Vinogradov, Evgueni; Kolvereid, Lars
The level of self-employment varies significantly among immigrants from different countries of origin. The objective of this research is to examine the relationship between home-country national intelligence and self-employment rates among first generation immigrants in Norway. Empirical secondary data on self-employment among immigrants from 117…
Mohsin, M. Naeem; Shabbir, Muhammad; Saeed, Wizra; Mohsin, M. Saleem
The study was conducted to know the status of Muslim immigrants' children with learning difficulties and importance of parents' involvement for the education whose children are with learning difficulties, and the factors responsible for the learning difficulties among immigrants' children. There were 81 immigrant children with learning…
Smith, Andrew C
Full Text Available Conference Proceedings Paul Cunningham and Miriam Cunningham (Eds) IIMC International Information Management Corporation, 2011 ISBN: 978-1-905824-24-3 An Intelligent Fractions Learning System: Implementation Andrew Cyrus SMITH1, Teemu H. LAINE2 1CSIR... to fractions. Our aim with the current research project is to extend the existing UFractions learning system to incorporate automatic data capturing. ?Intelligent UFractions? allows a teacher to remotely monitor the children?s progress during...
This paper examines citizenship learning and identity construction of new Chinese immigrants in a Canadian immigration settlement organization (ISO). I address the gap between the concept of "settlement" and "citizenship" generated by government-funded ISOs and new immigrants' actual practices in these programs. I adopt Dorothy…
Hall, Ernest L.; Liao, Xiaoqun; Alhaj Ali, Souma M.
Unlike intelligent industrial robots which often work in a structured factory setting, intelligent mobile robots must often operate in an unstructured environment cluttered with obstacles and with many possible action paths. However, such machines have many potential applications in medicine, defense, industry and even the home that make their study important. Sensors such as vision are needed. However, in many applications some form of learning is also required. The purpose of this paper is to present a discussion of recent technical advances in learning for intelligent mobile robots. During the past 20 years, the use of intelligent industrial robots that are equipped not only with motion control systems but also with sensors such as cameras, laser scanners, or tactile sensors that permit adaptation to a changing environment has increased dramatically. However, relatively little has been done concerning learning. Adaptive and robust control permits one to achieve point to point and controlled path operation in a changing environment. This problem can be solved with a learning control. In the unstructured environment, the terrain and consequently the load on the robot"s motors are constantly changing. Learning the parameters of a proportional, integral and derivative controller (PID) and artificial neural network provides an adaptive and robust control. Learning may also be used for path following. Simulations that include learning may be conducted to see if a robot can learn its way through a cluttered array of obstacles. If a situation is performed repetitively, then learning can also be used in the actual application. To reach an even higher degree of autonomous operation, a new level of learning is required. Recently learning theories such as the adaptive critic have been proposed. In this type of learning a critic provides a grade to the controller of an action module such as a robot. The creative control process is used that is "beyond the adaptive critic." A
Wu, Ya-Ling; Wu, Hsing-Chen
Based on a sociocultural approach to adult learning and poststructural feminist theories, this study draws on interviews with 11 married Vietnamese women to explore the higher education learning experiences of Vietnamese immigrant women in Taiwan. On the basis of their husbands' permission and support, Vietnamese immigrant women embraced the…
Zysberg, Leehu; Kasler, Jon
The literature is conflicted around the subject of the emotional abilities of individuals with Specific Learning Disabilities (SLDs): While many claim cognitive challenges are associated with emotional difficulties, some suggest emotional and interpersonal abilities are not compromised in such disorders and may help individuals compensate and cope effectively with the challenges they meet in learning environments. Two studies explored differences in emotional intelligence (EI) between young adults with and without SLD. Two samples (matched on gender, approximate age, and program of study; n = 100, and unmatched; n = 584) of college students took self-report and performance-based tests of EI (Ability-EI) as well as a measure of self-esteem and demographics associated with college performance (e.g.: SAT scores, gender, etc.). The results showed that while SAT scores and ability emotional intelligence (Ability-EI) were associated with college GPA, Ability-EI did not differ between the two groups, while self-report measures of EI and self-esteem did show differences, with the group with learning disabilities ranking lower. The effects remained stable when we controlled for demographics and potential intervening factors. The results suggest that EI may play a protective role in the association between background variables and college attainment in students with SLD. The results may provide a basis for interventions to empower students with SLD in academia.
Banerjee, R; Bradshaw, Gary; Carbonell, Jaime Guillermo; Mitchell, Tom Michael; Michalski, Ryszard Spencer
Machine Learning: An Artificial Intelligence Approach contains tutorial overviews and research papers representative of trends in the area of machine learning as viewed from an artificial intelligence perspective. The book is organized into six parts. Part I provides an overview of machine learning and explains why machines should learn. Part II covers important issues affecting the design of learning programs-particularly programs that learn from examples. It also describes inductive learning systems. Part III deals with learning by analogy, by experimentation, and from experience. Parts IV a
This paper develops a theoretical framework for employing learning analytics in online education to trace multiple learning variations of online students by considering their potential of being multiple intelligences based on Howard Gardner's 1983 theory of multiple intelligences. The study first emphasizes the need to facilitate students as…
Explains the Artificial Intelligence Applications to Learning Programme, which was developed in the United Kingdom to explore and accelerate the use of artificial intelligence (AI) technologies in learning in both the educational and industrial sectors. Highlights include program evaluation, marketing, ownership of information, consortia, and cost…
Lopez-Zafra, Esther; El Ghoudani, Karima
Migration is a normal process of people seeking new opportunities, work, or leisure in societies. The way people adapt to a new country (acculturation) is a complex process in which immigrants' evaluations about the culture of origin and their perceptions of the host country interact. The combination of these two factors produces four types of acculturation: separation, assimilation, integration, and marginalization. Several variables, such as personality, attitudes, and emotional intelligence, have been studied to help explain this process. However, the impact of a culture of honor and its interaction with other variables remains an open question that may help to explain how migrants can better adjust to their host culture. In this study, we examine the influence of the culture of honor (social) and emotional intelligence (individual) on acculturation. In a sample of 129 Moroccan women (mean age = 29, SD = 9.40) immigrants in Spain (mean time in Spain = 6 years, SD = 3.60), we investigated the relations among the variables of interest. Our results show that no significant differences emerged in the scores given for culture of honor (CH) and the acculturation strategies of the Moroccan immigrant women F(3, 99) = .233; p = .87. However women who preferred the integration strategy scored highest on emotional intelligence (EI), whereas the assimilated immigrants showed the lowest scores for EI F(3, 92) = 4.63; p = .005. Additionally, only in the case of integration does EI mediate between CH and the value given to the immigrant's own and host cultures (p <.001).
Fardinpour, Ali; Pedram, Mir Mohsen; Burkle, Martha
Virtual Learning Environments have been the center of attention in the last few decades and help educators tremendously with providing students with educational resources. Since artificial intelligence was used for educational proposes, learning management system developers showed much interest in making their products smarter and more…
Ozdemir, Ali; Alaybeyoglu, Aysegul; Mulayim, Naciye; Uysal, Muhammed
In this study, an intelligent system which determines learning style of the students is developed to increase success in effective and easy learning. The importance of the proposed software system is to determine convenience degree of the student's learning style. Personal information form and Dunn Learning Style Preference Survey are used to…
Xhafa, Fatos [Polytechnic Univ. of Catalonia, Barcelona (Spain). Dept. of Languages and Informatics Systems; Caballe, Santi; Daradoumis, Thanasis [Open Univ. of Catalonia, Barcelona (Spain). Dept. of Computer Sciences Multimedia and Telecommunications; Abraham, Ajith [Machine Intelligence Research Labs (MIR Labs), Auburn, WA (United States). Scientific Network for Innovation and Research Excellence; Juan Perez, Angel Alejandro (eds.) [Open Univ. of Catalonia, Barcelona (Spain). Dept. of Information Sciences
E-Learning has become one of the most wide spread ways of distance teaching and learning. Technologies such as Web, Grid, and Mobile and Wireless networks are pushing teaching and learning communities to find new and intelligent ways of using these technologies to enhance teaching and learning activities. Indeed, these new technologies can play an important role in increasing the support to teachers and learners, to shorten the time to learning and teaching; yet, it is necessary to use intelligent techniques to take advantage of these new technologies to achieve the desired support to teachers and learners and enhance learners' performance in distributed learning environments. The chapters of this volume bring advances in using intelligent techniques for technology enhanced learning as well as development of e-Learning applications based on such techniques and supported by technology. Such intelligent techniques include clustering and classification for personalization of learning, intelligent context-aware techniques, adaptive learning, data mining techniques and ontologies in e-Learning systems, among others. Academics, scientists, software developers, teachers and tutors and students interested in e-Learning will find this book useful for their academic, research and practice activity. (orig.)
Vasiliy M. Trembach
Full Text Available In the article issues of engineering intelligent tutoring systems of University with adaptation are considered. The article also dwells on some modern approaches to engineering of information systems. It shows the role of engineering e-learning devices (systems in system engineering. The article describes the basic principles of system engineering and these principles are expanded regarding to intelligent information systems. The structure of intelligent learning systems with adaptation of the individual learning environments based on services is represented in the article.
Blom, S.; Severiens, S.
In order to examine and explain differences in self-regulated (SR) deep learning of successful immigrant and non-immigrant students we investigated a population of 650 high track 10th grade students in Amsterdam, of which 39% had an immigrant background. By means of a questionnaire based on the MSLQ
Luu, Trong Tuan
Purpose: This research aims to examine whether there is the chain effect from corporate social responsibility (CSR) and emotional intelligence (EI) to organizational learning and competitive intelligence in chemical companies in a Vietnam business setting. Design/methodology/approach: Structural equation modeling (SEM) approach was used to analyze…
Duffy, S. M.; Duffy, Alex
In this paper the need for Intelligent Computer Aided Design (Int.CAD) to jointly support design and learning assistance is introduced. The paper focuses on presenting and exploring the possibility of realizing ''learning'' assistance in Int.CAD by introducing a new concept called Shared Learning...
Vostroknutov, Alexander; Polonio, Luca; Coricelli, Giorgio
Studies in cultural evolution have uncovered many types of social learning strategies that are adaptive in certain environments. The efficiency of these strategies also depends on the individual characteristics of both the observer and the demonstrator. We investigate the relationship between intelligence and the ways social and individual information is utilised to make decisions in an uncertain environment. We measure fluid intelligence and study experimentally how individuals learn from observing the choices of a demonstrator in a 2-armed bandit problem with changing probabilities of a reward. Participants observe a demonstrator with high or low fluid intelligence. In some treatments they are aware of the intelligence score of the demonstrator and in others they are not. Low fluid intelligence individuals imitate the demonstrator more when her fluid intelligence is known than when it is not. Conversely, individuals with high fluid intelligence adjust their use of social information, as the observed behaviour changes, independently of the knowledge of the intelligence of the demonstrator. We provide evidence that intelligence determines how social and individual information is integrated in order to make choices in a changing uncertain environment.
Full Text Available This paper develops a theoretical framework for employing learning analytics in online education to trace multiple learning variations of online students by considering their potential of being multiple intelligences based on Howard Gardner’s 1983 theory of multiple intelligences. The study first emphasizes the need to facilitate students as multiple intelligences by online education systems and then suggests a framework of the advanced form of learning analytics i.e., multimodal learning analytics for tracing and facilitating multiple intelligences while they are engaged in online ubiquitous learning. As multimodal learning analytics is still an evolving area, it poses many challenges for technologists, educationists as well as organizational managers. Learning analytics make machines meet humans, therefore, the educationists with an expertise in learning theories can help technologists devise latest technological methods for multimodal learning analytics and organizational managers can implement them for the improvement of online education. Therefore, a careful instructional design based on a deep understanding of students’ learning abilities, is required to develop teaching plans and technological possibilities for monitoring students’ learning paths. This is how learning analytics can help design an adaptive instructional design based on a quick analysis of the data gathered. Based on that analysis, the academicians can critically reflect upon the quick or delayed implementation of the existing instructional design based on students’ cognitive abilities or even about the single or double loop learning design. The researcher concludes that the online education is multimodal in nature, has the capacity to endorse multiliteracies and, therefore, multiple intelligences can be tracked and facilitated through multimodal learning analytics in an online mode. However, online teachers’ training both in technological implementations and
Alharbi, Mafawez; Jemmali, Mahdi
Many institutions and university has forced to use e learning, due to its ability to provide additional and flexible solutions for students and researchers. E-learning In the last decade have transported about the extreme changes in the distribution of education allowing learners to access multimedia course material at any time, from anywhere to suit their specific needs. In the form of e learning, instructors and learners live in different places and they do not engage in a classroom environment, but within virtual universe. Many researches have defined e learning based on their objectives. Therefore, there are small number of e-learning architecture have proposed in the literature. However, the proposed architecture has lack of embedding intelligent system in the architecture of e learning. This research argues that unexplored potential remains, as there is scope for e learning to be intelligent system. This research proposes e-learning architecture that incorporates intelligent system. There are intelligence components, which built into the architecture.
