inexpensive transport fuels, resulting in the continuous expansion of transport demand and vast improvements in mobility levels. The threat of peak oil and other environmental concerns, however, are forcing a paradigm shift in terms of transport planning. In recent times, many developed nations have been investigating alternative ways and means of weaning themselves off oil as the main transport energy source and managing transport energy demand. South Africa is a developing nation that, in terms of transportation technology and policy, lags behind developed countries. This presents South Africa with the opportunity to learn from other countries' triumphs and mistakes and to skip over obsolete investment patterns and in effective policy. It needs to be determined what South Africa can do to bend the stream of continuously growing transport (energy) demand, without hampering growth in mobility. Solutions can potentially be found by looking at the European Union's past and present situation and responses. This paper summarises various European energy management transport policies. These policies are translated into a South African context - pros, cons and implementation viability are identified. (author)

Managing energy demand through transport policy: What can South Africa learn from Europe?

Energy Technology Data Exchange (ETDEWEB)

Vanderschuren, Marianne, E-mail: marianne.vanderschuren@uct.ac.z [Centre for Transport Studies, Faculty of Engineering and the Built Environment, University of Cape Town, Private Bag, 7701 Rondebosch (South Africa); Lane, T.E., E-mail: lane.tanya@gmail.co [Centre for Transport Studies, University of Cape Town (South Africa); Korver, W., E-mail: WKorver@goudappel.n [Goudappel Coffeng BV (Netherlands)

2010-02-15

For years, the world has enjoyed the luxury of inexpensive transport fuels, resulting in the continuous expansion of transport demand and vast improvements in mobility levels. The threat of peak oil and other environmental concerns, however, are forcing a paradigm shift in terms of transport planning. In recent times, many developed nations have been investigating alternative ways and means of weaning themselves off oil as the main transport energy source and managing transport energy demand. South Africa is a developing nation that, in terms of transportation technology and policy, lags behind developed countries. This presents South Africa with the opportunity to learn from other countries' triumphs and mistakes and to skip over obsolete investment patterns and ineffective policy. It needs to be determined what South Africa can do to bend the stream of continuously growing transport (energy) demand, without hampering growth in mobility. Solutions can potentially be found by looking at the European Union's past and present situation and responses. This paper summarises various European energy management transport policies. These policies are translated into a South African context-pros, cons and implementation viability are identified.

THE IMPLEMENTATION OF ENGLISH-ONLY POLICY IN THE TERTIARY EFL CONTEXT IN TAIWAN

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David Dirkwen Wei

2013-01-01

Full Text Available Abstract: The implementation of English-only policy in the English classes at Wenzao Ursuline College of Languages in Taiwan has continued for nearly 40 years. Its advantages and disadvantages have also been debated and challenged because of the rising demands on students’ English proficiency in Taiwan. This study intended to reexamine the efficiency of the implementation of English-only policy in the English learning at a college of languages in Taiwan. Both quantitative and qualitative methods were used in the process of data collection. 279 English major and non-English major students were invited to answer questionnaires, and six participants were invited to join interviews. The process of data analysis included the analysis of both the quantitative questionnaire data and the qualitative interview data. This study found students’ progress in English listening and speaking proficiency in the basic and lower-intermediate levels because of English-only policy. However, the interaction between teachers and some students was hampered because of the policy. Also, the ambiguity emerging in the insistence on using English only blocked some learners from comprehending the meanings of the texts they were learning, specifically the texts in the upper-intermediate and intermediate-advanced levels of English reading and writing courses. This study also found that proper tolerance of using both students’ native language and English in TEFL classes in the way of code-switching may help students more than the implementation of English-only policy in a tertiary TEFL context.

BOOK REVIEW OPEN EDUCATIONAL RESOURCES: Policy, Costs and Transformation

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Can GULER

2016-10-01

Full Text Available This book presents 15 case studies contributed by researchers and policy makers. The Open Educational Resources (OER implementations are expressed through different point of views. This book focused on three themes: policy, costs and transformation. Policy theme is related to the establishment of priorities for supporting the decisions made by an institution or organization. Costs theme explores the funding of OER, particularly in the sense of cost effectiveness. Transformation theme provides examples that demonstrate how OER can be used in ways that go beyond replication of current teaching and learning models. The editors in the Introduction elaborately describe these three themes.

Learning Nanotechnology with Texts and Comics: The Impacts on Students of Different Achievement Levels

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Lin, Shu-Fen; Lin, Huann-shyang

2016-01-01

Comics are popular with adolescents because of their features of humor, narrative, and visual imagery. The purposes of this study were to examine the learning outcomes and emotional perceptions of reading a science comic book and a science text booklet for students of different levels of achievement, and to explore the main factors of the two…

Developing Policy Instruments for Education in the EU: The European Qualifications Framework for Lifelong Learning

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Elken, Mari

2015-01-01

The European Qualifications Framework (EQF) for lifelong learning has been characterized as a policy instrument with a number of contested ideas, raising questions about the process through which such instruments are developed at European level. The introduction of the EQF is in this article examined through variations of neo-institutional theory:…

Keeping Pace with K-12 Online & Blended Learning: An Annual Review of Policy and Practice. 10 Year Anniversary Issue

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Watson, John; Murin, Amy; Vashaw, Lauren; Gemin, Butch; Rapp, Chris

2013-01-01

"Keeping Pace with K-12 Online & Blended Learning" (2013), the 10th in a series of annual reports that began in 2004, examines the status of K-12 online education across the country. The report provides an overview of the latest policies, practices, and trends affecting online learning programs across all 50 states. In this 10th…

The Role of Working Memory in Multimedia Instruction: Is Working Memory Working during Learning from Text and Pictures?

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Schuler, Anne; Scheiter, Katharina; van Genuchten, Erlijn

2011-01-01

A lot of research has focused on the beneficial effects of using multimedia, that is, text and pictures, for learning. Theories of multimedia learning are based on Baddeley's working memory model (Baddeley 1999). Despite this theoretical foundation, there is only little research that aims at empirically testing whether and more importantly how…

Doing Mathematics with Purpose: Mathematical Text Types

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Dostal, Hannah M.; Robinson, Richard

2018-01-01

Mathematical literacy includes learning to read and write different types of mathematical texts as part of purposeful mathematical meaning making. Thus in this article, we describe how learning to read and write mathematical texts (proof text, algorithmic text, algebraic/symbolic text, and visual text) supports the development of students'…

Enhancing Video Games Policy Based on Least-Squares Continuous Action Policy Iteration: Case Study on StarCraft Brood War and Glest RTS Games and the 8 Queens Board Game

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Shahenda Sarhan

2016-01-01

Full Text Available With the rapid advent of video games recently and the increasing numbers of players and gamers, only a tough game with high policy, actions, and tactics survives. How the game responds to opponent actions is the key issue of popular games. Many algorithms were proposed to solve this problem such as Least-Squares Policy Iteration (LSPI and State-Action-Reward-State-Action (SARSA but they mainly depend on discrete actions, while agents in such a setting have to learn from the consequences of their continuous actions, in order to maximize the total reward over time. So in this paper we proposed a new algorithm based on LSPI called Least-Squares Continuous Action Policy Iteration (LSCAPI. The LSCAPI was implemented and tested on three different games: one board game, the 8 Queens, and two real-time strategy (RTS games, StarCraft Brood War and Glest. The LSCAPI evaluation proved superiority over LSPI in time, policy learning ability, and effectiveness.

Learning to learn in the European Reference Framework for lifelong learning

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Pirrie, Anne; Thoutenhoofd, Ernst D.

2013-01-01

This article explores the construction of learning to learn that is implicit in the document Key Competences for Lifelong LearningEuropean Reference Framework and related education policy from the European Commission. The authors argue that the hallmark of learning to learn is the development of a

Evidence-based policy for environmental sustainability: a path forward for South Africa

CSIR Research Space (South Africa)

Funke, Nicola S

2009-03-01

Full Text Available This handbook summarises the background behind, format of and lessons learned from a Collaborative Workshop on Evidence-based Policy-making that was held in November 2008. The workshop was organised by CSIR and funded by the UK's Department of Food...

A Comparative Analysis of E-Learning Policy Formulation in the European Union and the United States: Discursive Convergence and Divergence

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Erichsen, Elizabeth Roumell; Salajan, Florin D.

2014-01-01

This study developed a framework that compares the content and purposes of "federal" level European Union (EU) and United States (US) e-learning policy to ascertain trends, patterns, and points of convergence and divergence across the years 1994-2010. It reveals that the EU and US are applying similar rhetoric for policy framing,…

Learning from the Sun. Analysis of the use of experience curves for energy policy purposes. The case of photovoltaic power. Final report of the Photex project

International Nuclear Information System (INIS)

Schaeffer, G.J.; Seebregts, A.J.; Beurskens, L.W.M.; De Moor, H.H.C.; Alsema, E.; Sark, W.; Durstewicz, M.; Perrin, M.; Boulanger, P.; Laukamp, H.; Zuccaro, C.

2004-08-01

Since the 1990s energy policy scientists have started to explore the possibilities of using the experience curve approach for energy policy making. The concept of the experience curve is simple, at least in principle. It states that, for every doubling of cumulative produced capacity of a product or technology, the cost for making it declines with a fixed percentage (learning rate). Historical statistical analysis can be used to define this percentage. Extrapolating the trend thus found, into the future will then give relevant information about future cost developments and will also give information how much 'learning money' will be needed to get to the break-even point. The Photex project used the development of solar PV as a case to further explore this approach, and also to deduce lessons for PV policy. Other aims were to look at learning rates of the different components of PV-systems and to combine the experience curve analyses with bottom-up engineering studies. The main conclusion with regard to the use of experience curves for energy policy making is that this is an interesting approach, but that such an analysis should be done with much care. For the historical analysis the availability of reliable and firm data is essential. As cost data often are not available, price data could be used as a proxy, as long as sufficient long time ranges are used. Also, the analyst should take care he considers the right learning system boundaries. Furthermore the number of years to be included in the statistical analysis should at least be 10 years and this period sample should not over-represent stable price periods or periods of steep price decline. If possible, data uncertainties should be taken into account as well. An interesting finding was that, at least in the case of PV, the learning rate is not a constant, but can vary over time. In the case of PV it improved from 20% to 23%. Extrapolations into the future should take uncertainties into account and always be

Learning stoichiometry: A comparison of text and multimedia instructional formats

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Evans, Karen L.

Even after multiple instructional opportunities, first year college chemistry students are often unable to apply stoichiometry knowledge in equilibrium and acid-base chemistry problem solving. Cognitive research findings suggest that for learning to be meaningful, learners need to actively construct their own knowledge by integrating new information into, and reorganizing, their prior understandings. Scaffolded inquiry in which facts, procedures, and principles are introduced as needed within the context of authentic problem solving may provide the practice and encoding opportunities necessary for construction of a memorable and usable knowledge base. The dynamic and interactive capabilities of online technology may facilitate stoichiometry instruction that promotes this meaningful learning. Entering college freshmen were randomly assigned to either a technology-rich or text-only set of cognitively informed stoichiometry review materials. Analysis of posttest scores revealed a significant but small difference in the performance of the two treatment groups, with the technology-rich group having the advantage. Both SAT and gender, however, explained more of the variability in the scores. Analysis of the posttest scores from the technology-rich treatment group revealed that the degree of interaction with the Virtual Lab simulation was significantly related to posttest performance and subsumed any effect of prior knowledge as measured by SAT scores. Future users of the online course should be encouraged to engage with the problem-solving opportunities provided by the Virtual Lab simulation through either explicit instruction and/or implementation of some level of program control within the course's navigational features.

Analyzing discourse and text complexity for learning and collaborating a cognitive approach based on natural language processing

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Dascălu, Mihai

2014-01-01

With the advent and increasing popularity of Computer Supported Collaborative Learning (CSCL) and e-learning technologies, the need of automatic assessment and of teacher/tutor support for the two tightly intertwined activities of comprehension of reading materials and of collaboration among peers has grown significantly. In this context, a polyphonic model of discourse derived from Bakhtin’s work as a paradigm is used for analyzing both general texts and CSCL conversations in a unique framework focused on different facets of textual cohesion. As specificity of our analysis, the individual learning perspective is focused on the identification of reading strategies and on providing a multi-dimensional textual complexity model, whereas the collaborative learning dimension is centered on the evaluation of participants’ involvement, as well as on collaboration assessment. Our approach based on advanced Natural Language Processing techniques provides a qualitative estimation of the learning process and enhance...

The effects of generative testing on text retention and text comprehension

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Dirkx, Kim; Kester, Liesbeth; Kirschner, Paul A.

2011-01-01

Dirkx, K. J. H., Kester, L., & Kirschner, P. A. (2011, 30 August). The effects of generative testing methods on text retention and text comprehension. Paper presented at the annual meeting of the European Association for Research on Learning and Instruction, Exeter, United Kingdom.

Text Mining Applications and Theory

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Berry, Michael W

2010-01-01

Text Mining: Applications and Theory presents the state-of-the-art algorithms for text mining from both the academic and industrial perspectives.  The contributors span several countries and scientific domains: universities, industrial corporations, and government laboratories, and demonstrate the use of techniques from machine learning, knowledge discovery, natural language processing and information retrieval to design computational models for automated text analysis and mining. This volume demonstrates how advancements in the fields of applied mathematics, computer science, machine learning

Examining Mobile Learning Trends 2003-2008: A Categorical Meta-Trend Analysis Using Text Mining Techniques

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Hung, Jui-Long; Zhang, Ke

2012-01-01

This study investigated the longitudinal trends of academic articles in Mobile Learning (ML) using text mining techniques. One hundred and nineteen (119) refereed journal articles and proceedings papers from the SCI/SSCI database were retrieved and analyzed. The taxonomies of ML publications were grouped into twelve clusters (topics) and four…

School learning among the Kaingang indigenous people in the State of Paraná: language, literacy and language learning issues

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Rosângela Célia Faustino

2010-12-01

Full Text Available The present paper studies the issues of literacy and language learning in relation to the mother tongue of the Kaingang indigenous people in the state of Paraná. Based on data collected in field research, literature and documents (2007-2010, it discusses the public policies for social inclusion and the current policy of indigenous education developed in 1990 by the Ministry of Education - MEC. It also points out how this policy can foster the access to scientific knowledge among ethnic groups, increasing the chances of literacy, citizenship and indigenous autonomy.

Learning from Expository Text in L2 Reading: Memory for Causal Relations and L2 Reading Proficiency

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Hosoda, Masaya

2017-01-01

This study explored the relation between second-language (L2) readers' memory for causal relations and their learning outcomes from expository text. Japanese students of English as a foreign language (EFL) with high and low L2 reading proficiency read an expository text. They completed a causal question and a problem-solving test as measures of…

Using SMART Board Technology to Teach Young Students with Disabilities and Limited Group Learning Experience to Read Environmental Text

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Shepley, Collin; Lane, Justin D.; Gast, David L.

2016-01-01

A multiple probe design across behaviors was used to evaluate the effectiveness of a SMART Board used in conjunction with teacher delivered constant time delay (CTD) to teach environmental text to three young students with disabilities and minimal group learning experience during small group direct instruction. Observational learning, instructive…

Impact of Interactive Video Communication Versus Text-Based Feedback on Teaching, Social, and Cognitive Presence in Online Learning Communities.

Science.gov (United States)

Seckman, Charlotte

A key element to online learning is the ability to create a sense of presence to improve learning outcomes. This quasi-experimental study evaluated the impact of interactive video communication versus text-based feedback and found a significant difference between the 2 groups related to teaching, social, and cognitive presence. Recommendations to enhance presence should focus on providing timely feedback, interactive learning experiences, and opportunities for students to establish relationships with peers and faculty.

Episodic reinforcement learning control approach for biped walking

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Katić Duško

2012-01-01

Full Text Available This paper presents a hybrid dynamic control approach to the realization of humanoid biped robotic walk, focusing on the policy gradient episodic reinforcement learning with fuzzy evaluative feedback. The proposed structure of controller involves two feedback loops: a conventional computed torque controller and an episodic reinforcement learning controller. The reinforcement learning part includes fuzzy information about Zero-Moment- Point errors. Simulation tests using a medium-size 36-DOF humanoid robot MEXONE were performed to demonstrate the effectiveness of our method.

Organizational Learning in Schools under Sanction

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Kara S. Finnigan

2012-01-01

Full Text Available The focus on “school turnaround” has become central to policy and practice in the United States as a result of school accountability, yet little remains known about school improvement under sanction. This study uses theories of organizational learning to understand the processes through which educators search for and adopt reform strategies, as well as the extent to which these schools’ organizational culture and climate are conducive to this type of learning. Our mixed methods study involves document analysis, intensive case studies, and a survey of teachers in schools under sanction in a large urban school district in the USA. We found limited evidence of organizational learning, and instead evidence suggested superficial use of restructuring planning, rare diagnoses of root causes of low performance, and limited engagement in learning processes of school staff. In addition, schools relied on exploitation resulting in the recycling of previous practices. In part, the limited organizational learning in evidence was the result of structures and climates within these low-performing schools that inhibited a more learning-oriented approach to reform. Our study has implications for school improvement under accountability policies as it uncovers important challenges that limit organizational learning and, as a result, school improvement under sanction.

Learning by Doing vs Learning by Researching in a Model of Climate Change Policy Analysis

International Nuclear Information System (INIS)

Castelnuovo, E.; Galeotti, M.; Vergalli, S.; Gambarelli, G.

2004-01-01

Many predictions and conclusions in the climate change literature have been made and drawn on the basis of theoretical analyses and quantitative models that assume exogenous technological change. One is naturally led to wonder whether those conclusions and policy prescriptions hold in the more realistic case of endogenously evolving technologies. In previous work we took a popular integrated assessment model and modified it so as to allow for an explicit role of the stock of knowledge which accumulates through R and D investment. In our formulation knowledge affects both the output production technology and the emission-output ratio. In this paper we make further progress in our efforts aimed to model the process of technological change. In keeping with recent theories of endogenous growth, we specify two ways in which knowledge accumulates: via a deliberate, optimally selected R and D decision or via experience, giving rise to Learning by Doing. As an illustration, we simulate the model under the two versions of endogenous technical change and look at the dynamics of a selected number of relevant variables, including growth rates of GDP and physical capital, as well as total emissions and rate of domestic abatement. Keywords: Climate Policy, Environmental Modeling, Integrated Assessment, Technical Change

Lifelong Education and Learning, Societal Project and Competitive Advantage: Tensions and Ambivalences in Policy and Planning of Educational Change in Portugal

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Antunes, Fátima; Guimarães, Paula

2014-01-01

Both the Portuguese appropriation of the lifelong learning policy proposed by the European Union since the mid-1990s and the definition of adult education policy in Portugal were based on a discourse that emphasised an "unacceptable educational deficit" for democracy. The role of the State in the "governance" of the public…

Off-Policy Reinforcement Learning: Optimal Operational Control for Two-Time-Scale Industrial Processes.

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Li, Jinna; Kiumarsi, Bahare; Chai, Tianyou; Lewis, Frank L; Fan, Jialu

2017-12-01

Industrial flow lines are composed of unit processes operating on a fast time scale and performance measurements known as operational indices measured at a slower time scale. This paper presents a model-free optimal solution to a class of two time-scale industrial processes using off-policy reinforcement learning (RL). First, the lower-layer unit process control loop with a fast sampling period and the upper-layer operational index dynamics at a slow time scale are modeled. Second, a general optimal operational control problem is formulated to optimally prescribe the set-points for the unit industrial process. Then, a zero-sum game off-policy RL algorithm is developed to find the optimal set-points by using data measured in real-time. Finally, a simulation experiment is employed for an industrial flotation process to show the effectiveness of the proposed method.

Joint Extraction of Entities and Relations Using Reinforcement Learning and Deep Learning.

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Feng, Yuntian; Zhang, Hongjun; Hao, Wenning; Chen, Gang

2017-01-01

We use both reinforcement learning and deep learning to simultaneously extract entities and relations from unstructured texts. For reinforcement learning, we model the task as a two-step decision process. Deep learning is used to automatically capture the most important information from unstructured texts, which represent the state in the decision process. By designing the reward function per step, our proposed method can pass the information of entity extraction to relation extraction and obtain feedback in order to extract entities and relations simultaneously. Firstly, we use bidirectional LSTM to model the context information, which realizes preliminary entity extraction. On the basis of the extraction results, attention based method can represent the sentences that include target entity pair to generate the initial state in the decision process. Then we use Tree-LSTM to represent relation mentions to generate the transition state in the decision process. Finally, we employ Q -Learning algorithm to get control policy π in the two-step decision process. Experiments on ACE2005 demonstrate that our method attains better performance than the state-of-the-art method and gets a 2.4% increase in recall-score.

Agricultural policy, food policy, and communicable disease policy.

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Grant, Wyn

2012-12-01

Food and agricultural policy is an essential element of a communicable disease policy. The European Union has developed a more systematic and broadly based interest in questions of food safety and animal health and welfare linked to modernization of the Common Agricultural Policy, reflected in a new treaty obligation on animal welfare. Following the bovine spongiform encephalopathy crisis, moves were made to create a European competency, but implementation and enforcement resources reside with the member states. The European Animal Health Strategy is meant to lead to an EU animal health law, but this has already been constrained by fiscal austerity. The development of such a law may lead to a lowest common denominator formula that does little to enhance consumer protection or improve animal welfare. This is an inherent risk with top-down forms of Europeanization; more attention should be paid to lessons to be learned from bottom-up initiatives of the type used to counteract the bovine diarrhea virus. There will always be a tension among what is good policy for reducing the incidence of communicable disease, policy that is popular with EU citizens, and policy that is acceptable to member states.

A Model for Good Governance of Healthcare Technology Management in the Public Sector: Learning from Evidence-Informed Policy Development and Implementation in Benin.

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P Th Houngbo

Full Text Available Good governance (GG is an important concept that has evolved as a set of normative principles for low- and middle-income countries (LMICs to strengthen the functional capacity of their public bodies, and as a conditional prerequisite to receive donor funding. Although much is written on good governance, very little is known on how to implement it. This paper documents the process of developing a strategy to implement a GG model for Health Technology Management (HTM in the public health sector, based on lessons learned from twenty years of experience in policy development and implementation in Benin. The model comprises six phases: (i preparatory analysis, assessing the effects of previous policies and characterizing the HTM system; (ii stakeholder identification and problem analysis, making explicit the perceptions of problems by a diverse range of actors, and assessing their ability to solve these problems; (iii shared analysis and visioning, delineating the root causes of problems and hypothesizing solutions; (iv development of policy instruments for pilot testing, based on quick-win solutions to understand the system's responses to change; (v policy development and validation, translating the consensus solutions identified by stakeholders into a policy; and (vi policy implementation and evaluation, implementing the policy through a cycle of planning, action, observation and reflection. The policy development process can be characterized as bottom-up, with a central focus on the participation of diverse stakeholders groups. Interactive and analytical tools of action research were used to integrate knowledge amongst actor groups, identify consensus solutions and develop the policy in a way that satisfies criteria of GG. This model could be useful for other LMICs where resources are constrained and the majority of healthcare technologies are imported.

A Synthesis of Research on Informational Text Reading Interventions for Elementary Students With Learning Disabilities.

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Ciullo, Stephen; Lo, Yu-Ling Sabrina; Wanzek, Jeanne; Reed, Deborah K

2016-01-01

This research synthesis was conducted to understand the effectiveness of interventions designed to improve learning from informational text for students with learning disabilities in elementary school (K-5). The authors identified 18 studies through a comprehensive search. The interventions were evaluated to determine treatment effects and to understand implementation and methodological variables that influenced outcomes. Moderate to large effect sizes on researcher-developed measures for cognitive strategy interventions were reported. Interventions that utilized graphic organizers as study guides to support social studies learning were also associated with improved outcomes. The findings are considered within the context of limited implementation of standardized measures. The authors extend findings from previous research by reporting a paucity of interventions to enhance higher-level cognitive and comprehension skills. The majority of reviewed studies targeted fact acquisition and main idea identification, and overall encouraging findings were noted for these skills. Implications for future research are discussed. © Hammill Institute on Disabilities 2014.

Continuing Robot Skill Learning after Demonstration with Human Feedback

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Argall Brenna D.

2011-12-01

Full Text Available Though demonstration-based approaches have been successfully applied to learning a variety of robot behaviors, there do exist some limitations. The ability to continue learning after demonstration, based on execution experience with the learned policy, therefore has proven to be an asset to many demonstration-based learning systems. This paper discusses important considerations for interfaces that provide feedback to adapt and improve demonstrated behaviors. Feedback interfaces developed for two robots with very different motion capabilities - a wheeled mobile robot and high degree-of-freedom humanoid - are highlighted.

Using machine learning to disentangle homonyms in large text corpora.

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Roll, Uri; Correia, Ricardo A; Berger-Tal, Oded

2018-06-01

Systematic reviews are an increasingly popular decision-making tool that provides an unbiased summary of evidence to support conservation action. These reviews bridge the gap between researchers and managers by presenting a comprehensive overview of all studies relating to a particular topic and identify specifically where and under which conditions an effect is present. However, several technical challenges can severely hinder the feasibility and applicability of systematic reviews, for example, homonyms (terms that share spelling but differ in meaning). Homonyms add noise to search results and cannot be easily identified or removed. We developed a semiautomated approach that can aid in the classification of homonyms among narratives. We used a combination of automated content analysis and artificial neural networks to quickly and accurately sift through large corpora of academic texts and classify them to distinct topics. As an example, we explored the use of the word reintroduction in academic texts. Reintroduction is used within the conservation context to indicate the release of organisms to their former native habitat; however, a Web of Science search for this word returned thousands of publications in which the term has other meanings and contexts. Using our method, we automatically classified a sample of 3000 of these publications with over 99% accuracy, relative to a manual classification. Our approach can be used easily with other homonyms and can greatly facilitate systematic reviews or similar work in which homonyms hinder the harnessing of large text corpora. Beyond homonyms we see great promise in combining automated content analysis and machine-learning methods to handle and screen big data for relevant information in conservation science. © 2017 Society for Conservation Biology.

Broadening health policy education in medical school

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Nur A

2018-02-01

Full Text Available Ahmed Nur, Aqib Chaudry, Amar SodhaFaculty of Medicine, Imperial College London, London, UKWe read with great interest the article by Malik et al1 exploring medical studentparticipation in health policy roles. As medical students who recently completed anintercalated degree in healthcare management at Imperial College London, we spent alarge proportion of our time learning about health policy. Thus, we can offer a uniqueperspective on this issue.    We firstly commend the authors for identifying factors that act as barriers to medical student involvement in health policy roles. Noteworthy barriers impacting student involvement included: a lack of knowledge regarding health policy, an unawareness of opportunities available, and a lack of time. It was found that 43% identified lack of time as a barrier to their involvement in health policy.1 Bicket et al similarly found that time commitments and opportunity costs were the main drawbacks for students not pursuing their interests in leadership roles in medical school.2View the original paper by Malik and colleagues.

Extraction of events and rules of land use/cover change from the policy text

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Lin, Guangfa; Xia, Beicheng; Huang, Wangli; Jiang, Huixian; Chen, Youfei

2007-06-01

The database of recording the snapshots of land parcels history is the foundation for the most of the models on simulating land use/cover change (LUCC) process. But the sequences of temporal snapshots are not sufficient to deduce and describe the mechanism of LUCC process. The temporal relationship between scenarios of LUCC we recorded could not be transfer into causal relationship categorically, which was regarded as a key factor in spatial-temporal reasoning. The proprietor of land parcels adapted themselves to the policies from governments and the change of production market, and then made decisions in this or that way. The occurrence of each change of a land parcel in an urban area was often related with one or more decision texts when it was investigated on the local scale with high resolution of the background scene. These decision texts may come from different sections of a hierarchical government system on different levels, such as villages or communities, towns or counties, cities, provinces or even the paramount. All these texts were balance results between advantages and disadvantages of different interest groups. They are the essential forces of LUCC in human dimension. Up to now, a methodology is still wanted for on how to express these forces in a simulation system using GIS as a language. The presented paper was part of our initial research on this topic. The term "Event" is a very important concept in the frame of "Object-Oriented" theory in computer science. While in the domain of temporal GIS, the concept of event was developed in another category. The definitions of the event and their transformation relationship were discussed in this paper on three modeling levels as real world level, conceptual level and programming level. In this context, with a case study of LUCC in recent 30 years in Xiamen city of Fujian province, P. R. China, the paper focused on how to extract information of events and rules from the policy files collected and integrate

The invention of a new language of competence – a necessary tool for a lifelong learning policy

DEFF Research Database (Denmark)

Olesen, Henning Salling

2014-01-01

The invention of a new language of competence – a necessary tool for a lifelong learning policy. In order to obtain the ambitions of a real lifelong learning it is a crucial challenge to develop a new language of competence which can make validation independent of traditional academic curricula...... to societal practice, which involves something more than abstract cognitive knowledge. However, it is more difficult to specify theoretically the “non-cognitive” psycho-social prerequisites - and perhaps it is also politically tricky because it is in part a question of active involvement in and acceptance...

The development of accessibility indicators for distance learning programs

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Sheryl Burgstahler

2006-12-01

Full Text Available A study was undertaken to explore program policies and practices related to the accessibility of American distance learning courses to qualified students with disabilities. A literature review was conducted, a draft list of accessibility indicators was created, examples of applications of the indicators in existing distance learning programs were collected, the indicators were systematically applied to one distance learning program, input from a variety of distance learning programs was used to further refine the indicators, and these programs were encouraged to adopt the indicators and make use of resources provided by the project. Results of this exploratory work suggest that incorporating accessibility considerations into policies, procedures and communications of a program requires consideration of the unique needs of students, course designers, instructors and evaluators; involves approval and implementation at a variety of administrative levels; and is an ongoing process that may be implemented in incremental steps.

Combining machine learning, crowdsourcing and expert knowledge to detect chemical-induced diseases in text.

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Bravo, Àlex; Li, Tong Shu; Su, Andrew I; Good, Benjamin M; Furlong, Laura I

2016-01-01

Drug toxicity is a major concern for both regulatory agencies and the pharmaceutical industry. In this context, text-mining methods for the identification of drug side effects from free text are key for the development of up-to-date knowledge sources on drug adverse reactions. We present a new system for identification of drug side effects from the literature that combines three approaches: machine learning, rule- and knowledge-based approaches. This system has been developed to address the Task 3.B of Biocreative V challenge (BC5) dealing with Chemical-induced Disease (CID) relations. The first two approaches focus on identifying relations at the sentence-level, while the knowledge-based approach is applied both at sentence and abstract levels. The machine learning method is based on the BeFree system using two corpora as training data: the annotated data provided by the CID task organizers and a new CID corpus developed by crowdsourcing. Different combinations of results from the three strategies were selected for each run of the challenge. In the final evaluation setting, the system achieved the highest Recall of the challenge (63%). By performing an error analysis, we identified the main causes of misclassifications and areas for improving of our system, and highlighted the need of consistent gold standard data sets for advancing the state of the art in text mining of drug side effects.Database URL: https://zenodo.org/record/29887?ln¼en#.VsL3yDLWR_V. © The Author(s) 2016. Published by Oxford University Press.

Learners' Use of Communication Strategies in Text-Based and Video-Based Synchronous Computer-Mediated Communication Environments: Opportunities for Language Learning

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Hung, Yu-Wan; Higgins, Steve

2016-01-01

This study investigates the different learning opportunities enabled by text-based and video-based synchronous computer-mediated communication (SCMC) from an interactionist perspective. Six Chinese-speaking learners of English and six English-speaking learners of Chinese were paired up as tandem (reciprocal) learning dyads. Each dyad participated…

Critical Factors of E-Learning Adoption and Acceptance in Pakistan: A Literature Review

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F. Kanwal

2017-08-01

Full Text Available This review paper examines the prior studies on critical factors of e-learning adoption in Pakistan. The search terms identified 40 papers reporting 25 conceptual and qualitative and 15 quantitative evidence about the e-learning adoption and critical factors that may influence the adoption of e-learning in Pakistan. The findings revealed that modern paradigm shift requires the in-depth analysis of government policies, institutional and management role, students and faculty attitude, social norms, cultural values as well as technological advancement. These factors may directly or indirectly affect the intention of students towards e-learning adoption. The lack of quantitative evidences illustrate that policy makers, practitioners and researchers need to pay attention for further research of identifying and analyzing the critical factors which enhances the e-learning adoption in Pakistan.

Audio-visual synchronization in reading while listening to texts: Effects on visual behavior and verbal learning

OpenAIRE

Gerbier , Emilie; Bailly , Gérard; Bosse , Marie-Line

2018-01-01

International audience; Reading while listening to texts (RWL) is a promising way to improve the learning benefits provided by a reading experience. In an exploratory study, we investigated the effect of synchronizing the highlighting of words (visual) with their auditory (speech) counterpart during a RWL task. Forty French children from 3rd to 5th grade read short stories in their native language while hearing the story spoken by a narrator. In the non-synchronized (S-) condition the text wa...

Perspectives on learning to cook and public support for cooking education policies in the United States: A mixed methods study.

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Wolfson, Julia A; Frattaroli, Shannon; Bleich, Sara N; Smith, Katherine Clegg; Teret, Stephen P

2017-01-01

Declines in cooking skills in the United States may contribute to poor diet quality and high obesity rates. Little is known about how Americans learn to cook or their support for cooking education policies. The objective of this study was to examine how Americans learn to cook, attributions of responsibility for teaching children how to cook, and public support for policies to teach cooking skills. We used a concurrent, triangulation mixed-methods design that combined qualitative focus group data (from 7 focus groups in Baltimore, MD (N = 53)) with quantitative survey data from a nationally representative, web-based survey (N = 1112). We analyzed focus group data (using grounded theory) and survey data (using multivariable logistic regression). We find that relatively few Americans learn to cook from formal instruction in school or community cooking classes; rather, they primarily learn from their parents and/or by teaching themselves using cookbooks, recipe websites or by watching cooking shows on television. While almost all Americans hold parents and other family members responsible for teaching children how to cook, a broad majority of the public supports requiring cooking skills to be taught in schools either through existing health education (64%) or through dedicated home economics courses (67%). Slightly less than half of all Americans (45%) support increasing funding for cooking instruction for participants in the Supplemental Nutrition Assistance Program (SNAP). Broad public support for teaching cooking skills in schools suggests that schools are one promising avenue for policy action. However, school-based strategies should be complemented with alternatives that facilitate self-learning. More research is needed to identify effective means of teaching and disseminating the key cooking skills and knowledge that support healthy eating. Copyright © 2016 Elsevier Ltd. All rights reserved.

SAIL: Summation-bAsed Incremental Learning for Information-Theoretic Text Clustering.

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Cao, Jie; Wu, Zhiang; Wu, Junjie; Xiong, Hui

2013-04-01

Information-theoretic clustering aims to exploit information-theoretic measures as the clustering criteria. A common practice on this topic is the so-called Info-Kmeans, which performs K-means clustering with KL-divergence as the proximity function. While expert efforts on Info-Kmeans have shown promising results, a remaining challenge is to deal with high-dimensional sparse data such as text corpora. Indeed, it is possible that the centroids contain many zero-value features for high-dimensional text vectors, which leads to infinite KL-divergence values and creates a dilemma in assigning objects to centroids during the iteration process of Info-Kmeans. To meet this challenge, in this paper, we propose a Summation-bAsed Incremental Learning (SAIL) algorithm for Info-Kmeans clustering. Specifically, by using an equivalent objective function, SAIL replaces the computation of KL-divergence by the incremental computation of Shannon entropy. This can avoid the zero-feature dilemma caused by the use of KL-divergence. To improve the clustering quality, we further introduce the variable neighborhood search scheme and propose the V-SAIL algorithm, which is then accelerated by a multithreaded scheme in PV-SAIL. Our experimental results on various real-world text collections have shown that, with SAIL as a booster, the clustering performance of Info-Kmeans can be significantly improved. Also, V-SAIL and PV-SAIL indeed help improve the clustering quality at a lower cost of computation.

"What is relevant in a text document?": An interpretable machine learning approach.

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Leila Arras

Full Text Available Text documents can be described by a number of abstract concepts such as semantic category, writing style, or sentiment. Machine learning (ML models have been trained to automatically map documents to these abstract concepts, allowing to annotate very large text collections, more than could be processed by a human in a lifetime. Besides predicting the text's category very accurately, it is also highly desirable to understand how and why the categorization process takes place. In this paper, we demonstrate that such understanding can be achieved by tracing the classification decision back to individual words using layer-wise relevance propagation (LRP, a recently developed technique for explaining predictions of complex non-linear classifiers. We train two word-based ML models, a convolutional neural network (CNN and a bag-of-words SVM classifier, on a topic categorization task and adapt the LRP method to decompose the predictions of these models onto words. Resulting scores indicate how much individual words contribute to the overall classification decision. This enables one to distill relevant information from text documents without an explicit semantic information extraction step. We further use the word-wise relevance scores for generating novel vector-based document representations which capture semantic information. Based on these document vectors, we introduce a measure of model explanatory power and show that, although the SVM and CNN models perform similarly in terms of classification accuracy, the latter exhibits a higher level of explainability which makes it more comprehensible for humans and potentially more useful for other applications.

Regional cluster policies: learning by comparing?

NARCIS (Netherlands)

Hospers, Gerrit J.; Beugelsdijk, Sjoerd

2002-01-01

This paper deals with an intriguing paradox that can be observed in today’s regional economic policy making: whereas unique local factors are increasingly seen as the determinants of regional economic success, simultaneously more and more governments try to copy policy experiences that proved to be

Is an Illustration Always Worth Ten Thousand Words? Effects of Prior Knowledge, Learning Style and Multimedia Illustrations on Text Comprehension.

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Ollerenshaw, Alison; Aidman, Eugene; Kidd, Garry

1997-01-01

This study examined comprehension in four groups of undergraduates under text only, multimedia, and two diagram conditions of text supplementation. Results indicated that effects of text supplementation are mediated by prior knowledge and learning style: multimedia appears more beneficial to surface learners with little prior knowledge and makes…

Policy Incentives for the Adoption of Electric Vehicles across Countries

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Xingping Zhang

2014-11-01

Full Text Available Electric vehicles (EVs have prominent advantages for reducing CO2 emissions and alleviating the dependence on fossil fuel consumption in the transport sector. Therefore, many countries have set targets for EV development in recent years and have employed a number of policies to achieve environmental objectives and alleviate the energy pressure. Despite the fact that the adoption of EVs has increased in the past few years, more policies, such as financial incentives, technology support or charging infrastructure, should be made by governments to promote broader range use of EVs. In this paper, we review the relevant policies that different countries may adopt for stimulating the market of EVs. Based on this, we analyze the relationship between the policies and the adoption of EVs by taking America as an example. In conclusion, some effective policies are summarized to spur the market. Therefore, each country should learn from each other and employ effective policies based on the actual situation.