Tamez, Elaine; Myerson, Joel; Hale, Sandra
Based on early findings showing low correlations between intelligence test scores and learning on laboratory tasks, psychologists typically have dismissed the role of learning in intelligence and emphasized the role of working memory instead. In 2006, however, B.A. Williams developed a verbal learning task inspired by three-term reinforcement contingencies and reported unexpectedly high correlations between this task and Raven's Advanced Progressive Matrices (RAPM) scores [Williams, B.A., Pearlberg, S.L., 2006. Learning of three-term contingencies correlates with Raven scores, but not with measures of cognitive processing. Intelligence 34, 177-191]. The present study replicated this finding: Performance on the three-term learning task explained almost 25% of the variance in RAPM scores. Adding complex verbal working memory span, measured using the operation span task, did not improve prediction. Notably, this was not due to a lack of correlation between complex working memory span and RAPM scores. Rather, it occurred because most of the variance captured by the complex working memory span was already accounted for by the three-term learning task. Taken together with the findings of Williams and Pearlberg, the present results make a strong case for the role of learning in performance on intelligence tests.
Hansen, Keith A.
Intelligence agencies play a fundamental role in the prevention of nuclear proliferation, as they help to understand other countries' intentions and assess their technical capabilities and the nature of their nuclear activities. The challenges in this area remain, however, formidable. Past experiences and the discoveries of Iraq's WMD programs, of North Korean nuclear weapon program, and of Iranian activities, have put into question the ability of intelligence to monitor small, clandestine proliferation activities from either states or non-state entities. This Proliferation Paper analyzes the complex challenges intelligence faces and the various roles it plays in supporting national and international nuclear non-proliferation efforts, and reviews its track record. In an effort to shed light on the role and contribution of intelligence in national and international efforts to halt, if not prevent, further nuclear weapon proliferation, this paper first analyzes the challenges intelligence faces in monitoring small, clandestine proliferation activities and the role it plays in supporting non-proliferation efforts. It then reviews the intelligence track record in monitoring proliferation including the lessons learned from Iraq. Finally, it addresses whether it is possible for intelligence to accurately monitor future clandestine proliferation efforts. (author)
This core assessment provides an overview and training of the use of Emotional Intelligence (EI) in the workplace. It includes a needs analysis for a local Chamber of Commerce, and outlines the importance of improving their organizational communication with the improvement of their EI. Behavioral objectives related to the skills needed are…
Tan, Yin Leng; Macaulay, Linda A.
Employers increasingly demand not only academic excellence from graduates but also excellent interpersonal skills and the ability to work collaboratively in teams. This paper discusses the role of Group Intelligence software in helping to develop these higher order skills in the context of an enquiry based learning (EBL) project. The software supports teams in generating ideas, categorizing, prioritizing, voting and multi-criteria decision making and automatically generates a report of each team session. Students worked in a Group Intelligence lab designed to support both face to face and computer-mediated communication and employers provided feedback at two key points in the year long team project. Evaluation of the effectiveness of Group Intelligence software in collaborative learning was based on five key concepts of creativity, participation, productivity, engagement and understanding.
Full Text Available Mainstream distance learning nowadays is heavily influenced by traditional educational approaches that produceshomogenised learning scenarios for all learners through learning management systems. Any differentiation betweenlearners and personalisation of their learning scenarios is left to the teacher, who gets minimum support from the system inthis respect. This way, the truly digital native, the computer, is left out of the move, unable to better support the teachinglearning processes because it is not provided with the means to transform into knowledge all the information that it storesand manages. I believe learning management systems should care for supporting adaptation and personalisation of bothindividual learning and the formation of communities of learning. Open learner modelling and intelligent collaborativelearning environments are proposed as a means to care. The proposal is complemented with a general architecture for anintelligent environment for distance learning and an educational model based on the principles of self-management,creativity, significance and participation.
How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.
How can a machine learn from experience? Probabilistic modelling provides a framework for understanding what learning is, and has therefore emerged as one of the principal theoretical and practical approaches for designing machines that learn from data acquired through experience. The probabilistic framework, which describes how to represent and manipulate uncertainty about models and predictions, has a central role in scientific data analysis, machine learning, robotics, cognitive science and artificial intelligence. This Review provides an introduction to this framework, and discusses some of the state-of-the-art advances in the field, namely, probabilistic programming, Bayesian optimization, data compression and automatic model discovery.
Tsai, Jinn-Tsong; Chou, Ping-Yi; Fang, Jia-Cen
An intelligent genetic algorithm (IGA) is proposed to solve Japanese nonograms and is used as a method in a university course to learn evolutionary algorithms. The IGA combines the global exploration capabilities of a canonical genetic algorithm (CGA) with effective condensed encoding, improved fitness function, and modified crossover and…
Araya, A A
Intelligent systems should possess two fundamental capabilities: problem solving and learning. Problem solving capabilities allow an intelligent system to cope with problems in a given domain. Learning capabilities make possible for an intelligent system to improve the solution to the problems within its current reach or to cope with new problems. This paper examines research in artificial intelligence from the perspective of learning with the purpose of: 1) developing and understanding of the problem of learning from the AI point of view, and II) characterizing the current state of the art on learning in AI. 35 references.
Takeuchi, Miwa Aoki
This study examined immigrant parents' involvement in early years mathematics learning, focusing on learning of multiplication in in- and out-of-school settings. Ethnographic interviews and workshops were conducted in an urban city in Japan, to examine out-of-school practices of immigrant families. Drawing from sociocultural theory of learning and…
Andreae, John H
The explanation of brain functioning in terms of the association of ideas has been popular since the 17th century. Recently, however, the process of association has been dismissed as computationally inadequate by prominent cognitive scientists. In this book, a sharper definition of the term "association" is used to revive the process by showing that associative learning can indeed be computationally powerful. Within an appropriate organization, associative learning can be embodied in a robot to realize a human-like intelligence, which sets its own goals, exhibits unique unformalizable behaviou
Sener, Sabriye; Çokçaliskan, Ayten
Exploring learning style and multiple intelligence type of learners can enable the students to identify their strengths and weaknesses and learn from them. It is also very important for teachers to understand their learners' learning styles and multiple intelligences since they can carefully identify their goals and design activities that can…
Amitay, Sygal; Halliday, Lorna; Taylor, Jenny; Sohoglu, Ediz; Moore, David R
Although feedback on performance is generally thought to promote perceptual learning, the role and necessity of feedback remain unclear. We investigated the effect of providing varying amounts of positive feedback while listeners attempted to discriminate between three identical tones on learning frequency discrimination. Using this novel procedure, the feedback was meaningless and random in relation to the listeners' responses, but the amount of feedback provided (or lack thereof) affected learning. We found that a group of listeners who received positive feedback on 10% of the trials improved their performance on the task (learned), while other groups provided either with excess (90%) or with no feedback did not learn. Superimposed on these group data, however, individual listeners showed other systematic changes of performance. In particular, those with lower non-verbal IQ who trained in the no feedback condition performed more poorly after training. This pattern of results cannot be accounted for by learning models that ascribe an external teacher role to feedback. We suggest, instead, that feedback is used to monitor performance on the task in relation to its perceived difficulty, and that listeners who learn without the benefit of feedback are adept at self-monitoring of performance, a trait that also supports better performance on non-verbal IQ tests. These results show that 'perceptual' learning is strongly influenced by top-down processes of motivation and intelligence.
Becker, Lee A.
Presents and develops a general model of the nature of a learning system and a classification for learning systems. Highlights include the relationship between artificial intelligence and cognitive psychology; computer-based instructional systems; intelligent instructional systems; and the role of the learner's knowledge base in an intelligent…
Deliyska, B.; Rozeva, A.
The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e-learning in an online learner-centered environment. ILS is a distributed e-learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e-learning is achieved through the resources of the Semantic Web and is designed and developed around a course, group of courses or specialty. An essential part of ILS is learner model database which contains structured data about learner profile and temporal status in the learning process of one or more courses. In the paper a learner model position in ILS is considered and a relational database is designed from learner's domain ontology. Multidimensional modeling agent for the source database is designed and resultant learner data cube is presented. Agent's modules are proposed with corresponding algorithms and procedures. Multidimensional (OLAP) analysis guidelines on the resultant learner module for designing dynamic learning strategy have been highlighted.
Full Text Available Learning is the long process of transforming information as well as experience into knowledge, skills, attitude and behaviors. To make up the wide gap between the demand of increasing higher education and comparatively limited resources, more and more educational institutes are looking into instructional technology. Use of online resources not only reduces the cost of education but also meet the needs of society. Intelligent e-learning has become one of the important channels to reach out to students exceeding geographic boundaries. Besides this, the characteristics of e-learning have complicated the process of education, and have brought challenges to both instructors and students. This paper will focus on the discussion of different discipline of intelligent e-learning like scaffolding based e-learning, personalized e-learning, confidence based e-learning, intelligent tutoring system, etc. to illuminate the educational paradigm shift in intelligent e-learning system.
HAMAD, Zaina Mustafa Mahmoud; YOZGAT, Ugur
Performinga strong intelligence grants an organization a guaranteeof long-term success. This paper investigates the enhancing effect of organizational learning capabilities on competitive intelligence atthe commercial banks in Jordan. A sample within top and middle managements was used.Measurement instrument validity and model fit were assessed before testinghypotheses. This study emphasizes the role learning capability plays inenhancing intelligence. Key findings support importance of organi...
Capuano, Nicola; Gaeta, Matteo; Marengo, Agostino; Miranda, Sergio; Orciuoli, Francesco; Ritrovato, Pierluigi
Intelligent e-learning systems have revolutionized online education by providing individualized and personalized instruction for each learner. Nevertheless, until now very few systems were able to leave academic laboratories and be integrated into real commercial products. One of these few exceptions is the Learning Intelligent Advisor (LIA)…
Inglés, Cándido J.; Martínez-Monteagudo, María C.; Pérez Fuentes, Maria C.; García-Fernández, José M.; Molero, María del Mar; Suriá-Martinez, Raquel; Gázquez, José J.
The aim of this study was to analyse the relationship among emotional intelligence (EI) and learning strategies, identifying different emotional intelligence profiles and determining possible statistically significant differences in learning strategies through the identified profiles. Thousand and seventy-one Spaniards secondary school students…
Das, J; O’Connor, Neil
This volume contains the Proceedings of an International Conference on Intelligence and Learning held at York University, England, on July 16-20, 1979. The conference was made possible with the support and assistance of the following agencies: NAT 0 Scientific Division, specifically the Human Factors panel, was the major sponsor of the conference. Special thanks are due to Dr. B. A. Bayraktar, who helped organize the conference. Special appreciation is also expressed for the support of the University of York where the conference was held, the University of Alberta, the University of California, Los Angeles, the Medical Research Council, especially its Developmental Psychology Research U nit in London, and the British Council. The conference was jointly directed by J. P. Das and N. 0' Connor. The directors appreciate the assistance in administrative matters of Patricia Chobater and Emma Collins of the University of Alberta. The Editors of the Proceedings acknowledge and appreciate the following individuals who...
Purpose: The paper aims to explore the emotion learning experiences of some Chinese immigrants in Canadian engineering workplaces. Design/methodology/approach: The paper is based on life history style interviews with 14 Chinese immigrant engineers and 14 key informant interviews. Findings: Research respondents constructed a competitive, masculine,…
Smith, Walter L.
Precepting, coaching, and mentoring are teaching methods used extensively in nursing education in U.S. healthcare facilities. Filipino nurse immigrants have cultural backgrounds that may influence their experience with and perspectives of these learning interventions. Although Filipino nurse immigrants comprise approximately 0.2% of the population…
Medeiros Vieira, Leandro Mauricio; Ferasso, Marcos; Schröeder, Christine da Silva
This theoretical essay is a learning approach reflexion on Howard Gardner's Theory of Multiple Intelligences and the possibilities provided by the education model known as open and distance learning. Open and distance learning can revolutionize traditional pedagogical practice, meeting the needs of those who have different forms of cognitive…
Shute, Valerie J.
"Smithtown" is an intelligent computer program designed to enhance an individual's scientific inquiry skills as well as to provide an environment for learning principles of basic microeconomics. It was hypothesized that intelligent computer instruction on applying effective interrogative skills (e.g., changing one variable at a time…
van Schaik, Carel P.; Burkart, Judith M.