Policy learning and policy change: Theorizing their relations from different perspectives

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S. Moyson (Stéphane); P.W.A. Scholten (Peter); Weible, C.M. (Christopher M.)

2017-01-01

textabstractAll politics and policy issues involve the accumulation of data about problems and solutions in context of social interactions. Drawing on these data, policy actors acquire, translate, and disseminate new information and knowledge toward achieving political endeavors and for revising or

“Have policy makers erred?” Implications of mother tongue education for preprimary schooling in Uganda

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Ssentanda, Medadi Erisa

2014-12-01

Full Text Available The Uganda language-in-education policy is silent about pre-primary schooling. This level of education is largely in the hands of private individuals who, because of wide-spread misconceptions about learning and acquiring English in Uganda (as in many other African countries, instruct pre-primary school learners in English. This article demonstrates how this omission in language-in-education policy is creating competition between rural government and private schools regarding the teaching of English and the development of initial literacy. The absence of an official language policy for pre-primary schooling has also dichotomised the implementation of mother tongue education in rural areas. The policy allows rural primary schools to use mother tongue as language of learning and teaching in the first three school grades. However, whereas private schools instruct through English only, government schools to a large extent adhere to the policy, albeit with undesirable consequences. The practical implications of lack of a language-in-education policy for and minimal government involvement in pre-primary schooling are discussed in this article.

Comprehension of texts in Digital Format versus Printed Texts and Self-Regulated Learning in University Students

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Paula Gabriela Flores-Carrasco

2016-12-01

Full Text Available This article aims (1 to describe the levels of self-regulation and reading comprehension of scientific expository texts; (2 to establish the relationship between self-regulation and reading comprehension; and (3 to compare the performance in comprehension when the printed media (paper or digital media (computer is used. A quasi-experimental, quantitative, descriptive and correlative design was implemented. The sample was composed of 55 university students from four careers of Education; they were in 1st and 3rd year of study at a regional university of the Council of Rectors of Chilean Universities. Three measuring instruments were used: a questionnaire of self-regulated learning and two comprehension tests based on the understanding of Parodi’s (2005 assessment model. The implementation was made in two consecutive moments; first, the self-questionnaire; then, the tests for reading comprehension in both media. With the data obtained, statistical tests of variance, one-way ANOVA, Pearson’s correlation, and means comparison with Bruner and Munzel and U-Mann Whitney’s tests were calculated. In conclusion, and different from the initial statement, it was obtained that university students have an adequate level of self-regulation and low reading comprehension in both data, even the scores are relatively lower in digital data. In both data the output is inverse to the complexity of the questions. Between 1st and 3rd year, there is no increase either in the self-regulation or in reading comprehension; but, exceptionally, the career of Primary General Education specialist on Language and History did. There is a strong relationship between reading comprehension in printed media and self-regulation (ARATEX. The support does not affect reading comprehension, but individual reading skills of the subjects do. A competent reader will have similar performance in both reading supports.

Could a multimodal dictionary serve as a learning tool? An examination of the impact of technologically enhanced visual glosses on L2 text comprehension

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Takeshi Sato

2016-09-01

Full Text Available This study examines the efficacy of a multimodal online bilingual dictionary based on cognitive linguistics in order to explore the advantages and limitations of explicit multimodal L2 vocabulary learning. Previous studies have examined the efficacy of the verbal and visual representation of words while reading L2 texts, concluding that it facilitates incidental word retention. This study explores other potentials of multimodal L2 vocabulary learning: explicit learning with a multimodal dictionary could enhance not only word retention, but also text comprehension; the dictionary could serve not only as a reference tool, but also as a learning tool; and technology-enhanced visual glosses could facilitate deeper text comprehension. To verify these claims, this study investigates the multimodal representations’ effects on Japanese students learning L2 locative prepositions by developing two online dictionaries, one with static pictures and one with animations. The findings show the advantage of such dictionaries in explicit learning; however, no significant differences are found between the two types of visual glosses, either in the vocabulary or in the listening tests. This study confirms the effectiveness of multimodal L2 materials, but also emphasizes the need for further research into making the technologically enhanced materials more effective.

Learning about “wicked” problems in the Global South. Creating a film-based learning environment with “Visual Problem Appraisal”

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Loes Witteveen

2012-03-01

Full Text Available The current complexity of sustainable development in the Global South calls for the design of learning strategies that can deal with this complexity. One such innovative learning strategy, called Visual Problem Appraisal (VPA, is highlighted in this article. The strategy is termed visual as it creates a learning environment that is film-based. VPA enhances the analysis of complex issues, and facilitates stakeholder dialogue and action planning. The strategy is used in workshops dealing with problem analysis and policy design, and involves the participants “meeting” stakeholders through filmed narratives. The article demonstrates the value of using film in multi stakeholder learning environments addressing issues concerning sustainable development.

Applications of Speech-to-Text Recognition and Computer-Aided Translation for Facilitating Cross-Cultural Learning through a Learning Activity: Issues and Their Solutions

Science.gov (United States)

Shadiev, Rustam; Wu, Ting-Ting; Sun, Ai; Huang, Yueh-Min

2018-01-01

In this study, 21 university students, who represented thirteen nationalities, participated in an online cross-cultural learning activity. The participants were engaged in interactions and exchanges carried out on Facebook® and Skype® platforms, and their multilingual communications were supported by speech-to-text recognition (STR) and…

Place as Text: Approaches to Active Learning. 2nd Edition. National Collegiate Honors Council Monograph Series

Science.gov (United States)

Braid, Bernice, Ed.; Long, Ada, Ed.

2010-01-01

The decade since publication of "Place as Text: Approaches to Active Learning" has seen an explosion of interest and productivity in the field of experiential education. This monograph presents a story of an experiment and a blueprint of sorts for anyone interested in enriching an existing program or willing to experiment with pedagogy…

Differences in Strategy Use in the Reading Comprehension of Narrative and Science Texts among Students with and without Learning Disabilities

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Botsas, George

2017-01-01

The aim of the study was to investigate differences in cognitive and metacognitive strategy use in the reading comprehension of narrative and expository texts among students with learning disabilities (SLD) and without learning disabilities (SWOLD). A total of 122 fifth and sixth graders took part in the study. Half of them (n = 61) were SLD…

Understanding policy persistence-The case of police drug detection dog policy in NSW, Australia.

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Hughes, Caitlin E; Ritter, Alison; Lancaster, Kari; Hoppe, Robert

2017-06-01

Significant research attention has been given to understanding the processes of drug policy reform. However, there has been surprisingly little analysis of the persistence of policy in the face of opposition and evidence of ineffectiveness. In this article we analysed just such a case - police drug detection dog policy in NSW, Australia. We sought to identify factors which may account for the continuation of this policy, in spite of counter-evidence and concerted advocacy. The analysis was conducted using the Advocacy Coalition Framework (ACF). We collated documents relating to NSW drug detection dog policy from 1995 to 2016, including parliamentary records (NSW Parliament Hansard), government and institutional reports, legislation, police procedures, books, media, and academic publications. Texts were then read, coded and classified against the core dimensions of the ACF, including subsystem actors and coalitions, their belief systems and resources and venues employed for policy debate. Three coalitions were identified as competing in the policy subsystem: security/law and order, civil liberties and harm reduction. Factors that aided policy stability were the continued dominance of the security/law and order coalition since they introduced the drug dog policy; a power imbalance enabling the ruling coalition to limit when and where the policy was discussed; and a highly adversarial policy subsystem. In this context even technical knowledge that dogs infringed civil liberties and increased risks of overdose were readily downplayed, leading to only incremental changes in implementation rather than policy cessation or wholesale revision. The analysis provides new insights into why the accumulation of new evidence and advocacy efforts can be insufficient to drive significant policy change. It poses a challenge for the evidence-based paradigm suggesting that in highly adversarial policy subsystems new evidence is unlikely to generate policy change without broader

Mobile Message Services Using Text, Audio or Video for Improving the Learning Infrastructure in Higher Education

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Björn Olof Hedin

2006-06-01

Full Text Available This study examines how media files sent to mobile phones can be used to improve education at universities, and describes a prototype implement of such a system using standard components. To accomplish this, university students were equipped with mobile phones and software that allowed teachers to send text-based, audio-based and video-based messages to the students. Data was collected using questionnaires, focus groups and log files. The conclusions were that students preferred to have information and learning content sent as text, rather than audio or video. Text messages sent to phones should be no longer than 2000 characters. The most appreciated services were notifications of changes in course schedules, short lecture introductions and reminders. The prototype showed that this functionality is easy to implement using standard components.

Text mining with R a tidy approach

CERN Document Server

Silge, Julia

2017-01-01

Much of the data available today is unstructured and text-heavy, making it challenging for analysts to apply their usual data wrangling and visualization tools. With this practical book, you'll explore text-mining techniques with tidytext, a package that authors Julia Silge and David Robinson developed using the tidy principles behind R packages like ggraph and dplyr. You'll learn how tidytext and other tidy tools in R can make text analysis easier and more effective. The authors demonstrate how treating text as data frames enables you to manipulate, summarize, and visualize characteristics of text. You'll also learn how to integrate natural language processing (NLP) into effective workflows. Practical code examples and data explorations will help you generate real insights from literature, news, and social media. Learn how to apply the tidy text format to NLP Use sentiment analysis to mine the emotional content of text Identify a document's most important terms with frequency measurements E...

Understanding the United States and Brazil's response to obesity: institutional conversion, policy reform, and the lessons learned.

Science.gov (United States)

Gómez, Eduardo J

2015-06-10

In the United States (US) and Brazil, obesity has emerged as a health epidemic. This article is driven by the following research questions: how did the US and Brazil's federal institutions respond to obesity? And how did these responses affect policy implementation? The aim of this article is therefore to conduct a comparative case study analysis of how these nations' institutions responded in order to determine the key lessons learned. This study uses primary and secondary qualitative data to substantiate causal arguments and factual claims. Brazil shows that converting preexisting federal agencies working in primary healthcare to emphasize the provision of obesity prevention services can facilitate policy implementation, especially in rural areas. Brazil also reveals the importance of targeting federal grant support to the highest obesity prevalence areas and imposing grant conditionalities, while illustrating how the incorporation of social health movements into the bureaucracy facilitates the early adoption of nutrition and obesity policies. None of these reforms were pursued in the US. Brazil's government has engaged in innovative institutional conversion processes aiding its ability to sustain its centralized influence when implementing obesity policy. The US government's adoption of Brazil's institutional innovations may help to strengthen its policy response.

MOBILE LEARNING IN THE FOREIGN LANGUAGE CLASSROOM – CHALLENGES AND OPPORTUNITIES

Directory of Open Access Journals (Sweden)

Diana COJOCNEAN

2017-06-01

Full Text Available The article focuses on how foreign language teachers could use mobile learning in formal and informal learning environments. One of the key aims of the article is the focus on defining the pedagogy of mobile learning in the context of foreign language teaching and learning through the use of mobile learning tools during the foreign language lessons but also in informal learning contexts, encouraging learner autonomy and involvement in the learning task. Thus, the article presents how language teachers could try mobile learning based activities during foreign language lessons and outside the class, using students’ own devices through the implementation of a Bring Your Own Device Policy (BYOD within foreign language lessons.

A MODEL OF DISCOVERY LEARNING BASED - TEXT BOOK OF CHARACTER AND ISLAMIC EDUCATION : AN ACCURACY ANALYSIS OF STUDENT BOOK IN ELEMENTARY SCHOOL

Directory of Open Access Journals (Sweden)

Fadriati Fadriati

2018-05-01

Full Text Available This study aims at developing a valid discovery-learning text book for the Islamic Education (PAI and Character subject delivered at the fifth grade of Primary School based on the results of the accuracy analysis of the existing student books. This is a Research and Development (R and D applying the 4-D model proposed by Semmel and Thiagarajan, that is, defining, designing, developing, and disseminating. Data collection techniques used (1 instrument assessment with the format of student book analysis to measure the level of accuracy of the existing textbooks, (2 interviews and observations, conducted to the PAI teachers, and (3 validation sheets. Moreover, the technique of data analysis used inter rater analysis technique, known as the technique of intra class correlation coefficient analysis (Intraclass Correlation Coefficient-ICC. As the result, in terms of level of accuracy, the existing textbooks of Character and Islamic Education at the fifth grade of elementary school is still low. In general, the teachers claim that the existing text books are able to meet some of the basic competencies and indicators. However, the text books need to be refined and clarified the student learning activities, making it more simple for students to learn. On the other hand, the product of discovery learning textbooks on the subjects of Character and Islamic Education  at the fifth grade of elementary school are declared valid. This product is refined based on input, making it feasible for the students at the fifth grade of Primary School in learning Character and Islamic Education.

Concept mapping and text writing as learning tools in problem-oriented learning

NARCIS (Netherlands)

Fürstenau, B.; Kneppers, L.; Dekker, R.; Cañas, A.J.; Novak, J.D.; Vanhaer, J.

2012-01-01

In two studies we investigated whether concept mapping or summary writing better support students while learning from authentic problems in the field of business. We interpret concept mapping and summary writing as elaboration tools aiming at helping students to understand new information, and to

From Self-Regulation to Learning to Learn: Observations on the Construction of Self and Learning

Science.gov (United States)

Thoutenhoofd, Ernst D.; Pirrie, Anne

2015-01-01

The purpose of this article is to clarify the epistemological basis of self-regulated learning. The authors note that learning to learn, a term that has pervaded education policy at EU and national levels in recent years is often conflated with self-regulated learning. As a result, there has been insufficient attention paid to learning as social…

A Study of the Relationship between Institutional Policy, Organisational culture and E-Learning Use in Four South African Universities

Science.gov (United States)

Czerniewicz, Laura; Brown, Cheryl

2009-01-01

This article investigates the relationship between policy (conceptualised as goals, values and resources), organisational culture and e-learning use. Through both qualitative and quantitative research methods, we gathered data about staff and student perspectives from four diverse South African universities representing a selection of ICT in…

E-LEARNING AND LIFELONG LEARNING

Directory of Open Access Journals (Sweden)

George S. MOUZAKITIS

2011-01-01

Full Text Available It is supported that the object of education is to provide results. Hence, it is of crucial importance to economic development globally. In our era, globalization is a highly disputable event with strong persuasive arguments and equally solid disagreements. The impact of globalization in our everyday activities has been increased. In parallel, technological developments have contributed considerably to dramatic changes in economic, social and educational sectors. Globalization trends and technological developments demand from enterprises and educational organizations innovative ways of business practices and educational delivery in order to cope with the real market demands. Educational planners and policy makers have been trying to design new curricula in an attempt to adequately prepare the workforce to meet the current market requirements. Yet, the anticipated results have not been attained mainly because traditional educational systems proved to be inadequate to link the supply of knowledge and skills with the contemporary needs. This paper will connect e-learning educational/training courses delivery with lifelong learning (LLL. It will further analyze certain factors from the professional and educational point of view and provide recommendations on how to accelerate the implementation of LLL supported by e-learning.

Enablers and constrainers to participation: Has policy in Nordic countries reached its limit for raising participation in adult learning among certain groups? Paper presented (with R. Desjardins) at the II Nordic conference on Adult Learning, Linköping, Sweden, 17-19 April

DEFF Research Database (Denmark)

Milana, Marcella; Desjardins, Richard

barriers to participation, and ensure that disadvantaged groups have equal opportunity to take up adult learning. Together, observations indicate that policy matters in promoting adult learning, especially among adults that would otherwise not participate. At the same time the observations indicate......Despite comparatively high and equal participation in adult learning in Nordic countries, a distinct pattern of non-participation persists. Moreover, the pattern of adults who tend to participate comparatively less often is similar to the non-Nordic countries considered, although it is less...... accentuated. The Nordic countries have a long shared history of supporting and fostering a rich adult learning culture. Although various historical, social and cultural factors are behind this, Nordic countries also share a strong record of public policy that aims to: promote adult learning, target various...

Not Deep Learning but Autonomous Learning of Open Innovation for Sustainable Artificial Intelligence

Directory of Open Access Journals (Sweden)

JinHyo Joseph Yun

2016-08-01

Full Text Available What do we need for sustainable artificial intelligence that is not harmful but beneficial human life? This paper builds up the interaction model between direct and autonomous learning from the human’s cognitive learning process and firms’ open innovation process. It conceptually establishes a direct and autonomous learning interaction model. The key factor of this model is that the process to respond to entries from external environments through interactions between autonomous learning and direct learning as well as to rearrange internal knowledge is incessant. When autonomous learning happens, the units of knowledge determinations that arise from indirect learning are separated. They induce not only broad autonomous learning made through the horizontal combinations that surpass the combinations that occurred in direct learning but also in-depth autonomous learning made through vertical combinations that appear so that new knowledge is added. The core of the interaction model between direct and autonomous learning is the variability of the boundary between proven knowledge and hypothetical knowledge, limitations in knowledge accumulation, as well as complementarity and conflict between direct and autonomous learning. Therefore, these should be considered when introducing the interaction model between direct and autonomous learning into navigations, cleaning robots, search engines, etc. In addition, we should consider the relationship between direct learning and autonomous learning when building up open innovation strategies and policies.

A novel multi-agent decentralized win or learn fast policy hill-climbing with eligibility trace algorithm for smart generation control of interconnected complex power grids

International Nuclear Information System (INIS)

Xi, Lei; Yu, Tao; Yang, Bo; Zhang, Xiaoshun

2015-01-01

Highlights: • Proposing a decentralized smart generation control scheme for the automatic generation control coordination. • A novel multi-agent learning algorithm is developed to resolve stochastic control problems in power systems. • A variable learning rate are introduced base on the framework of stochastic games. • A simulation platform is developed to test the performance of different algorithms. - Abstract: This paper proposes a multi-agent smart generation control scheme for the automatic generation control coordination in interconnected complex power systems. A novel multi-agent decentralized win or learn fast policy hill-climbing with eligibility trace algorithm is developed, which can effectively identify the optimal average policies via a variable learning rate under various operation conditions. Based on control performance standards, the proposed approach is implemented in a flexible multi-agent stochastic dynamic game-based smart generation control simulation platform. Based on the mixed strategy and average policy, it is highly adaptive in stochastic non-Markov environments and large time-delay systems, which can fulfill automatic generation control coordination in interconnected complex power systems in the presence of increasing penetration of decentralized renewable energy. Two case studies on both a two-area load–frequency control power system and the China Southern Power Grid model have been done. Simulation results verify that multi-agent smart generation control scheme based on the proposed approach can obtain optimal average policies thus improve the closed-loop system performances, and can achieve a fast convergence rate with significant robustness compared with other methods

Globalisation, Transnational Policies and Adult Education

Science.gov (United States)

Milana, Marcella

2012-01-01

Globalisation, transnational policies and adult education--This paper examines policy documents produced by the United Nations Educational, Scientific and Cultural Organization (UNESCO) and the European Union (EU) in the field of adult education and learning. Both these entities address adult education as an explicit object of policy. This paper…

Jump-Starting Early Childhood Education at Home: Early Learning, Parent Motivation, and Public Policy.