If social learning is more efficient than independent individual exploration, animals should learn vital cultural skills exclusively, and routine skills faster, through social learning, provided they actually use social learning preferentially. Animals with opportunities for social learning indeed do so. Moreover, more frequent opportunities for social learning should boost an individual's repertoire of learned skills. This prediction is confirmed by comparisons among wild great ape populations and by social deprivation and enculturation experiments. These findings shaped the cultural intelligence hypothesis, which complements the traditional benefit hypotheses for the evolution of intelligence by specifying the conditions in which these benefits can be reaped. The evolutionary version of the hypothesis argues that species with frequent opportunities for social learning should more readily respond to selection for a greater number of learned skills. Because improved social learning also improves asocial learning, the hypothesis predicts a positive interspecific correlation between social-learning performance and individual learning ability. Variation among primates supports this prediction. The hypothesis also predicts that more heavily cultural species should be more intelligent. Preliminary tests involving birds and mammals support this prediction too. The cultural intelligence hypothesis can also account for the unusual cognitive abilities of humans, as well as our unique mechanisms of skill transfer. PMID:21357223
van Schaik, Carel P; Burkart, Judith M
If social learning is more efficient than independent individual exploration, animals should learn vital cultural skills exclusively, and routine skills faster, through social learning, provided they actually use social learning preferentially. Animals with opportunities for social learning indeed do so. Moreover, more frequent opportunities for social learning should boost an individual's repertoire of learned skills. This prediction is confirmed by comparisons among wild great ape populations and by social deprivation and enculturation experiments. These findings shaped the cultural intelligence hypothesis, which complements the traditional benefit hypotheses for the evolution of intelligence by specifying the conditions in which these benefits can be reaped. The evolutionary version of the hypothesis argues that species with frequent opportunities for social learning should more readily respond to selection for a greater number of learned skills. Because improved social learning also improves asocial learning, the hypothesis predicts a positive interspecific correlation between social-learning performance and individual learning ability. Variation among primates supports this prediction. The hypothesis also predicts that more heavily cultural species should be more intelligent. Preliminary tests involving birds and mammals support this prediction too. The cultural intelligence hypothesis can also account for the unusual cognitive abilities of humans, as well as our unique mechanisms of skill transfer.
Full Text Available The Effect of Emotional Intelligence Against Student Achievement aims to determine the effect of emotional intelligence which consists of self awareness, self management, Motivation, social awareness, relationship management partially and simultaneously on learning achievement. Respondents are students of SMP Negeri 4 Lalan Bumi Agung Vilage Musi Banyuasin Regency to be 135 people. Methods of data analysis using regression analysis techniques. Partial assay results (t-test showed emotional intelligence consists of Self awareness, self management, Motivation, social awareness, relationship management positive and significant effect on learning achievement. Simultaneous Test Results (Test-F emotional intelligence consists of Self awareness, self management, motivation, social awareness, relationship management and significant positive effect on learning achievement. Social awareness is more dominant influence on learning achievement.
Shaalan, Khaled F.
This paper describes the development of an intelligent computer-assisted language learning (ICALL) system for learning Arabic. This system could be used for learning Arabic by students at primary schools or by learners of Arabic as a second or foreign language. It explores the use of Natural Language Processing (NLP) techniques for learning…
Machine Learning is a type of artificial intelligence that provides machines or networks the ability to learn from data without the need to explicitly program them. There are different kinds of machine learning techniques. This thesis discusses the applications of two of these approaches: Genetic Fuzzy Logic and Convolutional Neural Networks (CNN). Fuzzy Logic System (FLS) is a powerful tool that can be used for a wide variety of applications. FLS is a universal approximator that reduces the need for complex mathematics and replaces it with expert knowledge of the system to produce an input-output mapping using If-Then rules. The expert knowledge of a system can help in obtaining the parameters for small-scale FLSs, but for larger networks we will need to use sophisticated approaches that can automatically train the network to meet the design requirements. This is where Genetic Algorithms (GA) and EVE come into the picture. Both GA and EVE can tune the FLS parameters to minimize a cost function that is designed to meet the requirements of the specific problem. EVE is an artificial intelligence developed by Psibernetix that is trained to tune large scale FLSs. The parameters of an FLS can include the membership functions and rulebase of the inherent Fuzzy Inference Systems (FISs). The main issue with using the GFS is that the number of parameters in a FIS increase exponentially with the number of inputs thus making it increasingly harder to tune them. To reduce this issue, the FLSs discussed in this thesis consist of 2-input-1-output FISs in cascade (Chapter 4) or as a layer of parallel FISs (Chapter 7). We have obtained extremely good results using GFS for different applications at a reduced computational cost compared to other algorithms that are commonly used to solve the corresponding problems. In this thesis, GFSs have been designed for controlling an inverted double pendulum, a task allocation problem of clustering targets amongst a set of UAVs, a fire
Gennari, Rosella; Vitorini, Pierpaolo; Vicari, Rosa; Prieta, Fernando
This volume presents recent research on Methodologies and Intelligent Systems for Technology Enhanced Learning. It contains the contributions of ebuTEL 2013 conference which took place in Trento, Italy, on September, 16th 2013 and of mis4TEL 2014 conference, which took take place in Salamanca, Spain, on September, 4th-6th 2014 This conference series are an open forum for discussing intelligent systems for Technology Enhanced Learning and empirical methodologies for its design or evaluation.
Dunjko, Vedran; Briegel, Hans J.
Quantum information technologies, and intelligent learning systems, are both emergent technologies that will likely have a transforming impact on our society. The respective underlying fields of research -- quantum information (QI) versus machine learning (ML) and artificial intelligence (AI) -- have their own specific challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question to what extent th...
Duo, Sun; Ying, Zhou Cai
Lack of personalized learning is the key shortcoming of traditional e-Learning system. This paper analyzes the personal characters in e-Learning activity. In order to meet the personalized e-learning, a personalized e-learning system based on intelligent agent was proposed and realized in the paper. The structure of system, work process, the design of intelligent agent and the realization of intelligent agent were introduced in the paper. After the test use of the system by certain network school, we found that the system could improve the learner's initiative participation, which can provide learners with personalized knowledge service. Thus, we thought it might be a practical solution to realize self- learning and self-promotion in the lifelong education age.
The aim of this essay to draw an outline of the effect of various types of intelligence, paying particular attention to the concept of so called "Emotional Intelligence" with a language teacher's perspective. Throughout the essay it is aimed to create an awareness of different intelligence capacity of each individual learner in an ideal language teaching environment. While doing this literature on the area has been scanned and case studies have been performed on learners of various cultu...
Lopes, Manuel; Montesano, Luis
In this survey we present different approaches that allow an intelligent agent to explore autonomous its environment to gather information and learn multiple tasks. Different communities proposed different solutions, that are in many cases, similar and/or complementary. These solutions include active learning, exploration/exploitation, online-learning and social learning. The common aspect of all these approaches is that it is the agent to selects and decides what information to gather next. ...
The immigrant population is growing in rural Minnesota, and those who are interested in farming will be replacing a dwindling population of traditionally white farmers. Like traditional American farmers, immigrant farmers have a need for continuing education to keep them up on best practices and new technology in agriculture. Minnesota's…
Bredeweg, Bert; Liem, Jochem; Beek, Wouter; Linnebank, Floris; Gracia, Jorge; Lozano, Esther; Wißner, Michael; Bühling, René; Salles, Paulo; Noble, Richard; Zitek, Andreas; Borisova, Petya; Mioduser, David
Articulating thought in computerbased media is a powerful means for humans to develop their understanding of phenomena. We have created DynaLearn, an intelligent learning environment that allows learners to acquire conceptual knowledge by constructing and simulating qualitative models of how systems
Sternberg, Robert J.
Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301
Sternberg, Robert J
Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.
Dias, Sofia B; Hadjileontiadis, Leontios J
This book offers useful information that evokes initiatives towards rethinking of the value, efficiency, inclusiveness, effectiveness and personalization of the intelligent learning management systems-based blended-learning environment.
Page, Robin L
To provide an integrated review of the literature of potential explanations for better than expected pregnancy outcomes in Mexican immigrants, focusing on socioeconomics, social support, desirability of pregnancy, nutrition, substance use, religion, acculturation, and prenatal care. Computerized searches of MEDLINE and CINAHL databases, as well as reference lists from published articles on low birth weight and prematurity in immigrants and acculturation in immigrants from January 1989 to December 2002. Search terms were Mexican immigrant women, childbearing, and pregnancy outcome, and only English-language articles were reviewed. Literature was selected from refereed publications in the areas of nursing, medicine, public health, family, and sociology. Data were extracted using keywords pertinent to pregnancy outcome in Mexican immigrants. Despite having many of the risk factors for poor pregnancy outcomes, Mexican immigrants have superior birth outcomes when compared to U.S.-born women. Social support, familism, healthy diet, limited use of cigarettes and alcohol, and religion may play a role in improved outcomes. The superior outcomes diminish with the process of acculturation as the individual adapts to her new culture. Low birth weight and prematurity are public health concerns in the United States. Through further study of the factors that lead to superior birth outcomes among Mexican immigrant women, rates of low birth weight and prematurity in the United States may be reduced.
Zongyao, Wang; Cong, Sui; Cheng, Shao
Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.
Background: The term digital natives refer to those born since the 1980s and have been growing up surrounded by technology. On the other hand, digital immigrants are born before 1980s and learned how to use technology later in life. Objectives: Goal of the paper is to explore attitudes of digital native students on the course of Business Informatics at higher educational institutions (HEIs), and to compare them with attitudes of digital immigrants. Methods/Approach: The survey was conducted i...
Sutiani, Ani; Silitonga, Mei Y.
This research focused on the effect of learning models and emotional intelligence in students' chemistry learning outcomes on reaction rate teaching topic. In order to achieve the objectives of the research, with 2x2 factorial research design was used. There were two factors tested, namely: the learning models (factor A), and emotional intelligence (factor B) factors. Then, two learning models were used; problem-based learning/PBL (A1), and project-based learning/PjBL (A2). While, the emotional intelligence was divided into higher and lower types. The number of population was six classes containing 243 grade X students of SMAN 10 Medan, Indonesia. There were 15 students of each class were chosen as the sample of the research by applying purposive sampling technique. The data were analyzed by applying two-ways analysis of variance (2X2) at the level of significant α = 0.05. Based on hypothesis testing, there was the interaction between learning models and emotional intelligence in students' chemistry learning outcomes. Then, the finding of the research showed that students' learning outcomes in reaction rate taught by using PBL with higher emotional intelligence is higher than those who were taught by using PjBL. There was no significant effect between students with lower emotional intelligence taught by using both PBL and PjBL in reaction rate topic. Based on the finding, the students with lower emotional intelligence were quite hard to get in touch with other students in group discussion.
Amin, Hafeez Ullah; Malik, Aamir Saeed; Kamel, Nidal; Chooi, Weng-Tink; Hussain, Muhammad
Educational psychology research has linked fluid intelligence with learning and memory abilities and neuroimaging studies have specifically associated fluid intelligence with event related potentials (ERPs). The objective of this study is to find the relationship of ERPs with learning and memory recall and predict the memory recall score using P300 (P3) component. A sample of thirty-four healthy subjects between twenty and thirty years of age was selected to perform three tasks: (1) Raven's Advanced Progressive Matrices (RAPM) test to assess fluid intelligence; (2) learning and memory task to assess learning ability and memory recall; and (3) the visual oddball task to assess brain-evoked potentials. These subjects were divided into High Ability (HA) and Low Ability (LA) groups based on their RAPM scores. A multiple regression analysis was used to predict the learning & memory recall and fluid intelligence using P3 amplitude and latency. Behavioral results demonstrated that the HA group learned and recalled 10.89 % more information than did the LA group. ERP results clearly showed that the P3 amplitude of the HA group was relatively larger than that observed in the LA group for both the central and parietal regions of the cerebrum; particularly during the 300-400 ms time window. In addition, a shorter latency for the P3 component was observed at Pz site for the HA group compared to the LA group. These findings agree with previous educational psychology and neuroimaging studies which reported an association between ERPs and fluid intelligence as well as learning performance. These results also suggest that the P3 component is associated with individual differences in learning and memory recall and further indicate that P3 amplitude might be used as a supporting factor in standard psychometric tests to assess an individual's learning & memory recall ability; particularly in educational institutions to aid in the predictability of academic skills.
Full Text Available E-learning is basically the integration of various technologies. E-Learning technology is now maturing and we can find a multiplicity of standards. New technologies such as agents and web services are promising better results. In this paper we have proposed an e-learning architecture that is dependent on intelligent agent systems and web services. These communication technologies will make the architecture more robust, scalable and efficient.
This article explores the situated meanings of literacy and lifelong learning in the lives of a selected group of first-generation immigrant Iranian women in Canadian institutions of higher education. Drawing from the participants' narratives, the results of this study suggest that, for these women, lifelong learning was greatly influenced by…
This article examines Canadian immigrant and intercultural learning as an insightful context for examining transformative learning. Theories of intercultural communication are explored, particularly the concept of transculturality and Bhabha's concept of "Third Space". Various concepts of the self are also compared, particularly two…
Full Text Available With the development of Chinese economy, oversea Chinese education has been paid more and more attention. However, the overseas Chinese education resource is relatively lack because of historical reasons, which hindered further development . How to better share the Chinese education resources and provide intelligent personalized information service for overseas student is a key problem to be solved. In recent years, the rise of cloud computing provides us an opportunity to realize intelligent learning mode. Cloud computing offers some advantages by allowing users to use infrastructure, platforms and software . In this paper we proposed an intelligent cloud learning model based on cloud computing. The learning model can utilize network resources sufficiently to implement resource sharing according to the personal needs of students, and provide a good practicability for online overseas Chinese education.
Gennari, Rosella; Vittorini, Pierpaolo; Prieta, Fernando
This volume presents recent research on Methodologies and Intelligent Systems for Technology Enhanced Learning. It contains the contributions of MIS4TEL 2015, which took place in Salamanca, Spain,. On June 3rd to 5th 2015. Like the previous edition, this proceedings and the conference is an open forum for discussing intelligent systems for Technology Enhanced Learning and empirical methodologies for their design or evaluation MIS4TEL’15 conference has been organized by University of L’aquila, Free University of Bozen-Bolzano and the University of Salamanca. .
Samigulina, Galina; Shayakhmetova, Assem; Nuysuppov, Adlet
The aim of the study is to develop innovative intelligent technology and information systems of distance education for people with impaired vision (PIV). To solve this problem a comprehensive approach has been proposed, which consists in the aggregate of the application of artificial intelligence methods and statistical analysis. Creating an accessible learning environment, identifying the intellectual, physiological, psychophysiological characteristics of perception and information awareness by this category of people is based on cognitive approach. On the basis of fuzzy logic the individually-oriented learning path of PIV is con- structed with the aim of obtaining high-quality engineering education with modern equipment in the joint use laboratories.
Full Text Available The aim of the study is to develop innovative intelligent technology and information systems of distance education for people with impaired vision (PIV. To solve this problem a comprehensive approach has been proposed, which consists in the aggregate of the application of artificial intelligence methods and statistical analysis. Creating an accessible learning environment, identifying the intellectual, physiological, psychophysiological characteristics of perception and information awareness by this category of people is based on cognitive approach. On the basis of fuzzy logic the individually-oriented learning path of PIV is con- structed with the aim of obtaining high-quality engineering education with modern equipment in the joint use laboratories.
Asma’a Abdulrazzaq Al-Mahbashi
Full Text Available Over the past decades, the potential for the direct use of corpora known as data driven learning (DDL has gained great prominence in English language classrooms. A substantial number of empirical studies demonstrated that DDL instruction positively affects students’ learning. As learning outcomes can be affected by individual differences, some researchers have investigated the efficiency of DDL in the light of learners’ different characteristics to determine the type of learners who were more responsive to DDL. The DDL literature has indicated the need for more research addressing for whom DDL best suits. Therefore, the aim of the current study was to examine whether or not learners’ predominant intelligences were significant predictors of DDL learning outcomes. The sample for this study included 30 female EFL Yemeni students at Sana’a University. The study used three primary instruments: a multiple intelligence questionnaire, a posttest and a delayed test on the vocabulary that was taught using DDL. The result of the correlation analyses between the participants’ three identified predominant intelligences and their performances in the posttest and delayed test showed an insignificant relationship between the variables. The regression analyses results also revealed that the predominant intelligences insignificantly predicted the participants’ posttest and delayed test performances. Based on these findings, learners’ needs and preferences should be activated and addressed by classroom instructions for creating a diverse and motivating learning environment.
Gracious, F. L. Antony; Shyla, F. L. Jasmine Anne
The present study Multiple Intelligence and Digital Learning Awareness of prospective B.Ed teachers was probed to find the relationship between Multiple Intelligence and Digital Learning Awareness of Prospective B.Ed Teachers. Data for the study were collected using self made Multiple Intelligence Inventory and Digital Learning Awareness Scale.…
Jerome Bruner identified three major ways of knowing: iconic, enactive, and symbolic. Schooling has been dominantly framed in the symbolic, and intelligence and achievement were measured in this realm. Gregory Bateson, concerned with mind-nature separation, differentiated between the map (a human-made abstraction) and the territory (the natural…
The development of computers and artificial intelligence theory allow their application in the field of education. Intelligent tutoring systems reflect student learning styles and adapt the curriculum according to their individual needs. The building of intelligent tutoring systems requires not only the creation of suitable software, but especially the search and application of the rules enabling ICT to individually adapt the curriculum. The main idea of this paper is to attempt to specify the rules for dividing the students to systematically working students and more practically or pragmatically inclined students. The paper shows that monitoring the work of students in e-learning environment, analysis of various approaches to educational materials and correspondence assignments show different results for the defined groups of students.
Full Text Available This article identifies and deconstructs the ways in which professionally successful adult immigrants to Canada chose to interact with and reshape different environments in order to foster their English learning process. The sample for this study was selected to be representative of the “brain gain” immigration wave to Canada of the last two decades. All 20 participants belong to the same category of highly-educated (17+ years of education, independent immigrants who came to Canada as young adults. The data collection process consisted of a series of three interviews with each participant. The data were analyzed following the principles of the grounded theory method. Several qualitative themes associated with learning English as an adult immigrant in various types of environments in Canada (instructed environments, ‘manipulated’ naturalistic environments, and unaltered naturalistic environments emerged from the interviews with the participants. The themes are critically explored and special emphasis is laid on the ways in which participants overcame difficulties inherent in the environmental factors that were not readily structured to offer immigrants opportunities to learn and practice English.
Klašnja-Milićević, Aleksandra; Ivanović, Mirjana; Budimac, Zoran; Jain, Lakhmi C
This monograph provides a comprehensive research review of intelligent techniques for personalisation of e-learning systems. Special emphasis is given to intelligent tutoring systems as a particular class of e-learning systems, which support and improve the learning and teaching of domain-specific knowledge. A new approach to perform effective personalization based on Semantic web technologies achieved in a tutoring system is presented. This approach incorporates a recommender system based on collaborative tagging techniques that adapts to the interests and level of students' knowledge. These innovations are important contributions of this monograph. Theoretical models and techniques are illustrated on a real personalised tutoring system for teaching Java programming language. The monograph is directed to, students and researchers interested in the e-learning and personalization techniques. .
Autonomous lifelong development and learning are fundamental capabilities of humans, differentiating them from current deep learning systems. However, other branches of artificial intelligence have designed crucial ingredients towards autonomous learning: curiosity and intrinsic motivation, social learning and natural interaction with peers, and embodiment. These mechanisms guide exploration and autonomous choice of goals, and integrating them with deep learning opens stimulating perspectives.
This paper describes the once-weekly psychoanalytic psychotherapy of a girl, called Ellie, aged eight at the start of her treatment. Ellie had a learning disability and displayed difficult behaviour at school and at home. In her therapy, Ellie grew in emotional intelligence, more in touch with and able to express her feelings. Her behaviour…
Upadhyay, Nitin; Agarwal, Vishnu Prakash
This paper proposes a methodology using graph theory, matrix algebra and permanent function to compare different architecture (structure) design of intelligent mobile learning environment. The current work deals with the development/selection of optimum architecture (structural) model of iMLE. This can be done using the criterion as discussed in…
Olsen, Jennifer K.; Belenky, Daniel M.; Aleven, Vincent; Rummel, Nikol
Collaborative and individual instruction may support different types of knowledge. Optimal instruction for a subject domain may therefore need to combine these two modes of instruction. There has not been much research, however, on combining individual and collaborative learning with Intelligent Tutoring Systems (ITSs). A first step is to expand…
Huang, Hsin-Hsiung; Su, Juing-Huei; Lee, Chyi-Shyong
A contest-oriented project for undergraduate students to learn implementation skills and theories related to intelligent mobile robots is presented in this paper. The project, related to Micromouse, Robotrace (Robotrace is the title of Taiwanese and Japanese robot races), and line-maze contests was developed by the embedded control system research…
Jung, Sunyoung; Fuller, Bruce; Galindo, Claudia
Poverty-related developmental-risk theories dominate accounts of uneven levels of household functioning and effects on children. But immigrant parents may sustain norms and practices--stemming from heritage culture, selective migration, and social support--that buffer economic exigencies. "Comparable" levels of social-emotional functioning in…
Chen, Shengqing; Huang, Xiaojian; Fang, Jiaze; Liang, Jia
The reasoning system can be used in many fields. How to improve reasoning efficiency is the core of the design of system. Through the formal description of formal proof and the regular matching algorithm, after introducing the machine learning algorithm, the system of intelligent formal reasoning and verification has high efficiency. The experimental results show that the system can verify the correctness of propositional logic reasoning and reuse the propositional logical reasoning results, so as to obtain the implicit knowledge in the knowledge base and provide the basic reasoning model for the construction of intelligent system.
Larsen, Lasse Juel; Helms, Niels Henrik
of tangible learning media and develop didactic approaches for teachers in primary school and furthermore to use the user experiences in a structured process where children participated in the innovation process. This has raised a fundamental question: How should we understand the relationship between......This short paper outlines experiences and reflections on the research and development project “Octopus” in order to describe and illustrate how intelligent context facilitates and embody learning. The framework is a research and development project where we have tried to work with new kinds......, embodiment, intelligent contexts, structure and flow. This paper does this through Bachtins concept of “Chronotopos” or how time and space influence and structure experience and learning....
Eamer, Allyson; Fernando, Shanti; King, Alyson E.
This qualitative study explores the reflexive relationships among mental illness, acculturation, and progress toward English proficiency in five adult immigrants being treated at a Canadian psychiatric hospital. The research explores the additional challenges faced by mentally ill individuals when learning a new language and the extent to which…
Adamuti-Trache, Maria; Anisef, Paul; Sweet, Robert
Immigrant women to Canada face unique challenges in gaining mastery of English or French, the country's two official languages. The study focuses on differences "among women" with respect to pre-migration and post-migration characteristics that position them differently with respect to language learning in the social contexts where they…
Souto-Manning, Mariana; Dernikos, Bessie; Yu, Hae Min
In light of the historical failure of boys of color in US schools, this article sheds light onto the ways in which normative discourses of literacy and learning shape the experiences of immigrant boys and how they are perceived and defined as un/successful students. Findings indicate that although these boys--deemed to be "at-risk" or…
Mahofa, Ernest; Adendorff, Stanley; Kwenda, Chiwimbiso
The aim of this study was to explore the learning of mathematics word problems by African immigrant early learners in the Western Cape Province of South Africa (SA). Phenomenology was used as the philosophical underpinning for this study and also informed the research method. Purposive sampling methods were used to select 10 African immigrant…
Bitew, Getnet; Ferguson, Peter
This article investigates the effect of cultural difference on the secondary school induction and learning of Ethiopian-Australian immigrant students living in Melbourne, Australia. A qualitative methodology was employed using interviews as data-collection instruments. Secondary school students, their teachers, and parents acted as participants in…
An E-learning system based on a multi-agent (MAS) architecture combined with the Dynamic Content Manager (DCM) model of E-learning, is presented. We discuss the benefits of using such a multi-agent architecture. Finally, the MAS architecture is compared with a pure service-oriented architecture (SOA). This MAS architecture may also be used within…
Full Text Available UFractions is a ubiquitous learning environment which combines mobile technology, tangible fraction blocks and a story-based game into a mathematical learning experience. In this paper the authors present a novel concept for monitoring a user’s...
Mehrunnisa A. Ali
Full Text Available This study examined what students in three professional programs – Nursing, Social Work, and Early Childhood Studies – could learn about working with immigrant families using narrative inquiry as a heuristic device. Data collected from the students in focus groups demonstrated their capacity for ethical caring by recognizing individual characteristics of immigrant families, becoming more self-aware in interactions with them, and noticing institutional practices from the families’ perspectives. The students also began to realize the uncertainties of professional practice, which could help promote the habit of reflection. Findings suggest that the experiment was worthwhile, albeit limited by self-reported data, a small sample, and a short duration. Dans cette étude, nous examinons ce que les étudiants inscrits dans trois programmes professionnels – soins infirmiers, travail social et études de la petite enfance – pourraient apprendre sur le travail avec des familles d’immigrants par le biais de l’enquête narrative en tant qu’instrument heuristique. Les données recueillies auprès des étudiants réunis en groupes de discussion ont indiqué que ceux-ci avaient prouvé leur aptitude à l’empathie éthique en reconnaissant les caractéristiques individuelles des familles d’immigrants, en devenant davantage conscients de leurs interactions avec ces familles et en prenant conscience des pratiques institutionnelles à partir du point de vue de ces familles. Les étudiants ont également commencé à comprendre les incertitudes de la pratique professionnelle, ce qui pourrait favoriser de meilleures habitudes de réflexion. Les résultats suggèrent que l’expérience était appréciable, bien qu’elle ait été limitée par des données auto-déclarées, un échantillon limité et une courte durée.
Full Text Available In computer-assisted education, the continuous monitoring and assessment of the learner is crucial for the delivery of personalized education to be effective. In this paper, we present a pilot application of the Student Diagnosis, Assistance, Evaluation System based on Artificial Intelligence (StuDiAsE, an open learning system for unattended student diagnosis, assistance and evaluation based on artificial intelligence. The system demonstrated in this paper has been designed with engineering students in mind and is capable of monitoring their comprehension, assessing their prior knowledge, building individual learner profiles, providing personalized assistance and, finally, evaluating a learner's performance both quantitatively and qualitatively by means of artificial intelligence techniques. The architecture and user interface of the system are being exhibited, the results and feedback received from a pilot application of the system within a theoretical engineering course are being demonstrated and the outcomes are being discussed.