Science.gov (United States)

Maloney, Erin A; Converse, Benjamin A; Gibbs, Chloe R; Levine, Susan C; Beilock, Sian L

2015-11-01

By the time children begin formal schooling, their experiences at home have already contributed to large variations in their math and language development, and once school begins, academic achievement continues to depend strongly on influences outside of school. It is thus essential that educational reform strategies involve primary caregivers. Specifically, programs and policies should promote and support aspects of caregiver-child interaction that have been empirically demonstrated to boost early learning and should seek to impede "motivational sinkholes" that threaten to undermine caregivers' desires to engage their children effectively. This article draws on cognitive and behavioral science to detail simple, low-cost, and effective tools caregivers can employ to prepare their children for educational success and then describes conditions that can protect and facilitate caregivers' motivation to use those tools. Policy recommendations throughout focus on using existing infrastructure to more deeply engage caregivers in effective early childhood education at home. © The Author(s) 2015.

Learning to Run challenge solutions: Adapting reinforcement learning methods for neuromusculoskeletal environments

OpenAIRE

Kidziński, Łukasz; Mohanty, Sharada Prasanna; Ong, Carmichael; Huang, Zhewei; Zhou, Shuchang; Pechenko, Anton; Stelmaszczyk, Adam; Jarosik, Piotr; Pavlov, Mikhail; Kolesnikov, Sergey; Plis, Sergey; Chen, Zhibo; Zhang, Zhizheng; Chen, Jiale; Shi, Jun

2018-01-01

In the NIPS 2017 Learning to Run challenge, participants were tasked with building a controller for a musculoskeletal model to make it run as fast as possible through an obstacle course. Top participants were invited to describe their algorithms. In this work, we present eight solutions that used deep reinforcement learning approaches, based on algorithms such as Deep Deterministic Policy Gradient, Proximal Policy Optimization, and Trust Region Policy Optimization. Many solutions use similar ...

A study on the role of influence group in public policy making

Directory of Open Access Journals (Sweden)

Abbas Monavarian

2014-09-01

Full Text Available Nowadays, learning more about influence groups on public policy making is one of most important subjects of management science. Governments are the primary sources for public policy making but influenced groups participate indirectly and while they remain out of power, they put pressure on many decisions. Some of participants in public policy making are not influenced groups but mostly, due to their participation in policy public making matter are called influenced groups. This research, from practical research purpose and method view, is a descriptive research and survey branch. The study investigates the effect of university based Iranian Sociological Association on public policy making. The study designs a questionnaire in Likert scale and distributes it among some experts. The results of our survey indicate that that Iranian Sociological Association could influence on public policy making through elite and prominent leaders, self-knowledge and information, elective campaigns, stimulation and connecting with people and other groups.

La rivoluzione dei MOOCs: un'analisi di policy framework su scala europea / The MOOCs’ (Revolution. A policy framework analysis at a European level

Directory of Open Access Journals (Sweden)

Rosanna De Rosa Valentina Reda

2013-12-01

Full Text Available Academic institutions all over the world, as well as active stakeholders in the field of education and supporting services, are exploring Moocs to try and understand how learning and teaching environments are changing, the outcomes of such a novelty for different countries and audiences, to what extent the Moocs revolution can represent both a unique opportunity to open up education and a new business model. Born to help universities and academic institutions to innovate pedagogical models, Moocs are developing along different routes. Using a policy framework analysis approach, this article presents the results of a European survey that questioned both public and private stakeholders on Moocs policy design, objectives and expected outcomes.

Effects of Gloss Type on Text Recall and Incidental Vocabulary Learning in Mobile-Assisted L2 Listening

Science.gov (United States)

Çakmak, Fidel; Erçetin, Gülcan

2018-01-01

This study investigates the effects of multimedia glosses on text recall and incidental vocabulary learning in a mobile-assisted L2 listening task. A total of 88 participants with a low level of proficiency in English were randomly assigned to one of four conditions that involved single channel (textual-only, pictorial-only) and dual-channel…

Analysis of the decision-support function of policy assessment in real-world policy making in the field of poverty and social inequalities. Case study on migrant integration policies in the Brussels-Capital Region

International Nuclear Information System (INIS)

Feyaerts, Gille; Deguerry, Murielle; Deboosere, Patrick; De Spiegelaere, Myriam

2017-01-01

Despite its high potential to support decision-making, the role of policy assessment in real-world policy making in the field of poverty and social inequalities remains largely questioned. In this study, we analyse policy assessment's role in a context of real-world policymaking, by means of a case study on a legislative proposal on integration policy for immigrant newcomers in the Brussels-Capital Region, for which we evaluate the potential effects on poverty and social inequalities. We first analyse the policy process surrounding the policy proposal – a process that is often treated as a black box within policy assessment research. Understanding the factors that influence and determine the decision-making process, enables us to gain insight into the potential decision-support function(s). Second, we develop an approach to policy assessment that aims to fully exploit its potential to contribute to the functions of both instrumental and conceptual learning. For this purpose, we propose to introduce the approach of realist evaluation and to focus on evaluating the underlying policy intervention theory from the perspective of poverty and social inequalities. Finally, we illustrate this new approach and its added value by applying it to the legislative proposal on integration policy and analyse its contribution to policy-oriented learning. - Highlights: •The field of policy assessment should draw on insights from policy studies. •We unpacked the policymaking black-box to identify the mechanisms of policy change. •The policy process is driven by an interaction of ideas, interests and institutions. •Policy assessment's potential lies in both instrumental and conceptual learning. •We propose to integrate realist evaluation's logic of inquiry within policy assessment.

Supporting the diffusion of healthy public policy in Canada: the Prevention Policies Directory.

Science.gov (United States)

Politis, Christopher E; Halligan, Michelle H; Keen, Deb; Kerner, Jon F

2014-01-01

Healthy public policy plays an essential role in a comprehensive public health approach to preventing cancer and chronic disease. Public policies spread through the 'policy diffusion' process, enabling governments to learn from another's enacted policy solutions. The Prevention Policies Directory (the Directory), an online database of municipal, provincial/territorial, and federal cancer and chronic disease prevention policies from across Canada, was developed to facilitate the diffusion of healthy public policies and support the work of prevention researchers, practitioners, and policy specialists. This information technology solution was implemented, through a participatory engagement approach, as a communication channel or policy knowledge transfer tool. It also addressed the intrinsic shortcomings of environmental scanning for policy surveillance and monitoring. A combination of quantitative web metrics and qualitative anecdotal evidence have illustrated that the Directory is becoming an important tool for healthy public policy surveillance and policy diffusion in Canada.

Sexual harassment, special relationships and consensual engagement policies within higher learning institutions : a labour law perspective

OpenAIRE

2015-01-01

LL.M. (Labour Law) A university is a community of adults in which close personal relationships between adults can develop. These institutions of higher learning recognise the need for policies prohibiting sexual harassment but few have addressed the subtle issues surrounding consensual and special amorous relationships between academic staff members and students and whether they have the right to regulate private behaviour between adults. The aim of this minor dissertation is to explore th...

VisualUrText: A Text Analytics Tool for Unstructured Textual Data

Science.gov (United States)

Zainol, Zuraini; Jaymes, Mohd T. H.; Nohuddin, Puteri N. E.

2018-05-01

The growing amount of unstructured text over Internet is tremendous. Text repositories come from Web 2.0, business intelligence and social networking applications. It is also believed that 80-90% of future growth data is available in the form of unstructured text databases that may potentially contain interesting patterns and trends. Text Mining is well known technique for discovering interesting patterns and trends which are non-trivial knowledge from massive unstructured text data. Text Mining covers multidisciplinary fields involving information retrieval (IR), text analysis, natural language processing (NLP), data mining, machine learning statistics and computational linguistics. This paper discusses the development of text analytics tool that is proficient in extracting, processing, analyzing the unstructured text data and visualizing cleaned text data into multiple forms such as Document Term Matrix (DTM), Frequency Graph, Network Analysis Graph, Word Cloud and Dendogram. This tool, VisualUrText, is developed to assist students and researchers for extracting interesting patterns and trends in document analyses.

Technology in the Pharmacy Learning Environment: Surveys of Use and Misuse

Directory of Open Access Journals (Sweden)

Kimberley J. Begley

2015-01-01

Full Text Available The use of technology in the classroom may have positive and negative effects on learning. The purpose of this investigation was twofold: to identify the effect technology is having on the pharmacy learning environment; and, to assess students' use of technology during class time for non-academic purposes. This study included a national cross-sectional survey as well as a single, college-specific survey. The national survey had a faculty response rate of 71.2%. Of the responders, approximately 61% identified significant problems related to students' use of technology in the pharmacy learning environment. Cell phones were a recognized concern and more than 90% of programs have chosen to restrict cell phone use in the classroom. The single college survey examining technology use during class for non-academic purposes had a student response rate of 87% and faculty response rate of 100%. Students and faculty members disagreed regarding the negative effects of technology use during class for non-academic purposes. Notably, 16% of students acknowledged their in-class use of technology for non-academic purposes had been disruptive to their learning, as compared to 95.7% of faculty. According to students, common reasons for off-task technology use included checking e-mail/text messages (75.1%, lack of engagement (58.1%, multitasking (56.2%, and accessing social media sites (33%. Faculty and students were asked about enforcement of technology policy. More faculty than students supported policy enforcement by faculty (65.2% versus 22.8%, respectively; p<0.001 as well as policy enforcement by students (78.3% versus 31.9%, respectively; p<0.001. Overall, technology use during class for non-academic purposes was common. Many schools and colleges of pharmacy are developing approaches to address these evolving issues by revising their technology use policies.   Type: Original Research

Sparse Machine Learning Methods for Understanding Large Text Corpora

Data.gov (United States)

National Aeronautics and Space Administration — Sparse machine learning has recently emerged as powerful tool to obtain models of high-dimensional data with high degree of interpretability, at low computational...

The Human Factor: Training and Professional Development as a Policy Tool

Directory of Open Access Journals (Sweden)

Lucian CIOLAN

2014-11-01

Full Text Available In this paper, we try to make a case for the risky approach of many decision-makers and pol- icy specialists to overuse authority and regula- tion-based tools, while neglecting the ones more focused on human capacity and persuasion. Especially in fields like education, we consider that the human factor should be at the core of any policy mix, and a tool like training and pro- fessional development should gain a more visible and persistent role in policy interventions. Firstly, we try to analyze the distribution of policy tools on the authority-complexity axes. The value we see in the mapping of policy tools is that it can be used for investigating and positioning the activity of a specific governing body or central gover- nance. Thus, a fundamental question remains as to what really influences the choice of policy tools or instruments, as a basis for better understand- ing the rationales behind a specific policy mix. We argue that policy failure could be ex- plained in many cases by the incapacity to ad- dress in a consistent and professional way the human capacities needed for implementation. Thus, training and professional development are, at least, poorly used from the perspective of the potential they have. As an argument, we tried to look at training and professional development in the specific area of teachers in pre-university education in Romania, situating it in the broader context of European policies in lifelong learning and participation of adults in continuing educa- tion and training, but also in the local policy en- vironment. The results of the research led us to the conclusion that educational policies should be among the first in the broader spectrum of public policies valuing and emphasizing learning, through training and professional development of the stakeholders involved in policy change together with adding more value to the Human Factor in educational policies. 

Subordinating careers to market forces? A critical analysis of European career guidance policy

Directory of Open Access Journals (Sweden)

Ingela Bergmo-Prvulovic

2012-10-01

Full Text Available This study explores language regarding career and career development in European policy documents on career guidance in order to disclose underlying view(s of these phenomena conveyed in the texts. Qualitative content analysis was used to approach the subject in the texts, followed by a sender-oriented interpretation. Sources for interpretation include several sociological and pedagogical approaches based upon social constructionism. These provide a framework for understanding how different views of career phenomena arise. The characterization of career phenomena in the documents falls into four categories: contextual change, environment-person correspondence, competence mobility, and empowerment. An economic perspective on career dominates, followed by learning and political science perspectives. Policy formulations convey contradictory messages and a form of career 'contract' that appears to subordinate individuals' careers to global capitalism, while attributing sole responsibility for career to individuals.

Keeping it pure – a pedagogical case study of teaching soft systems methodology in scenario and policy analysis

Directory of Open Access Journals (Sweden)

Ian Yeoman

2016-09-01

Full Text Available Purpose – Soft systems methodology (SSM is well documented in the academic and management literature. Over the last 40 years, the methodology has come to be adapted depending on the tool users’ skills and experience in order to fit the problem. The purpose of this paper is to demonstrate good teaching and learning practice from a pedagogical perspective. Design/methodology/approach – Dr Ian Yeoman of Victoria University of Wellington provides a personal reflection of how the methodology is used in the teaching and learning of TOUR301 Tourism Policy and Planning as a policy and scenario analysis method. Findings – The paper articulates the seven stages of SSM from problem situation unstructured, through to Rich Pictures, vision and guiding principles, policy solutions, comparisons, feasibility and implementation stages. The paper uses a series of teaching tasks to breakdown the complexity of the methodology thus guiding students and teachers in how to deploy the methodology in the classroom. Originality/value – The value of the paper demonstrates the reflective practice of SSM in action as an exemplar of good practice. The paper clearly articulates the stages of the methodology so students and teachers can adopt this approach in classroom environments following a scaffolding learning approach. The use of teaching tasks throughout the paper helps bring clarity and order thus enabling the teacher to effectively teach the subject and the students to learn. The most significant contribution of this paper is the articulation of good teaching practice in policy and scenario analysis which articulated through four learning lessons: facilitating a learning environment; the impact of visual thinking; political theory; the importance of incremental learning; and problem-based learning and international students.

Effects of Text Illustrations: A Review of Research.

Science.gov (United States)

Levie, W. Howard; Lentz, Richard

1982-01-01

Reviews results of 55 experiments comparing learning from illustrated text and learning from text alone. Research in closely related fields--nonrepresentational pictures (maps, diagrams, graphic organizers), learner-produced drawings, mental imagery, and oral prose--is also examined, and guidelines for practice are offered. A 160-item reference…

Language policy and language learning in Macedonia Which lessons may be adopted from the Swiss model?

Directory of Open Access Journals (Sweden)

Xhaferri, Gëzim

2014-03-01

Full Text Available The following paper will investigate the acquisition of Macedonian languages in public schools and universities, focusing on the Albanian and Macedonian languages. As the saying goes: "The more languages you speak, the more human you are". Abiding by this proverb, the citizens of the Republic of Macedonia should be encouraged to become multilingual by learning the national languages. The acquisition of the national languages in a multilingual, multiethnic and multicultural country like Macedonia is, in my opinion, a necessary step toward the establishment of smooth and peaceful communication between the country's two largest cultural groups (Macedonians and Albanians, and is therefore also a prerequisite for the successful integration of every citizen into their home country's society. This paper also investigates Switzerland's multilingual and multicultural society, which serves as a successful and positive example of how a nation can deal with a multilingual population and the integration of its population. With this in mind, the question is raised here whether the model of Switzerland's language policy and national language instruction can perhaps also serve as an example for the Republic of Macedonia.

Design to learn: customizing services when the future matters

Directory of Open Access Journals (Sweden)

Dan Ariely

2013-04-01

Full Text Available Internet-based customization tools can be used to design service encounters that maximize customers' utility in the present or explore their tastes to provide more value in the future, where these two goals conflict with each other. Maximizing expected customer satisfaction in the present leads to slow rates of learning that may limit the ability to provide quality in the future. An emphasis on learning can lead to unsatisfied customers that will not only forego purchasing in the current period, but, more seriously, never return if they lose trust in the service provider's ability to meet their needs. This paper describes service design policies that balance the objectives of learning and selling by characterizing customer lifetime value as a function of knowledge. The analysis of the customization problem as a dynamic program yields three results. The first result is the characterization of customization policies that quantify the value of knowledge so as to adequately balance the expected revenue of present and future interactions. The second result is an analysis of the impact of operational decisions on loyalty, learning, and profitability over time. Finally, the quantification of the value of knowing the customer provides a connection between customer acquisition and retention policies, thus enhancing the current understanding of the mechanisms connecting service customization, value creation, and customer lifetime value.

Teacher evaluation as a policy target for improved student learning: A fifty-state review of statute and regulatory action since NCLB.

Directory of Open Access Journals (Sweden)

Helen M. Hazi

2009-03-01

Full Text Available This paper reports on the analysis of state statutes and department of education regulations in fifty states for changes in teacher evaluation in use since the passage of No Child Left Behind Act of 2001. We asked what the policy activity for teacher evaluation is in state statutes and department of education regulations, how these changes in statutes and regulations might affect the practice of teacher evaluation, and what were the implications for instructional supervision from these policy actions. Teacher evaluation statutes and department of education regulations provided the data for this study, using archival records from each state's legislature and education departments that were placed into a comparison matrix based on criteria developed from the National Governors Association (NGA goals for school reform (Goldrick, 2002. Data were analyzed deductively in terms of these criteria for underlying theories of action (Malen, 2005, trends, and likely effects on teacher evaluation and implications for supervision. The majority of states adopted many of the NGA strategies, asserted oversight and involvement in local teacher evaluation practices, decreased the frequency of veteran teacher evaluation, and increased the types of data used in evaluation. Whether or not the changes in teacher evaluation will improve student learning in the long run remains to be seen.

Reading to learn experimental practice: The role of text and firsthand experience in the acquisition of an abstract science principle

Science.gov (United States)

Richmond, Erica Kesin

2008-10-01

From the onset of schooling, texts are used as important educational tools. In the primary years, they are integral to learning how to decode and develop fluency. In the later elementary years, they are often essential to the acquisition of academic content. Unfortunately, many children experience difficulties with this process, which is due in large part to their unfamiliarity with the genre of academic texts. The articles presented in this dissertation share an underlying theme of how to develop children's ability to comprehend and learn from academic, and specifically, non-narrative texts. The first article reviews research on the development of non-narrative discourse to elucidate the linguistic precursors to non-narrative text comprehension. The second and third articles draw from an empirical study that investigated the best way to integrate text, manipulation, and first-hand experience for children's acquisition and application of an abstract scientific principle. The scientific principle introduced in the study was the Control of Variables Strategy (CVS), a fundamental idea underlying scientific reasoning and a strategy for designing unconfounded experiments. Eight grade 4 classes participated in the study (N = 129), in one of three conditions: (a) read procedural text and manipulate experimental materials, (b) listen to procedural text and manipulate experimental materials, or (c) read procedural text with no opportunity to manipulate experimental materials. Findings from the study indicate that children who had the opportunity to read and manipulate materials were most effective at applying the strategy to designing and justifying unconfounded experiments, and evaluating written and physical experimental designs; however, there was no effect of instructional condition on a written assessment of evaluating familiar and unfamiliar experimental designs one week after the intervention. These results suggest that the acquisition and application of an abstract

Policy Makers, Information and Learning.

Science.gov (United States)

Beers, Pieter J.; van Asselt, Marjolein B. A.; Vermunt, Jan D.; Kirschner, Paul A.