AI based Tutoring and Learning Path Adaptation are well known concepts in e-Learning scenarios today and increasingly applied in modern learning environments. In order to gain more flexibility and to enhance existing e-learning platforms, the OPUS One LMS Extension package will enable a generic Intelligent Tutored Adaptive Learning Environment, based on a holistic Multidimensional Instructional Design Model (PENTHA ID Model), allowing AI based tutoring and adaptation functionality to existing Web-based e-learning systems. Relying on "real time" adapted profiles, it allows content- / course authors to apply a dynamic course design, supporting tutored, collaborative sessions and activities, as suggested by modern pedagogy. The concept presented combines a personalized level of surveillance, learning activity- and learning path adaptation suggestions to ensure the students learning motivation and learning success. The OPUS One concept allows to implement an advanced tutoring approach combining "expert based" e-tutoring with the more "personal" human tutoring function. It supplies the "Human Tutor" with precise, extended course activity data and "adaptation" suggestions based on predefined subject matter rules. The concept architecture is modular allowing a personalized platform configuration.
Miguel, Jorge; Xhafa, Fatos
Intelligent Data Analysis for e-Learning: Enhancing Security and Trustworthiness in Online Learning Systems addresses information security within e-Learning based on trustworthiness assessment and prediction. Over the past decade, many learning management systems have appeared in the education market. Security in these systems is essential for protecting against unfair and dishonest conduct-most notably cheating-however, e-Learning services are often designed and implemented without considering security requirements. This book provides functional approaches of trustworthiness analysis, modeling, assessment, and prediction for stronger security and support in online learning, highlighting the security deficiencies found in most online collaborative learning systems. The book explores trustworthiness methodologies based on collective intelligence than can overcome these deficiencies. It examines trustworthiness analysis that utilizes the large amounts of data-learning activities generate. In addition, as proc...
Larsen, Lasse Juel; Helms, Niels Henrik
of tangible learning media and develop didactic approaches for teachers in a primary school and furthermore to use the user experiences in a structured process where children participated in the innovation process. This has raised a fundamental question: How should we understand the relationship between....... This paper therefore aims at illustrating how and why the “Octopus” works and functions in a learning community (school) and discus the relations between distinctions, embodiment, intelligent contexts, structure and flow. This paper introduces a new reading of pervasive learning environments as the “Octopus......” through M.M. Bachtins concept of “Chronotopos” or how time and space influence and structure experience and learning. We have adapted this theory that originally is about literature in order to find new ways of understanding the time and place relation in learning....
This article addresses the inclusion of immigrant minority language students in Content and Language Integrated Learning (CLIL) bilingual education programmes. It reviews results of research on (1) the reasons, beliefs and attitudes underlying immigrant minority language parents' and students' choice for CLIL programmes; (2) these students' proficiency in the languages of instruction and their academic achievement; and (3) the effects of first language typology on their second and third language proficiency. The author explores conditions and reasons for the effectiveness of CLIL pedagogy, as well as the comparative suitability of CLIL programmes for immigrant minority language students. The review shows that CLIL programmes provide a means to acquire important linguistic, economic and symbolic capital in order to effect upward social mobility. Findings demonstrate that immigrant minority language students enrolled in CLIL programmes are able to develop equal or superior levels of proficiency in both languages of instruction compared to majority language students; with previous development of first language literacy positively impacting academic language development. CLIL programmes are found to offer immigrant minority language students educational opportunities and effective pedagogical support which existing mainstream monolingual and minority bilingual education programmes may not always be able to provide. In light of these findings, the author discusses shortcomings in current educational policy. The article concludes with recommendations for further research.[Figure not available: see fulltext.
Narli, Serkan; Ozgen, Kemal; Alkan, Huseyin
The present study aims to identify the relationship between individuals' multiple intelligence areas and their learning styles with mathematical clarity using the concept of rough sets which is used in areas such as artificial intelligence, data reduction, discovery of dependencies, prediction of data significance, and generating decision…
Da Fonseca, D; Cury, F; Bailly, D; Rufo, M
Most studies have tried to explain the school difficulties by analysing the intellectual factors that lead to school failure. However in addition to the instrumental capacities, authors also recognize the role played by other factors such as motivation. More specifically, the theory of achievement motivation aims to determine motivational factors involved in achievement situations when the students have to demonstrate their competencies. This paradigm attributes a central place to beliefs in order to explain children's behavior in academic situations. According to Dweck, it seems that beliefs about the nature of intelligence have a very powerful impact on behavior. These implicit theories of intelligence create a meaning system or conceptual framework that influences the individual interpretation of school situations. Thus, an entity theory of intelligence is the belief that intelligence is a fixed trait, a personal quality that cannot be changed. Students who subscribe to this theory believe that although people can learn new things, their underlying intelligence remains the same. In contrast, an incremental theory of intelligence is the belief that intelligence is a malleable quality that can increase through efforts. The identification of these two theories allows us to understand the cognition and behavior of individuals in achievement situations. Many studies carried out in the academic area show that students who hold an entity theory of intelligence (ie they consider intelligence like a stable quality) have a strong tendency to attribute their failures to a fixed trait. They are more likely to blame their intelligence for ne-gative outcomes and to attribute failures to their bad intellectual ability. In contrast, students who hold an incremental theory of intelligence (ie they consider intelligence as a malleable quality) are more likely to understand the same ne-gative outcomes in terms of specific factors: they attribute them to a lack of effort. This
Full Text Available Learning styles and types of intelligence are essential features of effective learning. Discovering and creative approach could be more appropriate form of learning to the current conditions of society.
The Smart Innovation, Systems and Technologies book series encompasses the topics of knowledge, intelligence, innovation and sustainability. The aim of the series is to make available a platform for the publication of books on all aspects of single and multi-disciplinary research on these themes in order to make the latest results available in a readily-accessible form. This book is devoted to the “Intelligent and Adaptive Educational-Learning Systems”. It privileges works that highlight key achievements and outline trends to inspire future research. After a rigorous revision process twenty manuscripts were accepted and organized into four parts as follows: · Modeling: The first part embraces five chapters oriented to: 1) shape the affective behavior; 2) depict the adaptive learning curriculum; 3) predict learning achievements; 4) mine learner models to outcome optimized and adaptive e-learning objects; 5) classify learning preferences of learners. · Content: The second part encompas...
Quinton, Stephen R.
The World Wide Web (WWW) provides learners and knowledge workers convenient access to vast stores of information, so much that present methods for refinement of a query or search result are inadequate - there is far too much potentially useful material. The problem often encountered is that users usually do not recognise what may be useful until they have progressed some way through the discovery, learning, and knowledge acquisition process. Additional support is needed to structure and identify potentially relevant information, and to provide constructive feedback. In short, support for learning is needed. The learning envisioned here is not simply the capacity to recall facts or to recognise objects. The focus is on learning that results in the construction of knowledge. Although most online learning platforms are efficient at delivering information, most do not provide tools that support learning as envisaged in this chapter. It is conceivable that Web-based learning environments can incorporate software systems that assist learners to form new associations between concepts and synthesise information to create new knowledge. This chapter details the rationale and theory behind a research study that aims to evolve Web-based learning environments into 'intelligent thinking' systems that respond to natural language human input. Rather than functioning simply as a means of delivering information, it is argued that online learning solutions will 1 day interact directly with students to support their conceptual thinking and cognitive development.
Zhang, Lu; Tan, Jianjun; Han, Dan; Zhu, Hao
Machine intelligence, which is normally presented as artificial intelligence, refers to the intelligence exhibited by computers. In the history of rational drug discovery, various machine intelligence approaches have been applied to guide traditional experiments, which are expensive and time-consuming. Over the past several decades, machine-learning tools, such as quantitative structure-activity relationship (QSAR) modeling, were developed that can identify potential biological active molecules from millions of candidate compounds quickly and cheaply. However, when drug discovery moved into the era of 'big' data, machine learning approaches evolved into deep learning approaches, which are a more powerful and efficient way to deal with the massive amounts of data generated from modern drug discovery approaches. Here, we summarize the history of machine learning and provide insight into recently developed deep learning approaches and their applications in rational drug discovery. We suggest that this evolution of machine intelligence now provides a guide for early-stage drug design and discovery in the current big data era. Copyright © 2017 Elsevier Ltd. All rights reserved.
This article deals with the implementation of Multiple Intelligences supported Project-Based learning in EFL/ESL Classrooms. In this study, after Multiple Intelligences supported Project-based learning was presented shortly, the implementation of this learning method into English classrooms. Implementation process of MI supported Project-based…
This dissertation is a presentation of a theoretical model of an intelligent Learning System (ILS). The approach view intelligent computer-based instruction on a curricular-level and educational-theory base, instead of the conventional instructional-only level. The ILS is divided into two components: (1) macro-level, curricular; and (2) micro-level (MAIS), instructional. The primary purpose of the ILS macro level is to establish the initial conditions of learning by considering individual difference variables within specification of the curriculum content domain. Second, the ILS macro-level will iteratively update the conditions of learning as the individual student progresses through the given curriculum. The term dynamic is used to describe the expert tutor that establishes and monitors the conditions of instruction between the ILS macro level and the micro level. As the student progresses through the instruction, appropriate information is sent back continuously to the macro level to constantly improve decision making for succeeding conditions of instruction.
The aim of this paper is to introduce the importance of emotional intelligence and the extent to which emotional intelligence can be implemented and used to improve language teaching and learning. Since emotional intelligence is perceived to play a crucial part in every aspect of people's lives, it can be extended to language teaching and…
Full Text Available Background: The term digital natives refer to those born since the 1980s and have been growing up surrounded by technology. On the other hand, digital immigrants are born before 1980s and learned how to use technology later in life. Objectives: Goal of the paper is to explore attitudes of digital native students on the course of Business Informatics at higher educational institutions (HEIs, and to compare them with attitudes of digital immigrants. Methods/Approach: The survey was conducted in 2014 using the sample of first-year Business Informatics students from the Faculty of Economics and Business in Zagreb, Croatia. Results were compared with a research conducted in 1998. Results: In comparison to an earlier research, digital natives perceive their level of competency in the subject of Business Informatics before teaching practices much higher compared to digital immigrants. However, there is still an increase in digital native students’ level of competency in the subject before and after teaching practices. Conclusions: The research confirms a shift from digital immigrants to digital natives who show high level of interest for Business Informatics course topics and find its utility very high. However, constant improvement of delivering knowledge is needed in order to keep these high levels.
Full Text Available This study was aimed to develop and produce an assessment instrument of mathematical learning results based on multiple intelligence. The methods in this study used Borg & Gall-Research and Development approach (Research & Development. The subject of research was 289 students. The results of research: (1 Result of Aiken Analysis showed 58 valid items were between 0,714 to 0,952. (2 Result of the Exploratory on factor analysis indicated the instrument consist of three factors i.e. mathematical logical intelligence-spatial intelligence-and linguistic intelligence. KMO value was 0.661 df 0.780 sig. 0.000 with valid category. This research succeeded to developing the assessment instrument of mathematical learning results based on multiple intelligence of second grade in elementary school with characteristics of logical intelligence of mathematics, spatial intelligence, and linguistic intelligence.
Kumaran, Dharshan; Hassabis, Demis; McClelland, James L
We update complementary learning systems (CLS) theory, which holds that intelligent agents must possess two learning systems, instantiated in mammalians in neocortex and hippocampus. The first gradually acquires structured knowledge representations while the second quickly learns the specifics of individual experiences. We broaden the role of replay of hippocampal memories in the theory, noting that replay allows goal-dependent weighting of experience statistics. We also address recent challenges to the theory and extend it by showing that recurrent activation of hippocampal traces can support some forms of generalization and that neocortical learning can be rapid for information that is consistent with known structure. Finally, we note the relevance of the theory to the design of artificial intelligent agents, highlighting connections between neuroscience and machine learning. Copyright © 2016 Elsevier Ltd. All rights reserved.
van Schaik, Carel; Graber, Sereina; Schuppli, Caroline; Burkart, Judith
Classical ethology and behavioral ecology did not pay much attention to learning. However, studies of social learning in nature reviewed here reveal the near-ubiquity of reliance on social information for skill acquisition by developing birds and mammals. This conclusion strengthens the plausibility of the cultural intelligence hypothesis for the evolution of intelligence, which assumes that selection on social learning abilities automatically improves individual learning ability. Thus, intelligent species will generally be cultural species. Direct tests of the cultural intelligence hypothesis require good estimates of the amount and kind of social learning taking place in nature in a broad variety of species. These estimates are lacking so far. Here, we start the process of developing a functional classification of social learning, in the form of the social learning spectrum, which should help to predict the mechanisms of social learning involved. Once validated, the categories can be used to estimate the cognitive demands of social learning in the wild.
Full Text Available English is the most important second language in most non-English speaking countries, including Malaysia. A good English proficiency comes from good grasp of grammar. To conquer the problems of low English proficiency among Malaysians, it is important to identify the key motivators that could facilitate the process of grammar learning. In this digital age, technology can play a very important role and mobile technology could be one of it. Thus, this study aims at designing a mobile learning tool, namely the Intelligent Mobile Learning Tool for Grammar Learning (i-MoL to act as the “on-the-go” grammar learning support via mobile phones. i-MoL helps reinforce grammar learning through mobile phone with game-like applications, inquiry-based activities and flashcard-like information. The intelligent part of i-MoL lies in its ability to map the mobile-based grammar learning content to individual’s preferred learning styles based on Felder-Silverman Learning Style Model (FSLSM. The instructional system design through the ADDIE model was used in this study as a systematic approach in designing a novel and comprehensive mobile learning tool for grammar learning. In terms of implications, this study provides insights on how mobile technologies can be utilized to meet the mobility demand among language learners today.
Although governments worldwide have invested significantly in intelligent sensor network research and applications, few books cover intelligent sensor networks from a machine learning and signal processing perspective. Filling this void, Intelligent Sensor Networks: The Integration of Sensor Networks, Signal Processing and Machine Learning focuses on the close integration of sensing, networking, and smart signal processing via machine learning. Based on the world-class research of award-winning authors, the book provides a firm grounding in the fundamentals of intelligent sensor networks, incl
ARL-SR-0318 ● MAR 2015 US Army Research Laboratory Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated...Adaptive Intelligent Tutoring Systems for Self-Regulated Learning by Robert A Sottilare Human Research and Engineering Directorate, ARL...TITLE AND SUBTITLE Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated Learning 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c
Hjertø, Kjell B.
A field sample of 1100 employees in the army was investigated to study the relationship between the individuals’ self reported emotional intelligence and learning outcomes in work groups, with two dimensions of emotional conflict as mediators, emotional person conflict and emotional task conflict. Most importantly, emotional intelligence predicted positively learning outcomes and emotional task conflict, and predicted negatively emotional person conflict. Further, emotional task ...
Hajhashemi, Karim; Caltabiano, Nerina; Anderson, Neil; Tabibzadeh, Seyed Asadollah
This study investigates multiple intelligences in relation to online video experiences, age, gender, and mode of learning from a rural Australian university. The inter-relationships between learners' different intelligences and their motivations and learning experience with the supplementary online videos utilised in their subjects are…
Lu, Jingyang; Li, Lun; Chen, Genshe; Shen, Dan; Pham, Khanh; Blasch, Erik
In this paper, a Cognitive Radio Network (CRN) based on artificial intelligence is proposed to distribute the limited radio spectrum resources more efficiently. The CRN framework can analyze the time-sensitive signal data close to the signal source using fog computing with different types of machine learning techniques. Depending on the computational capabilities of the fog nodes, different features and machine learning techniques are chosen to optimize spectrum allocation. Also, the computing nodes send the periodic signal summary which is much smaller than the original signal to the cloud so that the overall system spectrum source allocation strategies are dynamically updated. Applying fog computing, the system is more adaptive to the local environment and robust to spectrum changes. As most of the signal data is processed at the fog level, it further strengthens the system security by reducing the communication burden of the communications network.
Bouchet, Francois; Azevedo, Roger; Kinnebrew, John S.; Biswas, Gautam
Identification of student learning behaviors, especially those that characterize or distinguish students, can yield important insights for the design of adaptation and feedback mechanisms in Intelligent Tutoring Systems (ITS). In this paper, we analyze trace data to identify distinguishing patterns of behavior in a study of 51 college students…
Povlsen, Lene; Ringsberg, Karin C
with diabetes, in a more doubtful and negative way. The findings further indicate that the establishment of a trustful relationship between the immigrant families and the health-care professionals should be given high priority. The study concludes that parents with an immigrant background are likely to require...... special pedagogic, psychological and social support to learn to adapt and come to terms with the diagnosis of a chronic disease in a child....
Full Text Available The proposed goal oriented knowledge acquisition and assessment are based on the flexible educational model and allows to implement an adaptive control of the enhanced learning process according to the requirements of student's knowledge level, his state of cognition and subject learning history. The enhanced learner knowledge model specifies how the cognition state of the user will be achieved step by step. The use case actions definition is a starting point of the specification, which depends on different levels of learning scenarios and user cognition sub goals. The use case actions specification is used as a basis to set the requirements for service software specification and attributes of learning objects respectively. The paper presents the enhanced architecture of the student self-evaluation and on-line assessment system TestTool. The system is explored as an assessment engine capable of supporting and improving the individualized intelligent goal oriented self-instructional and simulation based mode of learning, grounded on the GRID distributed service architecture.
Full Text Available Knowledge graph (KG as a popular semantic network has been widely used. It provides an effective way to describe semantic entities and their relationships by extending ontology in the entity level. This article focuses on the application of KG in the traditional geological field and proposes a novel method to construct KG. On the basis of natural language processing (NLP and data mining (DM algorithms, we analyze those key technologies for designing a KG towards geological data, including geological knowledge extraction and semantic association. Through this typical geological ontology extracting on a large number of geological documents and open linked data, the semantic interconnection is achieved, KG framework for geological data is designed, application system of KG towards geological data is constructed, and dynamic updating of the geological information is completed accordingly. Specifically, unsupervised intelligent learning method using linked open data is incorporated into the geological document preprocessing, which generates a geological domain vocabulary ultimately. Furthermore, some application cases in the KG system are provided to show the effectiveness and efficiency of our proposed intelligent learning approach for KG.
mind, (ii) forms of mental self-government, and (iii) stylistic preferences. Importantly, Sternberg does not think that cognitive style...summarizes a study examining suitable cognitive and learning styles for intelligent tutoring technologies to improve the Canadian Forces (CF) distance...are the appropriate tool to address CF learning needs, as e-learning systems: • Cater to all individuals in the CF regardless of their cognitive or
JinHyo Joseph Yun
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.
Perez, Carlos E
Deep Learning Artificial Intelligence involves the interplay of Computer Science, Physics, Biology, Linguistics and Psychology. In addition to that, it is technology that can be extremely disruptive. The ramifications to society and even our own humanity will be profound. There are few subjects that are as captivating and as consequential as this. Surprisingly, there is very little that is written about this new technology in a more comprehensive and cohesive way. This book is an opinionated take on the developments of Deep Learning AI. One question many have will be "how to apply Deep Learning AI in a business context?" Technology that is disruptive does not automatically imply that its application to valuable use cases will be apparent. For years, many people could not figure out how to monetize the World Wide Web. We are in a similar situation with Deep Learning AI. The developments may be mind-boggling but its monetization is far from being obvious. This book presents a framework to address this shortcomi...
Hearne, D; Stone, S
The field of learning disabilities, like education in the main, is undergoing calls for reform and restructuring, an upheaval brought on in great part by the forces of opposing paradigms--reductionism and constructivism. In reexamining our past, we must begin to address the failures of traditional deficit models and their abysmally low "cure" rate. Several new theories have arisen that challenge traditional practices in both general and special education classrooms. Particularly influential has been the work of Howard Gardner, whose theory of multiple intelligences calls for a restructuring of our schools to accommodate modes of learning and inquiry with something other than deficit approaches. At least some current research in the field of learning disabilities has begun to focus on creativity and nontraditional strengths and talents that have not been well understood or highly valued by the schools. In this article, we briefly summarize the findings in our search for the talents of students labeled learning disabled, evidence of their abilities, implications of these for the schools, and a beginning set of practical recommendations.
Hoerig, Dianne C; David, Andrew S; D'Amato, Rik Carl
Although both intelligence tests and memory tests are commonly used in neuropsychological examinations, the relationship between memory and intelligence has not been fully explored, particularly for children having learning disabilities. Memory, or the ability to retain information, was evaluated using the Test of Memory and Learning, a recently released test that gives a comprehensive measure of global memory functioning. This, and the Wechsler Intelligence Scale for Children-Third Edition, used to assess intelligence, were given to 80 students with learning disabilities. The correlation between a global measure of memory and a global measure f intelligence was significant (r = .59), indicating that memory should be viewed as an important component when evaluating children with learning disabilities.
Liao, Xiaoqun; Cao, Ming; Hall, Ernest L.
Intelligent industrial and mobile robots may be considered proven technology in structured environments. Teach programming and supervised learning methods permit solutions to a variety of applications. However, we believe that to extend the operation of these machines to more unstructured environments requires a new learning method. Both unsupervised learning and reinforcement learning are potential candidates for these new tasks. The adaptive critic method has been shown to provide useful approximations or even optimal control policies to non-linear systems. The purpose of this paper is to explore the use of new learning methods that goes beyond the adaptive critic method for unstructured environments. The adaptive critic is a form of reinforcement learning. A critic element provides only high level grading corrections to a cognition module that controls the action module. In the proposed system the critic's grades are modeled and forecasted, so that an anticipated set of sub-grades are available to the cognition model. The forecasting grades are interpolated and are available on the time scale needed by the action model. The success of the system is highly dependent on the accuracy of the forecasted grades and adaptability of the action module. Examples from the guidance of a mobile robot are provided to illustrate the method for simple line following and for the more complex navigation and control in an unstructured environment. The theory presented that is beyond the adaptive critic may be called creative theory. Creative theory is a form of learning that models the highest level of human learning - imagination. The application of the creative theory appears to not only be to mobile robots but also to many other forms of human endeavor such as educational learning and business forecasting. Reinforcement learning such as the adaptive critic may be applied to known problems to aid in the discovery of their solutions. The significance of creative theory is that it
Afshar, Hassan Soodmand; Tofighi, Somayyeh; Hamazavi, Raouf
The idea that language learning is facilitated or inhibited by a multitude of factors has prompted scholars in the field to investigate variables considered to be crucial in the process of second or foreign language learning. This study investigated relationships between emotional intelligence, learning style, language learning strategy use, and…
Bray, S. E.
A vision was presented in a previous paper of how a common set of services within a framework could be used to provide all the information processing needs of Warfighters. Central to that vision was the concept of a "Virtual Knowledge Base". The paper presents an implementation of these ideas in the intelligence domain. Several innovative technologies were employed in the solution, which are presented and their benefits explained. The project was successful, validating many of the design principles for such a system which had been proposed in earlier work. Many of these principles are discussed in detail, explaining lessons learned. The results showed that it is possible to make vast improvements in the ability to exploit available data, making it discoverable and queryable wherever it is from anywhere within a participating network; and to exploit machine reasoning to make faster and better inferences from available data, enabling human analysts to spend more of their time doing more difficult analytical tasks rather than searching for relevant data. It was also demonstrated that a small number of generic Information Processing services can be combined and configured in a variety of ways (without changing any software code) to create "fact-processing" workflows, in this case to create different intelligence analysis capabilities. It is yet to be demonstrated that the same generic services can be reused to create analytical/situational awareness capabilities for logistics, operations, planning or other military functions but this is considered likely.
Niewoehner, Kevin R.; Carter, John (Technical Monitor)
The research accomplishments for the cooperative agreement 'Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)' include the following: (1) previous IFC program data collection and analysis; (2) IFC program support site (configured IFC systems support network, configured Tornado/VxWorks OS development system, made Configuration and Documentation Management Systems Internet accessible); (3) Airborne Research Test Systems (ARTS) II Hardware (developed hardware requirements specification, developing environmental testing requirements, hardware design, and hardware design development); (4) ARTS II software development laboratory unit (procurement of lab style hardware, configured lab style hardware, and designed interface module equivalent to ARTS II faceplate); (5) program support documentation (developed software development plan, configuration management plan, and software verification and validation plan); (6) LWR algorithm analysis (performed timing and profiling on algorithm); (7) pre-trained neural network analysis; (8) Dynamic Cell Structures (DCS) Neural Network Analysis (performing timing and profiling on algorithm); and (9) conducted technical interchange and quarterly meetings to define IFC research goals.
Nur Ihsan Halil
Full Text Available This article is inspired by Howard Gardner's concept of linguistic intelligence and also from some authors' previous writings. All of them became the authors' reference in developing ideas on constructing a literary learning model based on linguistic intelligence. The writing of this article is not done by collecting data empirically, but by developing and constructing an existing concept, namely the concept of linguistic intelligence, which is disseminated into a literature-based learning of verbal-linguistic intelligence. The purpose of this paper is to answer the question of how to apply the literary learning model based on the verbal-linguistic intelligence. Then, regarding Gardner's concept, the author formulated a literary learning model based on the verbal-linguistic intelligence through a story-telling learning model with five steps namely arguing, discussing, interpreting, speaking, and writing about literary works. In short, the writer draw a conclusion that learning-based models of verbal-linguistic intelligence can be designed with attention into five components namely (1 definition, (2 characteristics, (3 teaching strategy, (4 final learning outcomes, and (5 figures.