2003-01-01

Interviews explored the information needs of seven Dutch policymakers dealing with global sustainability. They sought information on cultural perspectives and linkages. Information gathering emphasized filtering to find specific information. Most used an application-oriented working style that, combined with policy-driven information seeking, was…

Private sector involvement in science and innovation policy-making in Hungary

OpenAIRE

Annamária Inzelt

2008-01-01

The overall thrust of this paper is that policy learning is enhanced by the participation of private business. It is assumed that business involvement would suggest abundant opportunities for policy learning and transfer. The empirical part of this paper investigates private sector involvement in science, technology and innovation (STI) policy-making in a transition economy (Hungary). Private sector involvement in Hungarian STI policy-making is investigated in terms of the stages and types of...

Instant Sublime Text starter

CERN Document Server

Haughee, Eric

2013-01-01

A starter which teaches the basic tasks to be performed with Sublime Text with the necessary practical examples and screenshots. This book requires only basic knowledge of the Internet and basic familiarity with any one of the three major operating systems, Windows, Linux, or Mac OS X. However, as Sublime Text 2 is primarily a text editor for writing software, many of the topics discussed will be specifically relevant to software development. That being said, the Sublime Text 2 Starter is also suitable for someone without a programming background who may be looking to learn one of the tools of

Language Policy

DEFF Research Database (Denmark)

Lauridsen, Karen M.

2008-01-01

Like any other text, instructive texts function within a given cultural and situational setting and may only be available in one language. However, the end users may not be familiar with that language and therefore unable to read and understand the instructions. This article therefore argues...... that instructive texts should always be available in a language that is understood by the end users, and that a corporate communication policy which includes a language policy should ensure that this is in fact the case for all instructive texts....

Dopaminergic balance between reward maximization and policy complexity

Directory of Open Access Journals (Sweden)

Naama eParush

2011-05-01

Full Text Available Previous reinforcement-learning models of the basal ganglia network have highlighted the role of dopamine in encoding the mismatch between prediction and reality. Far less attention has been paid to the computational goals and algorithms of the main-axis (actor. Here, we construct a top-down model of the basal ganglia with emphasis on the role of dopamine as both a reinforcement learning signal and as a pseudo-temperature signal controlling the general level of basal ganglia excitability and motor vigilance of the acting agent. We argue that the basal ganglia endow the thalamic-cortical networks with the optimal dynamic tradeoff between two constraints: minimizing the policy complexity (cost and maximizing the expected future reward (gain. We show that this multi-dimensional optimization processes results in an experience-modulated version of the softmax behavioral policy. Thus, as in classical softmax behavioral policies, probability of actions are selected according to their estimated values and the pseudo-temperature, but in addition also vary according to the frequency of previous choices of these actions. We conclude that the computational goal of the basal ganglia is not to maximize cumulative (positive and negative reward. Rather, the basal ganglia aim at optimization of independent gain and cost functions. Unlike previously suggested single-variable maximization processes, this multi-dimensional optimization process leads naturally to a softmax-like behavioral policy. We suggest that beyond its role in the modulation of the efficacy of the cortico-striatal synapses, dopamine directly affects striatal excitability and thus provides a pseudo-temperature signal that modulates the trade-off between gain and cost. The resulting experience and dopamine modulated softmax policy can then serve as a theoretical framework to account for the broad range of behaviors and clinical states governed by the basal ganglia and dopamine systems.

Development Education and Education in International Development Policy: Raising Quality through Critical Pedagogy and Global Skills

Directory of Open Access Journals (Sweden)

Amy Skinner

2013-11-01

Full Text Available Development education is an approach to learning that questions dominant paradigms of development and inspires citizen- and community-driven change towards a world of greater social justice. This article provides an overview of development education and reflects on the extent to which development education principles are currently reflected in, or missing from, mainstream educational policies pursued within an international development framework. In particular, the article addresses the issue of quality in education – one of the key current debates within international education policy – and suggests that, through its critical pedagogy and focus on the development of global skills, development education has a significant contribution to make to these debates. The article suggests that greater collaboration between the field of development education and international education policy could facilitate the creation of an agenda that focuses on education quality and learning processes, as opposed to the current preoccupation with education access and outcomes.

Lessons Learned from the Energy Policies of IEA Countries

Energy Technology Data Exchange (ETDEWEB)

NONE

2009-07-01

This information paper provides policy makers and managers, facing tough energy policy challenges, with a wider perspective of how the same issues are being addressed by different IEA member countries. The topics included are: Government structures for co-ordinating energy and climate policies; The use of long-term energy forecasts and scenarios; and Progress in the delivery of key energy security policies.

Individualism, instrumental reason and policy texts: some considerations from the perspective of contemporary political philosophy

Science.gov (United States)

Vilanova, Rita; Martins, Isabel

2017-12-01

This article dialogues with Matthew Weinstein's paper named "NGSS, disposability, and the ambivalence of Science in/under neoliberalism", in which he explores the argument that at the same time the NGSS framework is largely identified with neoliberal discourse, it presents points of ambivalence and resistance within. In this dialogue, we focused on two topics that we believe are important for the discussion of the ambivalences highlighted in the author's argument, namely: the the social production of indifference as a consequence of the neoliberal ideology and the production of a version of science streamlined for the neoliberal technoscientific job market within the `neoliberal ecosystem'. Based on the thesis of the Canadian philosopher Charles Taylor on ethics and on the concept of hybridism, we linked Weinsteins' analysis to issues related to individualism and instrumental reason, pointing out that it is possible that the ambivalences highlighted by Weinstein are, in fact, a component of neoliberal discourse. Nevertheless we agree that this kind of text presents loopholes that allows practices oriented for social change and for the improvement of democracies in progress. We conclude that for those who dedicate themselves to reflect upon educational strategies to cope with the hegemonic model remains the challenge of finding spaces and times in the curriculum in order to explore the gaps in policy texts and, more important, to promote the experience of democratic practices throughout the school communities.

Prognosis Essay Scoring and Article Relevancy Using Multi-Text Features and Machine Learning

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Arif Mehmood

2017-01-01

Full Text Available This study develops a model for essay scoring and article relevancy. Essay scoring is a costly process when we consider the time spent by an evaluator. It may lead to inequalities of the effort by various evaluators to apply the same evaluation criteria. Bibliometric research uses the evaluation criteria to find relevancy of articles instead. Researchers mostly face relevancy issues while searching articles. Therefore, they classify the articles manually. However, manual classification is burdensome due to time needed for evaluation. The proposed model performs automatic essay evaluation using multi-text features and ensemble machine learning. The proposed method is implemented in two data sets: a Kaggle short answer data set for essay scoring that includes four ranges of disciplines (Science, Biology, English, and English language Arts, and a bibliometric data set having IoT (Internet of Things and non-IoT classes. The efficacy of the model is measured against the Tandalla and AutoP approach using Cohen’s kappa. The model achieves kappa values of 0.80 and 0.83 for the first and second data sets, respectively. Kappa values show that the proposed model has better performance than those of earlier approaches.

Managing urban water crises: adaptive policy responses to drought and flood in Southeast Queensland, Australia

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Brian W. Head

2014-06-01

Full Text Available In this case study, I examine the quality of decision-making under conditions of rapidly evolving urban water crises, and the adaptive policy challenges of building regional resilience in response to both drought and flood. Like other regions of Australia, Southeast Queensland has been subject to substantial cycles of drought and flood. I draw on resilience literature concerning sustainability, together with governance literature on policy change, to explain the changing awareness of urban water crises and the strategic options available for addressing these crises in this case study. The problem of resilience thinking opens up a number of important questions about the efficacy and adaptability of the policy system. The case provides insights into the interplay between the ways in which problems are framed, the knowledge bases required for planning and decision-making, the collaborative governance processes required for managing complex and rapidly evolving issues, and the overall capacity for policy learning over time. Regional resilience was proclaimed as a policy goal by government, but the practices remained largely anchored in traditional technical frameworks. Centralized investment decisions and governance restructures provoked conflict between levels of government, undermining the capacity of stakeholders to create more consensual approaches to problem-solving and limiting the collective learning that could have emerged.

Event Recognition Based on Deep Learning in Chinese Texts.

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Yajun Zhang

Full Text Available Event recognition is the most fundamental and critical task in event-based natural language processing systems. Existing event recognition methods based on rules and shallow neural networks have certain limitations. For example, extracting features using methods based on rules is difficult; methods based on shallow neural networks converge too quickly to a local minimum, resulting in low recognition precision. To address these problems, we propose the Chinese emergency event recognition model based on deep learning (CEERM. Firstly, we use a word segmentation system to segment sentences. According to event elements labeled in the CEC 2.0 corpus, we classify words into five categories: trigger words, participants, objects, time and location. Each word is vectorized according to the following six feature layers: part of speech, dependency grammar, length, location, distance between trigger word and core word and trigger word frequency. We obtain deep semantic features of words by training a feature vector set using a deep belief network (DBN, then analyze those features in order to identify trigger words by means of a back propagation neural network. Extensive testing shows that the CEERM achieves excellent recognition performance, with a maximum F-measure value of 85.17%. Moreover, we propose the dynamic-supervised DBN, which adds supervised fine-tuning to a restricted Boltzmann machine layer by monitoring its training performance. Test analysis reveals that the new DBN improves recognition performance and effectively controls the training time. Although the F-measure increases to 88.11%, the training time increases by only 25.35%.

Candlestick and Faces: Aspects of Lifelong Learning.

Science.gov (United States)

Hunt, Cheryl

1999-01-01

Government policies view lifelong learning in terms of economic development. A SWOT (strengths, weaknesses, opportunities, threats) analysis of the environment of British community education councils revealed other views of lifelong learning: it takes time and political expediency and national policy can adversely affect what and how people learn.…

Validation of non-formal and informal learning from a European perspective – linking validation arrangements with national qualifications frameworks

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Borut Mikulec

2015-12-01

Full Text Available The paper analyses European policy on the validation of non-formal and informal learning, which is presented as a “salvation narrative” that can improve the functioning of the labour market, provide a way out from unemployment and strengthen the competitiveness of the economy. Taking as our starting point recent findings in adult education theory on the validation of non-formal and informal learning, we aim to prove the thesis that what European validation policy promotes is above all economic purpose and that it establishes a “Credential/Credit-exchange” model of validation of non-formal and informal learning. We proceed to ecxamine the effect of European VNIL policy in selected European countries where validation arrangements are linked to the qualifications framework. We find that the “Credential/ Credit-exchange” validation model was first established in a few individual European countries and then transferred, as a “successful” model, to the level of common European VNIL policy.

Fertilizer Reduction Policies in Developed Countries: Suitability and Implications

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LI Fang

2017-01-01

Full Text Available This study reviewed and analyzed the specific practices, implementation effects and applicable conditions of fertilizer reduction policies in the EU, US and Japan, explored the common laws and general conditions in the formulation of environmental orientation, and pro vided feasible policy recommendations for the formulation of fertilizer reduction policies in China. This study showed that fertilizer reduction policies in each country had their own advantages and disadvantages, and the applicable conditions were different. The EU's command and control policy was applicable to the situation of less farm households and the same agricultural planting type or farm type. The economic in centive policy in the US was applicable to the situation of more farm households, relatively perfect agricultural market system and sensitive price formation mechanism, while the public participation policy in Japan was applicable to regions with more relevant agricultural groups and strong economy. China should learn from each of these policies and make a comprehensive choice in the formulation of fertilizer reduc tion policies. Therefore, China should proceed from improving the agricultural price mechanism and the pollution-free agricultural products certification system as well as encouraging and supporting the development of large scale production units, and then promote the adoption of environmentally friendly technology through the guidance of market mechanism, ensure the effective implementation of environmental stan dards through farmers' integration and improve farmers' environmental awareness through propaganda guidance, so as to ensure the effective implementation of different types(command and control policy, economic incentive policy and public participation policyof fertilizer reduc tion policies.

The agricultural policy of Serbia and common agricultural policy

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Stanković Milica

2012-01-01

Full Text Available The agricultural sector has a relatively high importance in the economic structure of Serbia. The Common Agricultural Policy (CAP, Common Agricultural Policy is one of the main policies of the European Union. It is very important to point out the fundamental principles and objectives of the Common Agricultural Policy. Harmonization of the national agricultural policy of Serbia with the Common Agricultural Policy and acceptance of its mechanisms is crucial for the development of the agricultural sector as a whole.

Innovation in Health Policy Education: Project-Based Service Learning at a Distance for Graduate Midwifery Students.

Science.gov (United States)

Van Hoover, Cheri

2015-01-01

Core competencies for midwifery practice include an understanding of systems of health care delivery and advocacy for legislation and policy initiatives that promote quality in health care. Today's rapidly changing health care environment, due in part to the implementation of the Patient Protection and Affordable Care Act, mandates that midwives possess greater literacy in health policy and comfort with political action than ever before. Frequently disinterested in politics and intimidated by the policymaking process, student midwives lack the foundational knowledge and practical skills needed to meet this professional obligation. The Midwifery Institute of Philadelphia University graduate program educates both student nurse-midwives and student midwives in health policy using an innovative, project-based service-learning approach featuring real-world collaborative experiences. This novel teaching style is ideally suited for instruction at a distance because of the diversity of experience brought to the virtual classroom by students in widely disparate geopolitical locations. As students accomplish measurable objectives within their individually developed projects and reflect with classmates about their experiences, they feel empowered to effect change and report lower perceived barriers to future political engagement. © 2015 by the American College of Nurse-Midwives.

Machine learning versus knowledge based classification of legal texts

NARCIS (Netherlands)

de Maat, E.; Krabben, K.; Winkels, R.; Winkels, R.G.F.

2010-01-01

This paper presents results of an experiment in which we used machine learning (ML) techniques to classify sentences in Dutch legislation. These results are compared to the results of a pattern-based classifier. Overall, the ML classifier performs as accurate (>90%) as the pattern based one, but

SparkText: Biomedical Text Mining on Big Data Framework.

Science.gov (United States)

Ye, Zhan; Tafti, Ahmad P; He, Karen Y; Wang, Kai; He, Max M

Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research.

WHEN SENSING TEACHES MORE THAN TEXT BOOKS: REVITALIZING TEAM, ICT AND OBSERVATIONAL LEARNING TO THRIVE SOCIO-AFFECTIVE CONSCIOUSNESS IN LANGUAGE CLASSROOM

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Adi Suryani

2017-04-01

Full Text Available The flourish of ICT and complexity of today‘s social-cultural and technological issues entails a strong need for a change in education. Today‘s education should be more directed outward by observing what happens in the society instead of just inward by indoctrinating certain perspectives and memorizing facts. Thus, it is not classroomcentred education anymore, but it is now becoming society-centred and being the miniature of society. Today‘s classrooms are expected to facilitate broader and various learning process, dynamic mental process and provide autonomy and creativity for students to construct their own knowledge by observing, sensing and learning from society. Through this process, students can see society as place and source of learning. Learning from society can also trigger social learning. Together, the aspect of observing issues emerging in society and being able to accommodate various perspectives in jointlearning lay the foundation for creating socio-affective conscious learners. This study aims to explore how and what the students can learn by observing, thinking, feeling and proposing problem solving for social, cultural and technological issues in joint-learning and what challenges they encounter during their learning process. The data is grounded on students‘ reflective notes and the result of collaborated problem solving in groups in language classroom. The data shows that the students learn some constellations of socioaffective learning aspects. Those are the exercises of multiple sensory, social learning (awareness, coordination, affinity, sharing, respect, communication, emotional learning (regulation, awareness, positive emotional contagion in group, adaptive. Their sensory, social and affective learning are enhanced by ICT.

France and Germany nuclear energy policies revisited: A veblenian appraisal

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Petit Pascal

2013-01-01

Full Text Available Nuclear energy policy should have been a major area of cooperation for France and Germany, playing a lead role in the energy policy of the EU. Yet they have retained different options, especially regarding nuclear energy while the EU energy policy remained very indicative. These two “coordinated economies” should have been able to cooperate more closely on this issue. While the reasons for this difference in behavior have much to do with the specificities of the nuclear energy, they are more precisely related to the continuously rising level of security requirements, a learning process in which the magnitude of risks and time lengths appeared, even before Fukushima, to go beyond rational boundaries on which cooperation (as well as market ventures could be based. This raises the issue in the present state of the technologies of the possibility of an international governance of this nuclear industry.

Networking European Universities through e-learning (reviewed text)

OpenAIRE

Dlouhá, Jana

2008-01-01

Virtual Campus for a Sustainable Europe (VCSE) network has been selected to be part of the EC DG EAC Inventory of innovative good practice on education for sustainable development. The main purpose of the Inventory is to show concrete examples which have been implemented in the Member States under the concept of ESD in formal and non-formal learning contexts and which are at the forefront as regards innovative approaches. Projects/programmes selected as innovative good practice will be use...

How to motivate adults with low literacy and numeracy skills to engage and persist in learning: A literature review of policy interventions

Science.gov (United States)

Windisch, Hendrickje Catriona

2016-06-01

Low basic skills levels of adults are a complex policy problem which has neither straightforward causes nor solutions, and successful interventions are still relatively rare. Tackling serious literacy and numeracy weaknesses among adults is challenging, partly because the task itself is difficult, and partly because even if accomplished successfully, the returns on the investment (of expertise, time and money) are uncertain. The Survey of Adult Skills, an international investigation conducted in 22 member and two partner countries of the Organisation for Economic Co-operation and Development (OECD) as part of the Programme for the International Assessment of Adult Competencies (PIAAC), has revealed that a considerable number of adults possess only limited literacy and numeracy skills. Governments now recognise the need to upskill these adults in order to maintain national prosperity. This literature review examines current evidence on policy interventions for adults with low literacy and numeracy proficiencies to pinpoint what has so far proven to motivate adults to join and persist in basic literacy and numeracy learning. The author identifies three approaches which seem promising in helping to address individual learners' needs: (1) adapting instruction to learners' needs by means of regular assessment (formative assessment); (2) complementary e-learning (blended learning); and (3) contextualisation of basic skills provision both at work and at home (workplace learning and family literacy). The central challenge is to put the evidence to work.

Students' Learning Experiences from Didactic Teaching Sessions Including Patient Case Examples as Either Text or Video

DEFF Research Database (Denmark)

Pedersen, Kamilla; Moeller, Martin Holdgaard; Paltved, Charlotte

2017-01-01

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...

Planning and land policy tools for limiting urban sprawl: The example of Belgrade

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Zeković Slavka

2015-01-01

Full Text Available Both the characteristics of Serbia’s urban land policy, the delay in reforms and land development management of the Belgrade Metropolitan Area (BMA illustrate the complexities following the reshaping of institutional framework under the conditions of economic and other uncertainties of societal transition. The negative implications of the prolonged crisis on the new urban development policy and urban land tools can postpone the establishment and application of guidelines for limiting the urban sprawl. This paper presents a brief literature review, as well as the current urban land policy and land-use efficiency in the BMA. Traditional urban land tools will be shortly described, followed by recommendations for limiting sprawl. There is a need for readjusting the current planning and urban policy regarding the urban sprawl, from an urban “command-and-control” approach to a “learn-and-adapt” approach. We suggest the introduction of more innovative and flexible urban land policy tools. [Projekat Ministarstva nauke Republike Srbije, br. III47014

Fast Facts about Online Learning

Science.gov (United States)

International Association for K-12 Online Learning, 2013

2013-01-01

This report explores the latest data concerning online and blended learning, enrollment, access, courses, and key policies indicators. It also reviews online learning statistics, trends, policy issues, and iNACOL strategic priorities. This report provides a snapshot view of state funding models for both full-time and supplemental online learning…

The Impact of Zero Tolerance Policy on Children with Disabilities

Science.gov (United States)

Alnaim, Mariam

2018-01-01

The Zero Tolerance policy was intended to eliminate learners who are a danger to a learning institution (Henson, 2012). The development of this policy was to assist schools with better policing approaches of students conducts by employing tough disciplinary action and subsequently provide a safer learning environment. While the Zero Tolerance…

Adaptive Policies for Reducing Inequalities in the Social Determinants of Health

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Gemma Carey

2015-11-01

Full Text Available Inequalities in the social determinants of health (SDH, which drive avoidable health disparities between different individuals or groups, is a major concern for a number of international organisations, including the World Health Organization (WHO. Despite this, the pathways to changing inequalities in the SDH remain elusive. The methodologies and concepts within system science are now viewed as important domains of knowledge, ideas and skills for tackling issues of inequality, which are increasingly understood as emergent properties of complex systems. In this paper, we introduce and expand the concept of adaptive policies to reduce inequalities in the distribution of the SDH. The concept of adaptive policy for health equity was developed through reviewing the literature on learning and adaptive policies. Using a series of illustrative examples from education and poverty alleviation, which have their basis in real world policies, we demonstrate how an adaptive policy approach is more suited to the management of the emergent properties of inequalities in the SDH than traditional policy approaches. This is because they are better placed to handle future uncertainties. Our intention is that these examples are illustrative, rather than prescriptive, and serve to create a conversation regarding appropriate adaptive policies for progressing policy action on the SDH.

SparkText: Biomedical Text Mining on Big Data Framework.

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Zhan Ye

Full Text Available Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment.In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM, and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes.This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research.

Information Flow and Health Policy Literacy: The Role of the Media

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Sophya Yumakulov

2012-08-01

Full Text Available People increasingly can and want to obtain and generate health information themselves. With the increasing do-it-yourself sentiment comes also the desire to be more involved in one’s health care decisions. Patient driven health-care and health research models are emerging; terms such as participatory medicine and quantified-self are visible increasingly. Given the health consumer’s desire to be more involved in health data generation and health care decision making processes the authors submit that it is important to be health policy literate, to understanding how health policies are developed, what themes are discussed among health policy researchers and policy makers, to understand how ones demands would be discussed within health policy discourses. The public increasingly obtains their knowledge through the internet by searching web browsers for keywords. Question is whether the “health consumer” to come has knowledge of key terms defining key health policy discourses which would enable them to perform targeted searches for health policy literature relevant to their situation. The authors found that key health policy terms are virtually absent from printed and online news media which begs the question how the “health consumer” might learn about key health policy terms needed for web based searches that would allow the “health consumer” to access health policy discourses relevant to them.

Random maintenance policies

CERN Document Server

Nakagawa, Toshio

2014-01-01

Exploring random maintenance models, this book provides an introduction to the implementation of random maintenance, and it is one of the first books to be written on this subject.  It aims to help readers learn new techniques for applying random policies to actual reliability models, and it provides new theoretical analyses of various models including classical replacement, preventive maintenance and inspection policies. These policies are applied to scheduling problems, backup policies of database systems, maintenance policies of cumulative damage models, and reliability of random redundant systems. Reliability theory is a major concern for engineers and managers, and in light of Japan’s recent earthquake, the reliability of large-scale systems has increased in importance. This also highlights the need for a new notion of maintenance and reliability theory, and how this can practically be applied to systems. Providing an essential guide for engineers and managers specializing in reliability maintenance a...

The Economics of Wind Power in China and Policy Implications

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Zifa Liu

2015-02-01

Full Text Available In 2009, the implementation of feed-in tariff (FIT and attractive public subsidies for onshore wind farms aroused great investment enthusiasm and spurred remarkable development of wind power in China. Meanwhile, rapid learning-by-doing has significantly cut down the cost of wind turbines and the capital cost of wind farms as well. Therefore, it is the right time to examine the appropriateness of the existing FIT policy for wind power in China. In this paper, we employ the analytical framework for levelized cost of electricity (LCOE to model the generation cost of wind power. Results show that the existing FIT policy is attractive to investors, but serious curtailment and turbine quality issues could make wind power unprofitable. Meanwhile, rapid substantial decreases in the cost of wind power have made it competitive to coal power in 2013, implying that it is possible and necessary to reform the FIT policy for new wind farms. In the future, energy policies for onshore wind power in China could be concentrated on reducing the integration cost, so as to reduce the overall system cost.

Intelligent Control of a Sensor-Actuator System via Kernelized Least-Squares Policy Iteration

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Bo Liu

2012-02-01

Full Text Available In this paper a new framework, called Compressive Kernelized Reinforcement Learning (CKRL, for computing near-optimal policies in sequential decision making with uncertainty is proposed via incorporating the non-adaptive data-independent Random Projections and nonparametric Kernelized Least-squares Policy Iteration (KLSPI. Random Projections are a fast, non-adaptive dimensionality reduction framework in which high-dimensionality data is projected onto a random lower-dimension subspace via spherically random rotation and coordination sampling. KLSPI introduce kernel trick into the LSPI framework for Reinforcement Learning, often achieving faster convergence and providing automatic feature selection via various kernel sparsification approaches. In this approach, policies are computed in a low-dimensional subspace generated by projecting the high-dimensional features onto a set of random basis. We first show how Random Projections constitute an efficient sparsification technique and how our method often converges faster than regular LSPI, while at lower computational costs. Theoretical foundation underlying this approach is a fast approximation of Singular Value Decomposition (SVD. Finally, simulation results are exhibited on benchmark MDP domains, which confirm gains both in computation time and in performance in large feature spaces.

Learning From Short Text Streams With Topic Drifts.

Science.gov (United States)

Li, Peipei; He, Lu; Wang, Haiyan; Hu, Xuegang; Zhang, Yuhong; Li, Lei; Wu, Xindong

2017-09-18

Short text streams such as search snippets and micro blogs have been popular on the Web with the emergence of social media. Unlike traditional normal text streams, these data present the characteristics of short length, weak signal, high volume, high velocity, topic drift, etc. Short text stream classification is hence a very challenging and significant task. However, this challenge has received little attention from the research community. Therefore, a new feature extension approach is proposed for short text stream classification with the help of a large-scale semantic network obtained from a Web corpus. It is built on an incremental ensemble classification model for efficiency. First, more semantic contexts based on the senses of terms in short texts are introduced to make up of the data sparsity using the open semantic network, in which all terms are disambiguated by their semantics to reduce the noise impact. Second, a concept cluster-based topic drifting detection method is proposed to effectively track hidden topic drifts. Finally, extensive studies demonstrate that as compared to several well-known concept drifting detection methods in data stream, our approach can detect topic drifts effectively, and it enables handling short text streams effectively while maintaining the efficiency as compared to several state-of-the-art short text classification approaches.

Globalization, the Strong State and Education Policy: The Politics of Policy in Asia

Science.gov (United States)

Lim, Leonel

2016-01-01

Much of the scholarship around the workings of education policy has focused on the global West and has taken for granted the state's limited abilities in the control of policies as both text and discourse. Drawing upon policy texts from the Singapore Ministry of Education and ethnographic data collected in a Singapore school, this paper explores…

Globalization, transnational policies and adult education

DEFF Research Database (Denmark)

Milana, Marcella

2013-01-01

In this article I examine policy documents produced by the United Nations Educational, Scientific and Cultural Organization (UNESCO) and the European Union (EU) in the field of adult education and learning. In doing so, I critically examine how globalization processes are constructed as policy...... problems when these transnational political agents propose adult education as a response. My main argument is that while UNESCO presents the provision of adult education as a means for governments to globally overcome disadvantages experienced by their own citizenry, the EU institutionalizes learning...... the conceptual and methodological framework of my analysis. I proceed to examine the active role played by UNESCO and the EU in promoting adult education as a policy object at transnational level, and unpack the specific problem „representations. that are substantiated by these organizations. I argue...

E-learning and the Educational Organizations Structure Reengineering (EOSR

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Osama Alshara

2007-06-01

Full Text Available There are many calls for innovative learning methods that utilize advanced technologies. However, we will raise fundamental questions that look deep into the future of the educational organization. Can the educational institute survive without adapting learning technologies? Would the educational institute succeed in adapting new learning technologies without changing its organizational structure and processes? We claim that the answer to both questions is no. Our research will present the need for edu-cational institutes to incorporate learning technologies and focuses on the demand for the educational organization structure reengineering as a basic requirement for the suc-cess of incorporating learning technologies. Our study ex-plores the faculty requirements and policies and procedures of educational institutes in the UAE.The paper concludes with some discussions on findings from a case study of the need of educational organization struc-ture reengineering as a basic requirement for incorporating learning technologies.

EDUCATION POLICY AND EFL CURRICULUM IN INDONESIA: BETWEEN THE COMMITMENT TO COMPETENCE AND THE QUEST FOR HIGHER TEST SCORES

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Anita Lie

2007-01-01

Full Text Available Education policies and curricula provide the context and specific expectations that drive student learning and achievement towards a sustainable future. The underlying policies and practices in the EFL classrooms do not always match consistently. There is an emerging need to counterbalance the power of policymakers in ensuring that balanced, pedagogically sound education policies and EFL curriculum are produced, carried out, and monitored. As one of civil society organizations, TEFLIN is well positioned to serve that mission. TEFLIN may take the initiative to engage in the EFL curriculum review project, EFL curriculum design, and reform in EFL teacher education and certification.

Print versus digital texts: understanding the experimental research and challenging the dichotomies

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Bella Ross

2017-11-01

Full Text Available This article presents the results of a systematic critical review of interdisciplinary literature concerned with digital text (or e-text uses in education and proposes recommendations for how e-texts can be implemented for impactful learning. A variety of e-texts can be found in the repertoire of educational resources accessible to students, and in the constantly changing terrain of educational technologies, they are rapidly evolving, presenting new opportunities and affordances for student learning. We highlight some of the ways in which academic studies have examined e-texts as part of teaching and learning practices, placing a particular emphasis on aspects of learning such as recall, comprehension, retention of information and feedback. We also review diverse practices associated with uses of e-text tools such as note-taking, annotation, bookmarking, hypertexts and highlighting. We argue that evidence-based studies into e-texts are overwhelmingly structured around reinforcing the existing dichotomy pitting print-based (‘traditional’ texts against e-texts. In this article, we query this approach and instead propose to focus on factors such as students’ level of awareness of their options in accessing learning materials and whether they are instructed and trained in how to take full advantage of the capabilities of e-texts, both of which have been found to affect learning performance.

Development and testing of a text-mining approach to analyse patients' comments on their experiences of colorectal cancer care.

Science.gov (United States)

Wagland, Richard; Recio-Saucedo, Alejandra; Simon, Michael; Bracher, Michael; Hunt, Katherine; Foster, Claire; Downing, Amy; Glaser, Adam; Corner, Jessica

2016-08-01

Quality of cancer care may greatly impact on patients' health-related quality of life (HRQoL). Free-text responses to patient-reported outcome measures (PROMs) provide rich data but analysis is time and resource-intensive. This study developed and tested a learning-based text-mining approach to facilitate analysis of patients' experiences of care and develop an explanatory model illustrating impact on HRQoL. Respondents to a population-based survey of colorectal cancer survivors provided free-text comments regarding their experience of living with and beyond cancer. An existing coding framework was tested and adapted, which informed learning-based text mining of the data. Machine-learning algorithms were trained to identify comments relating to patients' specific experiences of service quality, which were verified by manual qualitative analysis. Comparisons between coded retrieved comments and a HRQoL measure (EQ5D) were explored. The survey response rate was 63.3% (21 802/34 467), of which 25.8% (n=5634) participants provided free-text comments. Of retrieved comments on experiences of care (n=1688), over half (n=1045, 62%) described positive care experiences. Most negative experiences concerned a lack of post-treatment care (n=191, 11% of retrieved comments) and insufficient information concerning self-management strategies (n=135, 8%) or treatment side effects (n=160, 9%). Associations existed between HRQoL scores and coded algorithm-retrieved comments. Analysis indicated that the mechanism by which service quality impacted on HRQoL was the extent to which services prevented or alleviated challenges associated with disease and treatment burdens. Learning-based text mining techniques were found useful and practical tools to identify specific free-text comments within a large dataset, facilitating resource-efficient qualitative analysis. This method should be considered for future PROM analysis to inform policy and practice. Study findings indicated that

SparkText: Biomedical Text Mining on Big Data Framework

Science.gov (United States)

He, Karen Y.; Wang, Kai

2016-01-01

Background Many new biomedical research articles are published every day, accumulating rich information, such as genetic variants, genes, diseases, and treatments. Rapid yet accurate text mining on large-scale scientific literature can discover novel knowledge to better understand human diseases and to improve the quality of disease diagnosis, prevention, and treatment. Results In this study, we designed and developed an efficient text mining framework called SparkText on a Big Data infrastructure, which is composed of Apache Spark data streaming and machine learning methods, combined with a Cassandra NoSQL database. To demonstrate its performance for classifying cancer types, we extracted information (e.g., breast, prostate, and lung cancers) from tens of thousands of articles downloaded from PubMed, and then employed Naïve Bayes, Support Vector Machine (SVM), and Logistic Regression to build prediction models to mine the articles. The accuracy of predicting a cancer type by SVM using the 29,437 full-text articles was 93.81%. While competing text-mining tools took more than 11 hours, SparkText mined the dataset in approximately 6 minutes. Conclusions This study demonstrates the potential for mining large-scale scientific articles on a Big Data infrastructure, with real-time update from new articles published daily. SparkText can be extended to other areas of biomedical research. PMID:27685652

Technological learning in offshore wind energy: Different roles of the government

International Nuclear Information System (INIS)

Smit, Thijs; Junginger, Martin; Smits, Ruud

2007-01-01

Offshore wind energy is a promising source of renewable electricity, even though its current costs prevent large-scale implementation. Technological learning has improved the technology and its economic performance already, and could result in significant further improvements. This study investigates how technological learning takes place in offshore wind energy and how technological learning is related to different policy regimes. Offshore wind energy developments in Denmark and the United Kingdom have been analysed with a technology-specific innovation systems approach. The results reveal that the dominant forms of learning are learning by doing and learning by using. At the same time, learning by interacting is crucial to achieve the necessary binding elements in the technology-specific innovation system. Generally, most learning processes were performed by self-organizing entities. However, sometimes cultural and technical barriers occurred, excluding component suppliers and knowledge institutes from the innovation system. Danish policies successfully anticipated these barriers and removed them; therefore, the Danish policies can be characterized as pro-active. British policies shaped stable conditions for learning only; therefore, they can be characterized as active. In the future, barriers could hinder learning by interacting between the oil and gas industry, the offshore wind industry and academia. Based on this study, we suggest national and international policy makers to design long-term policies to anticipate these barriers, in order to contribute to technological learning

Hospitals as learning organizations: fostering innovation through interactive learning.

Science.gov (United States)

Dias, Casimiro; Escoval, Ana

2015-01-01

The article aims to provide an analytical understanding of hospitals as "learning organizations." It further analyzes the development of learning organizations as a way to enhance innovation and performance in the hospital sector. The article pulls together primary data on organizational flexibility, innovation, and performance from 95 administrators from hospital boards in Portugal, collected through a survey, interviews with hospital's boards, and a nominal group technique with a panel of experts on health systems. Results show that a combination of several organizational traits of the learning organization enhances its capacity for innovation development. The logistic model presented reveals that hospitals classified as "advanced learning organizations" have 5 times more chance of developing innovation than "basic learning organizations." Empirical findings further pointed out incentives, standards, and measurement requirements as key elements for integration of service delivery systems and expansion of the current capacity for structured and real-time learning in the hospital sector. The major implication arising from this study is that policy needs to combine instruments that promote innovation opportunities and incentives, with instruments stimulating the further development of the core components of learning organizations. Such a combination of policy instruments has the potential to ensure a wide external cooperation through a learning infrastructure.

Explaining technological change of wind power in China and the United States: Roles of energy policies, technological learning, and collaboration

Science.gov (United States)

Tang, Tian

The following dissertation explains how technological change of wind power, in terms of cost reduction and performance improvement, is achieved in China and the US through energy policies, technological learning, and collaboration. The objective of this dissertation is to understand how energy policies affect key actors in the power sector to promote renewable energy and achieve cost reductions for climate change mitigation in different institutional arrangements. The dissertation consists of three essays. The first essay examines the learning processes and technological change of wind power in China. I integrate collaboration and technological learning theories to model how wind technologies are acquired and diffused among various wind project participants in China through the Clean Development Mechanism (CDM)--an international carbon trade program, and empirically test whether different learning channels lead to cost reduction of wind power. Using pooled cross-sectional data of Chinese CDM wind projects and spatial econometric models, I find that a wind project developer's previous experience (learning-by-doing) and industrywide wind project experience (spillover effect) significantly reduce the costs of wind power. The spillover effect provides justification for subsidizing users of wind technologies so as to offset wind farm investors' incentive to free-ride on knowledge spillovers from other wind energy investors. The CDM has played such a role in China. Most importantly, this essay provides the first empirical evidence of "learning-by-interacting": CDM also drives wind power cost reduction and performance improvement by facilitating technology transfer through collaboration between foreign turbine manufacturers and local wind farm developers. The second essay extends this learning framework to the US wind power sector, where I examine how state energy policies, restructuring of the electricity market, and learning among actors in wind industry lead to

The Effects of Text Density Levels and the Cognitive Style of Field Dependence on Learning from a CBI Tutorial

Science.gov (United States)

Ipek, Ismail

2011-01-01

The purpose of this study was to investigate the effects of variations in text density levels and the cognitive style of field dependence on learning from a CBI tutorial, based on the dependent measures of achievement, reading comprehension, and reading rate, and of lesson completion time. Eighty college undergraduate students were randomly…

Multiagent Reinforcement Learning with Regret Matching for Robot Soccer

Directory of Open Access Journals (Sweden)

Qiang Liu

2013-01-01

Full Text Available This paper proposes a novel multiagent reinforcement learning (MARL algorithm Nash- learning with regret matching, in which regret matching is used to speed up the well-known MARL algorithm Nash- learning. It is critical that choosing a suitable strategy for action selection to harmonize the relation between exploration and exploitation to enhance the ability of online learning for Nash- learning. In Markov Game the joint action of agents adopting regret matching algorithm can converge to a group of points of no-regret that can be viewed as coarse correlated equilibrium which includes Nash equilibrium in essence. It is can be inferred that regret matching can guide exploration of the state-action space so that the rate of convergence of Nash- learning algorithm can be increased. Simulation results on robot soccer validate that compared to original Nash- learning algorithm, the use of regret matching during the learning phase of Nash- learning has excellent ability of online learning and results in significant performance in terms of scores, average reward and policy convergence.

The Pied Piper of Neo Liberalism Calls the Tune in the Republic of Ireland: An Analysis of Education Policy Text from 2000-2012

Science.gov (United States)

Simmie, Geraldine Mooney

2012-01-01

This article offers an analysis of the rhetoric of education policy text during the timeframe from 2000 to 2012 in the Republic of Ireland. The study was framed within two different discourses of the role of the teacher: one discourse regards the teacher as a professional within a dynamic system of democratic relations (Anyon, 2011; Apple, 2012;…

Improving Collaborative Learning in the Classroom: Text Mining Based Grouping and Representing

Science.gov (United States)

Erkens, Melanie; Bodemer, Daniel; Hoppe, H. Ulrich

2016-01-01

Orchestrating collaborative learning in the classroom involves tasks such as forming learning groups with heterogeneous knowledge and making learners aware of the knowledge differences. However, gathering information on which the formation of appropriate groups and the creation of graphical knowledge representations can be based is very effortful…

Climate change adaptation: policy and practice

International Nuclear Information System (INIS)

Lynch, Amanda H.; Brunner, Ronald D.