Full Text Available This paper explores the reasoning and use of information and communications technology (ICT in lifelong learning by immigrant women. Data were collected from semi-structured and unstructured interviews. The study was carried out primarily in a school environment, which also makes it possible to draw conclusions about the connection between learning in and outside school environments. Most participants experienced major differences in the use of and access to ICT after moving to their new country. Most women use and access ICT, even if not of their own volition. Providing a summary of some of the benefits and barriers that emerged, our study has shown that it is important to distinguish the way someone reasons about ICT and their actual use of it. No account was taken of cultural differences between the participants’ countries of origin. This study made it possible for the immigrant women to voice their experiences, knowledge, and feelings about their situations in school and in everyday life.
..., citizenship/immigration status, passport information, addresses, phone numbers, etc.); (2) Records of... magnetic disc, tape, digital media, and CD-ROM. RETRIEVABILITY: Records may be retrieved by personal...
Manoj ROY. V.
Full Text Available In recent times Information and Communication Technology (ICT has been able to make inroads into the ways information is disseminated among those involved in direct farming and farming related enterprises. This paper arose from a two-year study of the KissanKerala, the e-learning project underway in Kerala, a small state in India. It is more conspicuous when we learn that the KissanKerala project is able to disseminate agricultural information also among digital immigrants. Since 2003, the KissanKerala has been providing advisory services to the farming community in Kerala using a combination of technologies. Salient features of the project are discussed. Noteworthy are its interactive web portal and the online agri-video channel that uses the video sharing platform of YouTube. In this paper, we look at the e-learning strategies adopted; virtual learning environments created and also discuss participative tools used for communication. We have also made an impact-study of the project with a large number of beneficiaries. We learn that the Kissan Kerala is one of the most successful learning projects undertaken in distance mode in India.
Munsawaengsub, Chokchai; Yimklib, Somkid; Nanthamongkolchai, Sutham; Apinanthavech, Suporn
To study the effect of promoting self-esteem by participatory learning program on emotional intelligence among early adolescents. The quasi-experimental study was conducted in grade 9 students from two schools in Bangbuathong district, Nonthaburi province. Each experimental and comparative group consisted of 34 students with the lowest score of emotional intelligence. The instruments were questionnaires, Program to Develop Emotional Intelligence and Handbook of Emotional Intelligence Development. The experimental group attended 8 participatory learning activities in 4 weeks to Develop Emotional Intelligence while the comparative group received the handbook for self study. Assessment the effectiveness of program was done by pre-test and post-test immediately and 4 weeks apart concerning the emotional intelligence. Implementation and evaluation was done during May 24-August 12, 2005. Data were analyzed by frequency, percentage, mean, standard deviation, Chi-square, independent sample t-test and paired sample t-test. Before program implementation, both groups had no statistical difference in mean score of emotional intelligence. After intervention, the experimental group had higher mean score of emotional intelligence both immediately and 4 weeks later with statistical significant (p = 0.001 and self-esteem by participatory learning process could enhance the emotional intelligence in early-adolescent. This program could be modified and implemented for early adolescent in the community.
Baklashova, Tatiana A.; Galishnikova, Elena M.; Khafizova, Liliya A.
The relevance of the topic is due to the enhancing role of emotional intelligence in second language learning. The article aims to substantiate that emotional intelligence (EI) strengthens training quality of future professionals, gives it an emotional color, and thereby increases a variety of intellectual skills. The leading methodical approaches…
Muuro, Maina Elizaphan; Oboko, Robert; Wagacha, Waiganjo Peter
In this paper we explore the impact of an intelligent grouping algorithm based on learners' collaborative competency when compared with (a) instructor based Grade Point Average (GPA) method level and (b) random method, on group outcomes and group collaboration problems in an online collaborative learning environment. An intelligent grouping…
Hali, Nur Ihsan
This article is inspired by Howard Gardner's concept of linguistic intelligence and also from some authors' previous writings. All of them became the authors' reference in developing ideas on constructing a literary learning model based on linguistic intelligence. The writing of this article is not done by collecting data empirically, but by…
The purpose of this study was to determine the nature of the relationship between the emotional intelligence of the school principal and the school as a learning organization. These constructs originated in the business world and have recently been examined within the context of education. Studies on principal emotional intelligence have shown the…
Chen, Hong-Ren; Chiang, Chih-Hao; Lin, Wen-Shan
With the rapid progress in information technology, interactive whiteboards have become IT-integrated in teaching activities. The theory of multiple intelligences argues that every person possesses multiple intelligences, emphasizing learners' cognitive richness and the possible role of these differences in enhanced learning. This study is the…
Kanagarajan, Sujith; Ramakrishnan, Sivakumar
Ubiquitous Learning Environment (ULE) has been becoming a mobile and sensor based technology equipped environment that suits the modern world education discipline requirements for the past few years. Ambient Intelligence (AmI) makes much smarter the ULE by the support of optimization and intelligent techniques. Various efforts have been so far…
Wallace, Scott A.; McCartney, Robert; Russell, Ingrid
Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…
Podeschi, R. J.
This paper reports on the use of QlikView business intelligence software for use in a Business Intelligence (BI) course within an undergraduate information systems program. The course provides students with concepts related to data warehousing, data mining, visualizations, and software tools to provide business intelligence solutions for decision…
Schrauf, Robert W; Weintraub, Sandra; Navarro, Ellen
Adaptations of the National Adult Reading Test (NART) for assessing premorbid intelligence in languages other than English requires (a) generating word-items that are rare and do not follow grapheme-to-phoneme mappings common in that language, and (b) subsequent validation against a cognitive battery normed on the population of interest. Such tests exist for Italy, France, Spain, and Argentina, all normed against national versions of the Wechsler Adult Intelligence Scale. Given the varieties of Spanish spoken in the United States, the adaptation of the Spanish Word Accentuation Test (WAT) requires re-validating the original word list, plus possible new items, against a cognitive battery that has been normed on Spanish-speakers from many countries. This study reports the generation of 55 additional words and revalidation in a sample of 80 older, Spanish-dominant immigrants. The Batería Woodcock-Muñoz Revisada (BWM-R), normed on Spanish speakers from six countries and five U.S. states, was used to establish criterion validity. The original WAT word list accounted for 77% of the variance in the BWM-R and 58% of the variance in Ravens Colored Progressive Matrices, suggesting that the unmodified list possesses adequate predictive validity as an indicator of intelligence. Regression equations are provided for estimating BWM-R and Ravens scores from WAT scores.
National Aeronautics and Space Administration — Building an autonomous architecture that uses directed self-learning neuro-fuzzy networks with the aim of developing an intelligent autonomous collision avoidance...
Full Text Available Tujuan penelitian ini adalah (1 Untuk mengetahui hubungan antara tingkat kecerdasan dengan prestasi belajar matematika (2 Untuk mengetahui hubungan antara motivasi berprestasi dengan prestasi belajar matematika (3 Untuk mengetahui hubungan antara kebiasaan belajar dengan prestasi belajar matematika (4 Untuk mengetahui hubungan antara tingkat kecerdasan, motivasi berprestasi, dan kebiasaan belajar matematika dengan prestasi belajar matematika siswa semester 1 kelas XI IPA SMAN 1 Bojong. Jumlah sampel dalam penelitian ini sebanyak 40 orang siswa. Penelitian ini merupakan penelitian deskriptif korelatif sehingga data dianalisa untuk mendeskripsikan hubungan antara tingkat kecerdasan, motivasi berprestasi, dan kebiasaan belajar matematika dengan prestasi belajar matematika siswa. Instrumen pengambilan data menggunakan dokumentasi dan angket, dan dianalisa menggunakan regresi dan korelasi linier sederhana, serta regresi dan korelasi linier berganda. Hasil penelitian menunjukkan bahwa terdapat hubungan yang signifikan antara : (1 tingkat kecerdasan dengan prestasi belajar matematika siswa, (2 motivasi berprestasi dengan prestasi belajar matematika siswa, (3 kebiasaan belajar dengan prestasi belajar matematika siswa (4 tingkat kecerdasan, motivasi berprestasi dan kebiasaan belajar matematika dengan prestasi belajar matematika siswa. The purpose of this study is (1 To determine the relationship between the level of intelligence and academic achievement of mathematics (2 To determine the relationship between achievement motivation and learning achievement in mathematics (3 To determine the relationship between study habits and academic achievement of mathematics (4 To determine the relationship between level of intelligence, achievement motivation and study habits mathematics learning achievement of student mathematics 1st semester of grade XI IPA SMAN 1 Bojong. The number of samples in this study were 40 students.This research was descriptive
de Castro-Santos, Amable; Fajardo, Waldo; Molina-Solana, Miguel
Our students taking the Artificial Intelligence and Knowledge Engineering courses often encounter a large number of problems to solve which are not directly related to the subject to be learned. To solve this problem, we have developed a game based e-learning system. The elected game, that has been implemented as an e-learning system, allows to…
Jovanovic, Jelena; Gasevic, Dragan; Torniai, Carlo; Bateman, Scott; Hatala, Marek
Today's technology-enhanced learning practices cater to students and teachers who use many different learning tools and environments and are used to a paradigm of interaction derived from open, ubiquitous, and socially oriented services. In this context, a crucial issue for education systems in general, and for Intelligent Learning Environments…
Huang, Chenn-Jung; Chen, Chun-Hua; Luo, Yun-Cheng; Chen, Hong-Xin; Chuang, Yi-Ta
Recently, a lot of open source e-learning platforms have been offered for free in the Internet. We thus incorporate the intelligent diagnosis and assessment tool into an open software e-learning platform developed for programming language courses, wherein the proposed learning diagnosis assessment tools based on text mining and machine learning…
Cavaleri, Steven A.; Fearon, David S.
Project management provides a natural home for organizational learning, freeing it from mechanical processes. Organizational learning plays a critical role in intelligent project management, which combines manageability, performance outcomes of knowledge management, and innovation. Learning should be integrated into an organization's core…
Kliegel, Matthias; Altgassen, Mareike
The present study investigated fluid and crystallized intelligence as well as strategic task approaches as potential sources of age-related differences in adult learning performance. Therefore, 45 young and 45 old adults were asked to learn pictured objects. Overall, young participants outperformed old participants in this learning test. However,…
Brigham, Susan M.; Baillie Abidi, Catherine; Zhang, Yuhui
Migration is a gendered phenomenon, embedded within patriarchal structures and social relations that extend beyond State borders. We draw on a transnational feminist framework to explore the gendered dimensions of young refugee and immigrant women's migration and learning experiences. Ten women were involved in a participatory photography research…
Benini, Silvia; Murray, Liam
More than 10 years have passed since the first introduction of the term "digital natives" in Prensky's (2001a, 2001b) two seminal articles. Prensky argues that students today, having grown up in the Digital Age, learn differently from their predecessors, or "digital immigrants". As such, the pedagogical tools and methods used…
Calero, M. Dolores; Mata, Sara; Carles, Rosario; Vives, Carmen; Lopez-Rubio, Sonia; Fernandez-Parra, Antonio; Navarro, Elena
The objective of this study was to test the usefulness of dynamic assessment for determining cognitive abilities such as classification, auditory and visual memory, pattern sequences, perspective taking, verbal planning, learning potential, and metacognition in immigrant preschool children with and without competence in the dominant language…
Lund, Darren; Lianne, Lee
This article documents a community-initiated service-learning project within a teacher education program. A social justice model guided the initiative to raise critical awareness on power and privilege while countering deficit-model thinking. Partnering with community agencies serving immigrant children and youth, the faculty researcher worked…
Colegrove, Kiyomi Sánchez-Suzuki; Adair, Jennifer Keys
This article documents what happened in a first grade classroom when young Latina/o children of immigrants had consistent classroom-based opportunities to use their agency in their learning. Applying theoretical constructs from development economics to data from the Agency and Young Children ethnographic project, we explore three forms of agency…
Eichler, Matthew A.; Mizzi, Robert C.
Sexual-minority male immigrants re-locating from the Middle East to the United States and Canada have particular experiences upon entry and integration into their new societies. The needs of learning and identity are highlighted through a multiple case approach involving three men. Interviews were conducted with the three participants, which were…
Yusri, Yusri; Emzir, Emzir
The objective of this study is to know the effects of learning models (problem solving and project based learning) and linguistic intelligence on the students of persuasive writing skill of the fourth semester students of English Department, State Polytechnic of Sriwijaya Palembang, in the academic year of 2016-2017. The writer used linguistic intelligence test and persuasive writing test to collect the data. The data was analyzed statistically by using two-factor ANOVA a...
Xu, Bin; Sun, Fuchun
This paper addresses the dynamic surface control of uncertain nonlinear systems on the basis of composite intelligent learning and disturbance observer in presence of unknown system nonlinearity and time-varying disturbance. The serial-parallel estimation model with intelligent approximation and disturbance estimation is built to obtain the prediction error and in this way the composite law for weights updating is constructed. The nonlinear disturbance observer is developed using intelligent approximation information while the disturbance estimation is guaranteed to converge to a bounded compact set. The highlight is that different from previous work directly toward asymptotic stability, the transparency of the intelligent approximation and disturbance estimation is included in the control scheme. The uniformly ultimate boundedness stability is analyzed via Lyapunov method. Through simulation verification, the composite intelligent learning with disturbance observer can efficiently estimate the effect caused by system nonlinearity and disturbance while the proposed approach obtains better performance with higher accuracy.