2007-01-01

Full text: Full text: Worldwide, the threefold increase in the incidence of extreme weather events since 1960 was been accompanied by a ninefold increase in damages, reaching a peak of US$219 billion in 2005 due to the impacts of Hurricane Katrina. There is strong evidence that the increases in extremes, particularly heatwave and flood, are related to climate change. Adaptive governance presents an opportunity to factor the global problem into many simpler local problems to be addressed in parallel. We propose opening up the established frame, based on insights from field testing the principles of adaptive governance and independently corroborated by other research. First, in terms of science, we propose more intensive research centred on case studies of local communities and extreme events, each of which is unique under a comprehensive description. Differences among them must be taken into account to understand past damages or reduce vulnerability. Second, in terms of policy, we support a procedurally-rational approach, one that accommodates inevitable uncertainties, integrates scientific and local knowledge into policies to advance the community's common interest, and relies on learning from experience. Importantly, the approach is constructed to give something back of value to the participating communities - usually information and insight on their own circumstances - in return for their time, expertise, and good will. Third, in terms of decision-making, we suggest structural changes that begin with harvesting experience from the bottom-up, to make policies that have worked anywhere on the ground available for voluntary adaptation by similar communities elsewhere, and to inform higher-level officials about local resource needs. This approach produces lessons that can be re-contextualised to inform both scientific understanding and policy action in similar contexts directly, without going through generalisations. The common interest lies in reducing the

School leadership for equity and learning and the question of school autonomy

Directory of Open Access Journals (Sweden)

Pavlos Hatzopoulos

2015-03-01

Full Text Available The article draws from the work conducted in the context of the European Policy Network on School Leadership (EPNoSL. In particular, it is based on an in-depth review of school leadership policies in 21 European countries and the discourse that is taking place in EPNoSL’s webinars, national workshops and peer learning activities organised in several EU countries with the participation of a variety of school leadership stakeholders (including policy makers at European, national, and local levels, school leaders, teachers and other professionals, academics, researchers, parents and students. EPNoSL is a network of 42 European institutions that aims at improving policy on, and practice in, school leadership in Europe. The article discusses the question of school autonomy in the context of school leadership policy development in Europe. School autonomy is considered as a critical precondition for the development of comprehensive school leadership policies. Based on the comprehensive framework of school leadership policy development that has been developed in the context of this project, the article undertakes two main tasks. Firstly, it attempts to show that instead of searching for universal solutions on the question of school autonomy, it is important to reflect on context-specific policies on autonomy that aim at the attainment of concrete learning and equity goals. Secondly, it specifies seven general directions for policies on school autonomy that are adaptive to the divergent experiences of European education systems.

Connecting reason to power : Assessments, learning, and environmental policy integration in Swedish energy policy

NARCIS (Netherlands)

Nilsson, M.A.

2005-01-01

The purpose of this thesis is to contribute to understanding what makes a policymaking system better at integrating sustainability concerns into its processes. Three questions are in focus. First, how can policy integration be understood analytically and what is its actual status in sector policy?

Genre based Approach to Teach Writing Descriptive Text

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Putu Ngurah Rusmawan

2017-10-01

Full Text Available This study aims to discuss how teaching and learning activities were carried out by using Genre based Approach in teaching writing descriptive text at junior high school. This study was conducted in the classroom of VII-1. Therefore, the appropriate design was qualitative research design. The subject of the study was the English teacher. To collect data, the researcher used observation and interview. The finding of the study described that the teaching and learning activities that were carried out by the teacher fulfilled the basic competencies. The teacher carried out the opening teaching activities by greeting, asking the students’ preparation during the lesson, checking the student’s attendance list, and informing the learning objective. The teacher carried out the main teaching activities by informing about how to write a descriptive text, giving, and asking opinions, eliciting the students’ understanding, prompting and directing to do exercises. The teacher carried out the closing teaching activities by directing the student to continue at home and eliciting the students’ reflection of what they could learn at that time.

Use and limitations of learning curves for energy technology policy: A component-learning hypothesis

International Nuclear Information System (INIS)

Ferioli, F.; Schoots, K.; Zwaan, B.C.C. van der

2009-01-01

In this paper, we investigate the use of learning curves for the description of observed cost reductions for a variety of energy technologies. Starting point of our analysis is the representation of energy processes and technologies as the sum of different components. While we recognize that in many cases 'learning-by-doing' may improve the overall costs or efficiency of a technology, we argue that so far insufficient attention has been devoted to study the effects of single component improvements that together may explain an aggregated form of learning. Indeed, for an entire technology the phenomenon of learning-by-doing may well result from learning of one or a few individual components only. We analyze under what conditions it is possible to combine learning curves for single components to derive one comprehensive learning curve for the total product. The possibility that for certain technologies some components (e.g., the primary natural resources that serve as essential input) do not exhibit cost improvements might account for the apparent time dependence of learning rates reported in several studies (the learning rate might also change considerably over time depending on the data set considered, a crucial issue to be aware of when one uses the learning curve methodology). Such an explanation may have important consequences for the extent to which learning curves can be extrapolated into the future. This argumentation suggests that cost reductions may not continue indefinitely and that well-behaved learning curves do not necessarily exist for every product or technology. In addition, even for diffusing and maturing technologies that display clear learning effects, market and resource constraints can eventually significantly reduce the scope for further improvements in their fabrication or use. It appears likely that some technologies, such as wind turbines and photovoltaic cells, are significantly more amenable than others to industry-wide learning. For such

Social investment in the globalising learning economy

DEFF Research Database (Denmark)

Lundvall, Bengt-Åke; Lorenz, Edward

2011-01-01

This paper demonstrates the importance of social investment and egalitarian distribution policy for reproducing the basis of a learning economy.......This paper demonstrates the importance of social investment and egalitarian distribution policy for reproducing the basis of a learning economy....

Networking European Universities through e-learning (reviewed text

Directory of Open Access Journals (Sweden)

Jana Dlouhá

2008-05-01

The main purpose of the Inventory is to show concrete examples which have been implemented in the Member States under the concept of ESD in formal and non-formal learning contexts and which are at the forefront as regards innovative approaches. Projects/programmes selected as innovative good practice will be used to inform the preparation of the next Progress Report on the EU Sustainable Development Strategy in Education. See European Commission DG Education and Culture Inventory of innovative practices in education for sustainable development, the case study VCSE - Virtual Campus for a Sustainable Europe (EUROPEAN LEVEL, page 33.

To What Extent Are Canadian Second Language Policies Evidence-Based? Reflections on the Intersections of Research and Policy

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Jim eCummins

2014-05-01

Full Text Available The paper addresses the intersections between research, ideology, and Canadian educational policies focusing on four major areas: (a core and immersion programs for the teaching of French to Anglophone students, (b policies concerning the learning of English and French by students from immigrant backgrounds, (c heritage language teaching, and (d the education of Deaf and hard-of hearing students. With respect to the teaching of French, policy-makers have largely ignored the fact that most core French programs produce meager results for the vast majority of students. Only a small proportion of students (< 10% attend more effective alternatives (e.g. French immersion and Intensive French programs. With respect to immigrant-background students, a large majority of teachers and administrators have not had opportunities to access the knowledge base regarding effective instruction for these students nor have they had opportunities for pre-service or in-service professional development regarding effective instructional practices. Educational policies have also treated the linguistic resources that children bring to school with, at best, benign neglect. In some cases (e.g., Ontario school systems have been explicitly prohibited from instituting enrichment bilingual programs that would promote students’ bilingualism and biliteracy. Finally, with respect to Deaf students, policy-makers have ignored overwhelming research on the positive relationship between academic success and the development of proficiency in natural sign languages, preferring instead to perpetuate the falsehood that acquisition of languages such as American Sign Language by young children (with or without cochlear implants will impede children’s language and academic development. The paper reviews the kinds of policies, programs, and practices that could be implemented (at no additional cost if policy-makers and educators pursued evidence-based educational policies.

A quick survey of text categorization algorithms

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Dan MUNTEANU

2007-12-01

Full Text Available This paper contains an overview of basic formulations and approaches to text classification. This paper surveys the algorithms used in text categorization: handcrafted rules, decision trees, decision rules, on-line learning, linear classifier, Rocchio’s algorithm, k Nearest Neighbor (kNN, Support Vector Machines (SVM.

Have any lessons been learned as a result of the past two decades of laissez faire in fiscal/monetary policy, energy/environment policy (or lack thereof)?

International Nuclear Information System (INIS)

Schreyer, E.

2009-01-01

'Full text:' The complexity that surrounds many aspects of technological change and of political and economic policy exists side by side with fundamental (in inconvenient) givens. The overwhelming desire to continue “business as usual” policies with respect to resource use; non-accountability in rates of resource depletion; emissions buildup and projected climate impact has resulted in the loss of a quarter century in moderating the pace of these eventually unsustainable practices. This paper's focus is on the necessity of adopting the precautionary principle in formulating practical public policy to reduce the threat of climate change; to shift the rate of fossil fuel depletion from fast track to slow and measured pace and to implement economic stimuli through renewable energy projects, etc. (author)

Patient Safety and Organizational Learning

DEFF Research Database (Denmark)

Zinck Pedersen, Kirstine

pragmatism, situated learning theory and science and technology studies, the paper contrasts the notion of ‘systemic’ learning expressed by the safety policy program with notions of learning as a socio-materially situated practice. Based on fieldwork conducted in 2010 in a Danish university hospital, I...... propose that learning, and more specifically learning from critical incidents, should be understood as a practical and experience-based activity as well as an equally individual and social achievement, which is always formed in relation to the specificities of the concrete situation. Parting from......The key trope of patient safety policy is learning. With the motto of going from ‘a culture of blame to a learning culture’, the safety program introduces a ‘systemic perspective’ to facilitate openness and willingness to talk about failures, hereby making failures into a system property. Within...

A Qualitative Analysis of Pesantren Educational Management: School Culture and Leadership of a Professional Learning Community

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Nyimas Mu'azzomi

2017-12-01

Full Text Available The purpose of this paper is to explore supportive and shared leadership structures at one Indonesian Islamic boarding school (Pesantren as a function of school culture policies and procedures in a professional learning community in the disctrict. A qualitative study was conducted at one Pesantren located in Jambi, an Indonesian province in west part of Sumatra island. We interviewed three administrators and five teachers to get in-depth information about the purpose of this paper. The interview transcriptions were translated, coded, divided into themes, and elaborated in the findings of the paper. The findings of study conclude that Pesantren leaders in the perspective of the participants must provide supportive and shared leadership structures for teachers in order to create positive cultures and effective a professional learning community for the development of the Pesantren. Leaders of the Pesantren must directly cooperate with teaching staff to provide policies and procedures for teachers in the leadership structure to directly impact school improvement through professional learning community collaborative attempts. This study was conducted based on the school culture and professional learning communities literature by exploring existent policies and practices in schools as unique cases. This study is significant to the community as specific cases informing educational leaders especially in Islamic education on mechanisms that may be leveraged to ensure successful implementation of policies and procedures on the leadership and school culture of a professional learning community literature.

Unicorn: Continual Learning with a Universal, Off-policy Agent

OpenAIRE

Mankowitz, Daniel J.; Žídek, Augustin; Barreto, André; Horgan, Dan; Hessel, Matteo; Quan, John; Oh, Junhyuk; van Hasselt, Hado; Silver, David; Schaul, Tom

2018-01-01

Some real-world domains are best characterized as a single task, but for others this perspective is limiting. Instead, some tasks continually grow in complexity, in tandem with the agent's competence. In continual learning, also referred to as lifelong learning, there are no explicit task boundaries or curricula. As learning agents have become more powerful, continual learning remains one of the frontiers that has resisted quick progress. To test continual learning capabilities we consider a ...

Brazil's new national policy on solid waste

DEFF Research Database (Denmark)

Jabbour, A.B.L.d.S.; Jabbour, C.J.C.; Sarkis, J.

2014-01-01

Brazil, one of the world's largest developing countries, has recently introduced a new solid waste management regulatory policy. This new regulatory policy will have implications for a wide variety of stakeholders and sets the stage for opportunities and lessons to be learned. These issues...

Building a Learning Profession. ACER Policy Briefs. Issue 3

Science.gov (United States)

Ingvarson, Lawrence

2003-01-01

This paper falls into two main sections: (1) an overview of contemporary research on effective professional learning for practicing educators; and (2) recommendations for action to promote effective learning for practicing educators. Three central questions guide the paper: (1) When does professional learning lead to improved learning outcomes for…

Logistic regression a self-learning text

CERN Document Server

Kleinbaum, David G

1994-01-01

This textbook provides students and professionals in the health sciences with a presentation of the use of logistic regression in research. The text is self-contained, and designed to be used both in class or as a tool for self-study. It arises from the author's many years of experience teaching this material and the notes on which it is based have been extensively used throughout the world.

Science Policy: Behind the Scenes

Science.gov (United States)

Barnett, Travis

2011-04-01

I served nine weeks as an intern in the House of Representatives Committee on Science and Technology. For the majority of the summer I served in the Research and Science Education Subcommittee, researching, among other things, cyber-enabled learning, cybersecurity, and alternate energy costs. I learned a great deal about the workings of the American government and how to contribute to a professional office environment. During these nine weeks, my personal communication skills were greatly improved. My internship was created and funded by the John and Jane Mather Foundation for the Arts and Sciences, and as the only merit-based science committee intern, I felt a great responsibility to prove my worth in the Committee. It is important to have scientists involved in the policy of our government in order to keep our nation on a progressive track, and to preserve current scientific discoveries for posterity. Immersed in government and science policy, I feel very learned and prepared to participate in these fields.

Python 3 text processing with NLTK 3 cookbook

CERN Document Server

Perkins, Jacob

2014-01-01

This book is intended for Python programmers interested in learning how to do natural language processing. Maybe you've learned the limits of regular expressions the hard way, or you've realized that human language cannot be deterministically parsed like a computer language. Perhaps you have more text than you know what to do with, and need automated ways to analyze and structure that text. This Cookbook will show you how to train and use statistical language models to process text in ways that are practically impossible with standard programming tools. A basic knowledge of Python and the basi

Whose University is it anyway? The complex world(s) of lifelong (higher) learning, government policy and institutional habitus

OpenAIRE

Marr, Liz; Harvey, Morag

2012-01-01

At a time of worldwide economic recession, policy decisions at governmental and institutional level have to balance the basic human rights of access to education with the skills needs for economic competitiveness. This is playing out across Europe in a myriad of ways, as social problems exacerbated by lack of opportunity, add to the complexity of funding decisions.\\ud As part of the OPULL (Opening up Universities to Lifelong Learning) project, four European universities have been conducting r...

District Governance and Student Learning in Indonesia

OpenAIRE

Pradhan, Menno; de Ree, Joppe

2014-01-01

We document the likely importance of district governance and teacher management policies in relation to student learning in Indonesian primary schools. As the responsibility to deliver primary education has been decentralized to district governments, we expect district specific variations in teacher management policies. Consequently, we also expect variations in learning trajectories across districts. We document substantial heterogeneity in learning gains across districts. Furthermore, we sh...

Biography, policy and language teaching practices in a multilingual context: Early childhood classrooms in Mauritius

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Aruna Ankiah-Gangadeen

2014-12-01

Full Text Available Language policies in education in multilingual postcolonial contexts are often driven by ideological considerations more veered towards socio-economic and political viability for the country than towards the practicality at implementation level. Centuries after the advent of colonisation, when culturally and linguistically homogenous countries helped to maintain the dominion of colonisers, the English language still has a stronghold in numerous countries due to the material rewards it offers. How then are the diversity of languages – often with different statuses and functions in society – reconciled in the teaching and learning process? How do teachers deal with the intricacies that are generated within a situation where children are taught in a language that is foreign to them? This paper is based on a study involving pre-primary teachers in Mauritius, a developing multilingual African country. The aim was to understand how their approach to the teaching of English was shaped by their biographical experiences of learning the language. The narrative inquiry methodology offered rich possibilities to foray into these experiences, including the manifestations of negotiating their classroom pedagogy in relation to their own personal historical biographies of language teaching and learning, the policy environment, and the pragmatic classroom specificities of diverse, multilingual learners. These insights become resources for early childhood education and teacher development in multilingual contexts caught within the tensions between language policy and pedagogy.

Informing principal policy reforms in South Africa through data-based evidence

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Gabrielle Wills

2015-12-01

Full Text Available In the past decade there has been a notable shift in South African education policy that raises the value of school leadership as a lever for learning improvements. Despite a growing discourse on school leadership, there has been a lack of empirical based evidence on principals to inform, validate or debate the efficacy of proposed policies in raising the calibre of school principals. Drawing on findings from a larger study to understand the labour market for school principals in South Africa, this paper highlights four overarching characteristics of this market with implications for informing principal policy reforms. The paper notes that improving the design and implementation of policies guiding the appointment process for principals is a matter of urgency. A substantial and increasing number of principal replacements are taking place across South African schools given a rising age profile of school principals. In a context of low levels of principal mobility and high tenure, the leadership trajectory of the average school is established for nearly a decade with each principal replacement. Evidence-based policy making has a strong role to play in getting this right.

What lessons have been learned in reforming the Renewables Obligation? An analysis of internal and external failures in UK renewable energy policy

International Nuclear Information System (INIS)

Wood, Geoffrey; Dow, Stephen

2011-01-01

Despite operating a delivery programme for RES-E since 1990, UK targets and policy goals have not been achieved. In response, the Government reformed the RO. This article re-examines UK renewable energy policy by analysing the internal and external failures of the various mechanisms to determine if Government has learnt from previous experience in reforming the RO. Government did not learn from their own actions during the NFFO/RO transition, evidenced by high-levels of similarity in internal/external failures. The reformed-RO is expected to significantly increase deployment, has provided a 'renewables package' by comprehensively addressing both internal/external failures but major internal failures (price/financial risk) still remain, resulting in contiguous failures over two decades and two mechanism changes (NFFO, RO, RO/reformed-RO). Success will again be heavily dependent on a select few technologies and new/untested measures to combat external failures. Mechanism-extension to 2037 is probably the single most important factor underlying potential deployment increases. However, introducing a FIT-like system via the sheer number of 'bolt-on' reforms to counter policy failures indicates loss of direction and clarity. Overall, although Government appears to have learnt some of its lessons from the past two-decades, significant doubt remains whether renewable energy policy objectives will be met via the latest mechanism change. - Research highlights: → Review of UK renewable energy policy learning behaviour via the 2009 Renewable Obligation reform. → Applies key lessons and analysis of NFFO/RO, RO reform and possible FIT schemes. → Finds UK Government has learnt some lessons from the past but some failures remain contiguous over two decades. → In contrast to previous changes, 2009 reform provided a comprehensive reform package. → Significant doubt remains whether objectives will be met via latest mechanism change.

Did my M.D. really go to University to learn? Detrimental effects of numerus clausus on self-efficacy, mastery goals and learning.

Directory of Open Access Journals (Sweden)

Nicolas Sommet

Full Text Available Exams with numerus clausus are very common in Medicine, Business Administration and Law. They are intended to select a predefined number of academic candidates on the basis of their rank rather than their absolute performance. Various scholars and politicians believe that numerus clausus policies are a vector of academic excellence. We argue, however, that they could have ironic epistemic effects. In comparison with selective policies based on criterion-based evaluations, selection via numerus clausus creates negative interdependence of competence (i.e., the success of some students comes at the expense of the others. Thus, we expect it to impair students' sense of self-efficacy and--by extension--the level of mastery goals they adopt, as well as their actual learning. Two field studies respectively reported that presence (versus absence and awareness (versus ignorance of numerus clausus policies at University was associated with a decreased endorsement of mastery goals; this effect was mediated by a reduction in self-efficacy beliefs. Moreover, an experimental study revealed that numerus clausus negatively predicted learning; this effect was, again, mediated by a reduction in self-efficacy beliefs. Practical implications for the selection procedures in higher education are discussed.

A study of active learning methods for named entity recognition in clinical text.

Science.gov (United States)

Chen, Yukun; Lasko, Thomas A; Mei, Qiaozhu; Denny, Joshua C; Xu, Hua

2015-12-01

Named entity recognition (NER), a sequential labeling task, is one of the fundamental tasks for building clinical natural language processing (NLP) systems. Machine learning (ML) based approaches can achieve good performance, but they often require large amounts of annotated samples, which are expensive to build due to the requirement of domain experts in annotation. Active learning (AL), a sample selection approach integrated with supervised ML, aims to minimize the annotation cost while maximizing the performance of ML-based models. In this study, our goal was to develop and evaluate both existing and new AL methods for a clinical NER task to identify concepts of medical problems, treatments, and lab tests from the clinical notes. Using the annotated NER corpus from the 2010 i2b2/VA NLP challenge that contained 349 clinical documents with 20,423 unique sentences, we simulated AL experiments using a number of existing and novel algorithms in three different categories including uncertainty-based, diversity-based, and baseline sampling strategies. They were compared with the passive learning that uses random sampling. Learning curves that plot performance of the NER model against the estimated annotation cost (based on number of sentences or words in the training set) were generated to evaluate different active learning and the passive learning methods and the area under the learning curve (ALC) score was computed. Based on the learning curves of F-measure vs. number of sentences, uncertainty sampling algorithms outperformed all other methods in ALC. Most diversity-based methods also performed better than random sampling in ALC. To achieve an F-measure of 0.80, the best method based on uncertainty sampling could save 66% annotations in sentences, as compared to random sampling. For the learning curves of F-measure vs. number of words, uncertainty sampling methods again outperformed all other methods in ALC. To achieve 0.80 in F-measure, in comparison to random

Autonomy, Conformity and Organizational Learning

Directory of Open Access Journals (Sweden)

Hideo Owan

2013-07-01

Full Text Available There is often said to be a tension between the two types of organizational learning activities, exploration and exploitation. The argument goes that the two activities are substitutes, competing for scarce resources when firms need different capabilities and management policies. We present another explanation, attributing the tension to the dynamic interactions among search, knowledge sharing, evaluation and alignment within organizations. Our results show that successful organizations tend to bifurcate into two types: those that always promote individual initiatives and build organizational strengths on individual learning and those good at assimilating the individual knowledge base and exploiting shared knowledge. Straddling the two types often fails. The intuition is that an equal mixture of individual search and assimilation slows down individual learning, while at the same time making it difficult to update organizational knowledge because individuals’ knowledge base is not sufficiently homogenized. Straddling is especially inefficient when the operation is sufficiently complex or when the business environment is sufficiently turbulent.

Reinforcement learning or active inference?

Directory of Open Access Journals (Sweden)

Karl J Friston

2009-07-01

Full Text Available This paper questions the need for reinforcement learning or control theory when optimising behaviour. We show that it is fairly simple to teach an agent complicated and adaptive behaviours using a free-energy formulation of perception. In this formulation, agents adjust their internal states and sampling of the environment to minimize their free-energy. Such agents learn causal structure in the environment and sample it in an adaptive and self-supervised fashion. This results in behavioural policies that reproduce those optimised by reinforcement learning and dynamic programming. Critically, we do not need to invoke the notion of reward, value or utility. We illustrate these points by solving a benchmark problem in dynamic programming; namely the mountain-car problem, using active perception or inference under the free-energy principle. The ensuing proof-of-concept may be important because the free-energy formulation furnishes a unified account of both action and perception and may speak to a reappraisal of the role of dopamine in the brain.

Virtual policy networks: navigating the policy web

OpenAIRE

McNutt, Kathleen

2006-01-01

Governing in an information-rich environment necessitates a redistribution of power and new approaches to policy learning. The key basis for this organizational repositioning is the accommodation of information. For the first time in human history mass amounts of information may be collected, stored, and searched using networked technologies. While informational assets are a critical commodity in the policymaking process, the extraordinary increase in the creation and dissemination of informa...

Policies as translation: situating the transnational social policies

Directory of Open Access Journals (Sweden)

Paul Stubbs

2012-06-01

Full Text Available This article explores some of the implications of the development of an anthropology or ethnography of the transnational dimensions of policies. The fi rst part explains the basic conceptual apparatus, in terms of policies as a generator of meanings. The second part examines policies as translation and explores its implications in terms of the transnationalization of the policies and, in particular, it seeks to contrast the translation of policies with more orthodox knowledge of policies transference. The third part explores the translation of policies through a refl exive ethnographical approach, analyzing a number of cases based on the practical involvement of the authors in social policies reforms in regions of the Central Europe and the East. The fourth part presents some conclusions and indicates certain theoretical and ethical objections that can and must be raised with regard to the presented approach.

Learning from Evidence in a Complex World

Science.gov (United States)

Sterman, John D.

2006-01-01

Policies to promote public health and welfare often fail or worsen the problems they are intended to solve. Evidence-based learning should prevent such policy resistance, but learning in complex systems is often weak and slow. Complexity hinders our ability to discover the delayed and distal impacts of interventions, generating unintended “side effects.” Yet learning often fails even when strong evidence is available: common mental models lead to erroneous but self-confirming inferences, allowing harmful beliefs and behaviors to persist and undermining implementation of beneficial policies. Here I show how systems thinking and simulation modeling can help expand the boundaries of our mental models, enhance our ability to generate and learn from evidence, and catalyze effective change in public health and beyond. PMID:16449579

Using Gloss to Help Fifth and Sixth Graders Comprehend Social Studies Text: An Informal Study of a Learning Aid. Working Paper No. 295.

Science.gov (United States)

Witte, Pauline

A two-part study examined the effectiveness of glossing (writing comments or questions in text to improve comprehension) when students use it in social studies texts in combination with discussions and other activities. Students were divided into two groups, one of which learned glossing while the other engaged in assigned workbook activities.…

Evaluation of learning: practices and alternatives to school inclusion

Directory of Open Access Journals (Sweden)

Ana Carolina Christofari

2012-11-01

Full Text Available This paper aims to analyze the evaluation of learning, considering this assessment as a process focusing on pedagogical relationship. Thus, we discuss the implications that emerge as nexus between a questioning on the evaluation and goal of education for all children in the mainstream school, including those with disabilities. Throughout the text are also discussed the singularities associated with disability and debated the evaluation of learning as a process that should involve the group-class, no differences in evaluative logic, even though it may refer to procedures that indicate some variability. The theme of learning evaluation evokes one of the more complex facets of the school curriculum and announces problematizations referred to school inclusion policies such as: all students learn? How to build different intervention strategies for teaching the same group? How to evaluate students considering the singularities of them? This text should be understood as a reflection based in the ransom of the historicity of the subject treated in this work, the analysis of academic production, supporting the literature which has been discussing the processes of learning assessment, and the welcome signs everyday school - explicit in certain practices - to prepare the analysis. It is therefore in this context, to discuss a kind of resizing, reshaping the concept of learning assessment looking at possibilities for dialogue with the perspective of education for all. It is conceived, well, as the evaluation process that should serve as monitoring the process of teaching and learning with the objective of building teaching strategies considering the singularities of students.

Engaged: Educators and the Policy Process

Science.gov (United States)

Colvin, Richard Lee; Bassett, Katherine; Hansen, Jessica; Boffy, Holly Franks; DelColle, Jeanne; Fennell, Maddie; Izzo, Marguerite; Lechleiter-Luke, Leah; Mieliwocki, Rebecca; Minkel, Justin; Pearson, Michelle; Poulos, Christopher; Woods-Murphy, Maryann

2015-01-01

The premise of the white paper is that education policy results are better for students when policies are informed and shaped by highly effective educators who know firsthand what it takes to deliver excellent teaching and learning. Policymakers and educators should share a sense of urgency to work together to provide every child in our country…

Reinforcement learning for dpm of embedded visual sensor nodes

International Nuclear Information System (INIS)

Khani, U.; Sadhayo, I. H.

2014-01-01

This paper proposes a RL (Reinforcement Learning) based DPM (Dynamic Power Management) technique to learn time out policies during a visual sensor node's operation which has multiple power/performance states. As opposed to the widely used static time out policies, our proposed DPM policy which is also referred to as OLTP (Online Learning of Time out Policies), learns to dynamically change the time out decisions in the different node states including the non-operational states. The selection of time out values in different power/performance states of a visual sensing platform is based on the workload estimates derived from a ML-ANN (Multi-Layer Artificial Neural Network) and an objective function given by weighted performance and power parameters. The DPM approach is also able to dynamically adjust the power-performance weights online to satisfy a given constraint of either power consumption or performance. Results show that the proposed learning algorithm explores the power-performance tradeoff with non-stationary workload and outperforms other DPM policies. It also performs the online adjustment of the tradeoff parameters in order to meet a user-specified constraint. (author)

A Guide Text or Many Texts? "That is the Question”

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Delgado de Valencia Sonia

2001-08-01

Full Text Available The use of supplementary materials in the classroom has always been an essential part of the teaching and learning process. To restrict our teaching to the scope of one single textbook means to stand behind the advances of knowledge, in any area and context. Young learners appreciate any new and varied support that expands their knowledge of the world: diaries, letters, panels, free texts, magazines, short stories, poems or literary excerpts, and articles taken from Internet are materials that will allow learnersto share more and work more collaboratively. In this article we are going to deal with some of these materials, with the criteria to select, adapt, and create them that may be of interest to the learner and that may promote reading and writing processes. Since no text can entirely satisfy the needs of students and teachers, the creativity of both parties will be necessary to improve the quality of teaching through the adequate use and adaptation of supplementary materials.

An Intelligent System For Arabic Text Categorization

NARCIS (Netherlands)

Syiam, M.M.; Tolba, Mohamed F.; Fayed, Z.T.; Abdel-Wahab, Mohamed S.; Ghoniemy, Said A.; Habib, Mena Badieh

Text Categorization (classification) is the process of classifying documents into a predefined set of categories based on their content. In this paper, an intelligent Arabic text categorization system is presented. Machine learning algorithms are used in this system. Many algorithms for stemming and

Innovation in Citizen Science – Perspectives on Science-Policy Advances

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Susanne Hecker

2018-04-01

Full Text Available Citizen science is growing as a field of research with contributions from diverse disciplines, promoting innovation in science, society, and policy. Inter- and transdisciplinary discussions and critical analyses are needed to use the current momentum to evaluate, demonstrate, and build on the advances that have been made in the past few years. This paper synthesizes results of discussions at the first international citizen science conference of the European Citizen Science Association (ECSA in 2016 in Berlin, Germany, and distills major points of the discourse into key recommendations. To enhance innovation in science, citizen science needs to clearly demonstrate its scientific benefit, branch out across disciplines, and foster active networking and new formats of collaboration, including true co-design with participants. For fostering policy advances, it is important to embrace opportunities for policy-relevant monitoring and policy development and to work with science funders to find adequate avenues and evaluation tools to support citizen science. From a society angle it is crucial to engage with societal actors in various formats that suit participants and to evaluate two-way learning outcomes as well as to develop the transformative role of science communication. We hope that these key perspectives will promote citizen science progress at the science-society-policy interface.

Learn to Lead: Mapping Workplace Learning of School Leaders

Science.gov (United States)

Hulsbos, Frank Arnoud; Evers, Arnoud Theodoor; Kessels, Joseph Willem Marie

2016-01-01

In recent years policy makers' interest in the professional development of school leaders has grown considerably. Although we know some aspect of formal educational programs for school leaders, little is known about school leaders' incidental and non-formal learning in the workplace. This study aims to grasp what workplace learning activities…

The policy trail methodology

DEFF Research Database (Denmark)

Holford, John; Larson, Anne; Melo, Susana

of ‘policy trail’, arguing that it can overcome ‘methodological nationalism’ and link structure and agency in research on the ‘European educational space’. The ‘trail’ metaphor, she suggests, captures the intentionality and the erratic character of policy. The trail connects sites and brings about change......, but – although policy may be intended to be linear, with specific outcomes – policy often has to bend, and sometimes meets insurmountable obstacles. This symposium outlines and develops the methodology, but also reports on research undertaken within a major FP7 project (LLLIght’in’Europe, 2012-15) which made use......In recent years, the “policy trail” has been proposed as a methodology appropriate to the shifting and fluid governance of lifelong learning in the late modern world (Holford et al. 2013, Holford et al. 2013, Cort 2014). The contemporary environment is marked by multi-level governance (global...

IMPROVING THE STUDENTS’ COMPETENCE IN DEVELOPING A PARAGRAPH OF DISCUSSION TEXTS USING THEMATIC PROGRESSION PATTERNS WITH COOPERATIVE LEARNING METHOD (TP-CL

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Farikah Farikah

2017-04-01

Full Text Available This research analyzes the effectiveness of thematic progression patterns with cooperative learning method (TP-CL in teaching the students’ competence in developing a paragraph of discussion texts and the effectiveness of teaching-learning activities of paragraph writing class. This mixed method research was conducted in the English Department of Tidar University of Magelang in the academic year of 2011/2012. The sample of this research were the fourth semester students of UTM. To collect the research data, writing test, observation and interview were used while to analyze the data, she used descriptive and inferential statistics for quantitative data and constant comparative method for qualitative data. The first result shows that implementing TP-CL is effective for teaching the students’ competence in developing a paragraph of discussion texts. It can be seen from the results of writing tests. Based on Brown and Bailey’s theory in Brown (2004, it can be seen that the mean score of organization element in pretest is 10.77 and the post test of paragraph writing is 16.73. The second result shows that there is an improvement of the effectiveness of teaching-learning activity of writing class by implementing TP-CL. The effectiveness can be seen from the indicators of effective teaching based on Blum in Nunan and Lamb (1996 and Creemer’s theory (1994. The results suggest that writing lecturers should introduce to develop a paragraph to the students in order that they can write paragraphs coherently and various theme in order that they can write the paragraph artistically.

Concurrent Learning of Control in Multi agent Sequential Decision Tasks

Science.gov (United States)

2018-04-17

Concurrent Learning of Control in Multi-agent Sequential Decision Tasks The overall objective of this project was to develop multi-agent reinforcement... learning (MARL) approaches for intelligent agents to autonomously learn distributed control policies in decentral- ized partially observable... learning of policies in Dec-POMDPs, established performance bounds, evaluated these algorithms both theoretically and empirically, The views

Learning attention for historical text normalization by learning to pronounce

DEFF Research Database (Denmark)

Bollmann, Marcel; Bingel, Joachim; Søgaard, Anders

2017-01-01

Automated processing of historical texts often relies on pre-normalization to modern word forms. Training encoder-decoder architectures to solve such problems typically requires a lot of training data, which is not available for the named task. We address this problem by using several novel encoder...

Policy work as a reform project

OpenAIRE

Hal K. Colebatch

2008-01-01

One aspect of the modernization of liberal government in the late 20th century was an increased attention to policy, both as a concept for interrogating government, and as the basis for organizing work within government, leading to the development of ‘policy analysis’ as a decision tool. This paper reviews the development of specialised forms of ‘policy work’ in liberal western political systems in order to establish what can be learned by other sorts of polity, and in particular, the tran...

Monetary Policy Strategy: Lessons from the Crisis

OpenAIRE

Frederic S. Mishkin

2011-01-01

This paper examines what we have learned and how we should change our thinking about monetary policy strategy in the aftermath of the 2007-2009 financial crisis. It starts with a discussion of where the science of monetary policy was before the crisis and how central banks viewed monetary policy strategy. It will then examine how the crisis has changed the thinking of both macro/monetary economists and central bankers. Finally, it looks how much of the science of monetary policy needs to be a...

Instance-based Policy Learning by Real-coded Genetic Algorithms and Its Application to Control of Nonholonomic Systems

Science.gov (United States)

Miyamae, Atsushi; Sakuma, Jun; Ono, Isao; Kobayashi, Shigenobu

The stabilization control of nonholonomic systems have been extensively studied because it is essential for nonholonomic robot control problems. The difficulty in this problem is that the theoretical derivation of control policy is not necessarily guaranteed achievable. In this paper, we present a reinforcement learning (RL) method with instance-based policy (IBP) representation, in which control policies for this class are optimized with respect to user-defined cost functions. Direct policy search (DPS) is an approach for RL; the policy is represented by parametric models and the model parameters are directly searched by optimization techniques including genetic algorithms (GAs). In IBP representation an instance consists of a state and an action pair; a policy consists of a set of instances. Several DPSs with IBP have been previously proposed. In these methods, sometimes fail to obtain optimal control policies when state-action variables are continuous. In this paper, we present a real-coded GA for DPSs with IBP. Our method is specifically designed for continuous domains. Optimization of IBP has three difficulties; high-dimensionality, epistasis, and multi-modality. Our solution is designed for overcoming these difficulties. The policy search with IBP representation appears to be high-dimensional optimization; however, instances which can improve the fitness are often limited to active instances (instances used for the evaluation). In fact, the number of active instances is small. Therefore, we treat the search problem as a low dimensional problem by restricting search variables only to active instances. It has been commonly known that functions with epistasis can be efficiently optimized with crossovers which satisfy the inheritance of statistics. For efficient search of IBP, we propose extended crossover-like mutation (extended XLM) which generates a new instance around an instance with satisfying the inheritance of statistics. For overcoming multi-modality, we

Factors Affecting the Implementation of Policy 2450, Distance Education and the West Virginia Virtual School, as Perceived by Principals/Assistant Principals, Counselors, and Distance Learning Contacts and/or Course Facilitators

Science.gov (United States)

Burdette, Keith R.

2013-01-01

This study examined the factors important to the implementation of West Virginia Board of Education Policy 2450, Distance Learning and the West Virginia Virtual School. The purpose of this study was to determine the factors that facilitated and impeded implementation of the policy, as perceived by principals/assistant principals, counselors, and…

Extreme Trust Region Policy Optimization for Active Object Recognition.

Science.gov (United States)

Liu, Huaping; Wu, Yupei; Sun, Fuchun; Huaping Liu; Yupei Wu; Fuchun Sun; Sun, Fuchun; Liu, Huaping; Wu, Yupei

2018-06-01

In this brief, we develop a deep reinforcement learning method to actively recognize objects by choosing a sequence of actions for an active camera that helps to discriminate between the objects. The method is realized using trust region policy optimization, in which the policy is realized by an extreme learning machine and, therefore, leads to efficient optimization algorithm. The experimental results on the publicly available data set show the advantages of the developed extreme trust region optimization method.