The three-phase process "-Instrument for Minority Immigrant Science Learning Environment," an 8-scale, 32-item see Appendix I- (I_MISLE) instrument when completed by teachers provides an accurate description of existing conditions in classrooms in which immigrant and refugee students are situated. Through the completion of the instrument…
Matthew A. Eichler
Full Text Available Sexual-minority male immigrants re-locating from the Middle East to the United States and Canada have particular experiences upon entry and integration into their new societies. The needs of learning and identity are highlighted through a multiple case approach involving three men. Interviews were conducted with the three participants, which were analyzed by the authors using qualitative case analysis. The data highlights the unmet expectations for life as a new immigrant, as well as the complexities of becoming involved in sexual-minority settings. Their learning experiences may be explained using a theoretical framework of transformative learning. These findings suggest that sexual-minority immigrants have complex needs, such as identifying with appropriate communities and deconstructing false representations of “gay rights” and citizenship in popular culture. Educational and social programs could address these needs when considering what might be important for immigrant adult learners.
Canadian Council on Learning, 2008
Nearly one out of five Canadian residents was born outside of Canada and approximately two-thirds of Canada's population growth results from net international migration. Only Australia, where immigrants represent 24% of the population, has a greater percentage of immigrants than Canada (18%). Immigration is a major factor in Canada's economic…
Widayanto, Arif; Pratiwi, Hasih; Mardiyana
The purpose of this study was to examine the presence or absence of different effects of multiple treatments (used learning models and logical-mathematical intelligence) on the dependent variable (affective domain of mathematics). This research was quasi experimental using 3x3 of factorial design. The population of this research was VIII grade students of junior high school in Karanganyar under the academic year 2017/2018. Data collected in this research was analyzed by two ways analysis of variance with unequal cells using 5% of significance level. The result of the research were as follows: (1) Teaching and learning with model TS lead to better achievement in affective domain than QSH, teaching and learning with model QSH lead to better achievement in affective domain than using DI; (2) Students with high mathematics logical intelligence have better achievement in affective domain than students with low mathematics logical intelligence have; (3) In teaching and learning mathematics using learning model TS, students with moderate mathematics logical intelligence have better achievement in affective domain than using DI; and (4) In teaching and learning mathematics using learning model TS, students with low mathematics logical intelligence have better achievement in affective domain than using QSH and DI.
Leasa, Marleny; Corebima, Aloysius D.; Ibrohim; Suwono, Hadi
Students have unique ways in managing the information in their learning process. VARK learning styles associated with memory are considered to have an effect on emotional intelligence. This quasi-experimental research was conducted to compare the emotional intelligence among the students having auditory, reading, and kinesthetic learning styles in…
Liang, Kun; Zhang, Yiying; He, Yeshen; Zhou, Yilin; Tan, Wei; Li, Xiaoxia
With the development of mobile platform, such as smart cellphone and pad, the E-Learning model has been rapidly developed. However, due to the low completion rate for E-Learning platform, it is very necessary to analyze the behavior characteristics of online learners to intelligently adjust online education strategy and enhance the quality of learning. In this paper, we analyzed the relation indicators of E-Learning to build the student profile and gave countermeasures. Adopting the similarit...
Yi Fei Wang; Stephen Petrina
the goal of this article is to explore how learning analytics can be used to predict and advise the design of an intelligent language tutor, chatbot Lucy. With its focus on using student-produced data to understand the design of Lucy to assist English language learning, this research can be a valuable component for language-learning designers to improve second language acquisition. In this article, we present students’ learning journey and data trails, the chatting log architecture and result...
Full Text Available Looking at learning procedure in general and language learning in particular, variations abound in learning processes and styles. Along this journey, some learners travel/move ahead smoothly and some others are faced with challenges of different sorts. Among the significant factors contributing to more effective and efficient language learning output, motivation, attitude, and personality traits play major roles. However, the role played by the intelligence seems to be critical in any language learning tasks and activities. Emotional Intelligence, which is believed to harmonize cognitive and emotional dispositions, seems to be indispensable to the interrelation between the learner’s Multiple Intelligence makeup and respective preferred learning strategies. This can be used to develop materials and teaching tasks to become more or less compatible with the learners’ varying preferences and abilities, thereby promoting their achievements. The findings of the study pertaining to the interrelation of students’ Multiple Intelligence profile and their preferred Language Learning Strategies can be used to plan and categorize language learning and teaching tasks and materials in order to modify them more in accordance with the choice of the students. The educators might use the findings to choose from among various teaching materials to satisfy the needs of their learners with different illiteracies through conducting need analysis prior to choosing any learning and teaching content materials.
Amaral, Luiz A.; Meurers, Detmar
This paper explores the motivation and prerequisites for successful integration of Intelligent Computer-Assisted Language Learning (ICALL) tools into current foreign language teaching and learning (FLTL) practice. We focus on two aspects, which we argue to be important for effective ICALL system development and use: (i) the relationship between…
Pratiwi, W. N.; Rochintaniawati, D.; Agustin, R. R.
This research was focused on investigating the effect of multiple intelligence -based learning as a learning approach towards students’ concept mastery and interest in learning matter. The one-group pre-test - post-test design was used in this research towards a sample which was according to the suitable situation of the research sample, n = 13 students of the 7th grade in a private school in Bandar Seri Begawan. The students’ concept mastery was measured using achievement test and given at the pre-test and post-test, meanwhile the students’ interest level was measured using a Likert Scale for interest. Based on the analysis of the data, the result shows that the normalized gain was .61, which was considered as a medium improvement. in other words, students’ concept mastery in matter increased after being taught using multiple intelligence-based learning. The Likert scale of interest shows that most students have a high interest in learning matter after being taught by multiple intelligence-based learning. Therefore, it is concluded that multiple intelligence – based learning helped in improving students’ concept mastery and gain students’ interest in learning matter.
Lytras, Miltiadis, Ed.; Naeve, Ambjorn, Ed.
In the context of Knowledge Society, the convergence of knowledge and learning management is a critical milestone. "Intelligent Learning Infrastructure for Knowledge Intensive Organizations: A Semantic Web Perspective" provides state-of-the art knowledge through a balanced theoretical and technological discussion. The semantic web perspective…
The objective of the present study is to determine whether there is a significant relationship between the students' readiness in online learning and their emotional intelligence levels. Correlational research method was used in the study. Online Learning Readiness Scale which was developed by Hung et al. (2010) has been used and Trait Emotional…
Pradhan, Rabindra Kumar; Jena, Lalatendu Kesari; Singh, Sanjay Kumar
Purpose: The purpose of this study is to examine the relationship between organisational learning and adaptive performance. Furthermore, the study investigates the moderating role of emotional intelligence in the perspective of organisational learning for addressing adaptive performance of executives employed in manufacturing organisations.…
Arends, Hugo; Heeren, B.J.; Keuning, H.W.; Jeuring, J.T.
Embedded systems engineers need to learn how I/O programming expressions for microcontrollers evaluate. We designed, implemented, and tested an intelligent tutoring system prototype for learning such evaluations. The Microcontroller Knowledge (MicK) tutor guides a student step-by-step towards a
Dong Yun Kim; Poong Hyun Seong; .
In this research, we propose a fuzzy gain scheduler (FGS) with an intelligent learning algorithm for a reactor control. In the proposed algorithm, the gradient descent method is used in order to generate the rule bases of a fuzzy algorithm by learning. These rule bases are obtained by minimizing an objective function, which is called a performance cost function. The objective of the FGS with an intelligent learning algorithm is to generate gains, which minimize the error of system. The proposed algorithm can reduce the time and effort required for obtaining the fuzzy rules through the intelligent learning function. It is applied to reactor control of nuclear power plant (NPP), and the results are compared with those of a conventional PI controller with fixed gains. As a result, it is shown that the proposed algorithm is superior to the conventional PI controller. (author)
This study examines the application of classical music backsound in mathematics learning. The method used is quasi experimental design nonequivalent pretest-posttest control group in elementary school students in Tasikmalaya city, Indonesia. The results showed that classical music contributed significantly to the mathematical intelligence of elementary school students. The mathematical intelligence shown is in the cognitive ability ranging from the level of knowledge to evaluation. High level mathematical intelligence is shown by students in reading and writing integers with words and numbers. The low level of mathematical intelligence exists in projecting the story into a mathematical problem. The implication of this research is the use of classical music backsound on learning mathematics should pay attention to the level of difficulty of mathematics material being studied.
Full Text Available The aim of this paper was to describe the relationship between Interpersonal Intelligence and the learners' vocabulary learning through teaching reading activity so as to see whether this type of intelligence contributes to better vocabulary learning and whether there is any significant relationship between the performance of participants with interpersonal intelligence and their vocabulary learning in reading activity or not. This quantitative study consisted of a vocabulary test, a reading passage, an English proficiency test and a Multiple Intelligences questionnaire followed the study. A pre- test and post -test were conducted to get the differences in the students‟ post- test vocabulary score and their pre- test vocabulary score served as their gain score in vocabulary knowledge through reading. The comparison between the students‟ scores showed that there was no significant difference in the final performance of two groups. Therefore, this study doesn‟t support the idea of relationship between interpersonal intelligence and vocabulary learning through reading, but as a positive point, the present study indicated that reading texts can greatly assist the learners in developing the level of their vocabulary knowledge. This study proved to be useful for Iranian EFL learners and also EFL teachers can adopt the technique in their classes to advance their students' language learning. A comparison of the results after the next course cycle will then allow us to assess the effects of enhancing vocabulary knowledge, which would not be possible without reading texts.
Full Text Available Gardner's Multiple Intelligences theory is presented as a cognitive perspective on intelligence which has profound implications for education in general. More specifically, it has led to the application of eight of these frames to language teaching and learning. In this chapter, we will argue in favour of the application of MIT to the EFL classroom, using as support some of the major insights for language teaching from brain science.
The Department of Defense (DoD) relies heavily on information systems to complete a myriad of tasks, from day-to-day personnel actions to mission critical imagery retrieval, intelligence analysis, and mission planning...
Singh, Satinder; Okun, Andy; Jackson, Andrew
An artificial-intelligence program called AlphaGo Zero has mastered the game of Go without any human data or guidance. A computer scientist and two members of the American Go Association discuss the implications. See Article p.354
Franco de los Ríos, Camilo; Hougaard, Jens Leth; Nielsen, Kurt
Intelligent decision support should allow integrating human knowledge with efficient algorithms for making interpretable and useful recommendations on real world decision problems. Attitudes and preferences articulate and come together under a decision process that should be explicitly modeled...
Wass, Christopher; Denman-Brice, Alexander; Rios, Chris; Light, Kenneth R; Kolata, Stefan; Smith, Andrew M; Matzel, Louis D
Contemporary descriptions of human intelligence hold that this trait influences a broad range of cognitive abilities, including learning, attention, and reasoning. Like humans, individual genetically heterogeneous mice express a "general" cognitive trait that influences performance across a diverse array of learning and attentional tasks, and it has been suggested that this trait is qualitatively and structurally analogous to general intelligence in humans. However, the hallmark of human intelligence is the ability to use various forms of "reasoning" to support solutions to novel problems. Here, we find that genetically heterogeneous mice are capable of solving problems that are nominally indicative of inductive and deductive forms of reasoning, and that individuals' capacity for reasoning covaries with more general learning abilities. Mice were characterized for their general learning ability as determined by their aggregate performance (derived from principal component analysis) across a battery of five diverse learning tasks. These animals were then assessed on prototypic tests indicative of deductive reasoning (inferring the meaning of a novel item by exclusion, i.e., "fast mapping") and inductive reasoning (execution of an efficient search strategy in a binary decision tree). The animals exhibited systematic abilities on each of these nominal reasoning tasks that were predicted by their aggregate performance on the battery of learning tasks. These results suggest that the coregulation of reasoning and general learning performance in genetically heterogeneous mice form a core cognitive trait that is analogous to human intelligence. (c) 2012 APA, all rights reserved.
Kumalasari, Lita; Yusuf Hilmi, A.; Priyandoko, Didik
The purpose of this study is to offer an alternative teaching approach or strategies which able to accommodate students’ different ability, intelligence and learning style. Also can gives a new idea for the teacher as a facilitator for exploring how to teach the student in creative ways and more student-center activities, for a lesson such as circulatory system. This study was carried out at one private school in Bandung involved eight students to see their responses toward the lesson that delivered by using Multiple Intelligence approach which is include Linguistic, Logical-Mathematical, Visual-Spatial, Musical, Bodily-Kinesthetic, Interpersonal, Intrapersonal, and Naturalistic. Students were test by using MI test based on Howard Gardner’s MI model to see their dominant intelligence. The result showed the percentage of top three ranks of intelligence are Bodily-Kinesthetic (73%), Visual-Spatial (68%), and Logical-Mathematical (61%). The learning process is given by using some different multimedia and activities to engaged their learning style and intelligence such as mini experiment, short clip, and questions. Student response is given by using self-assessment and the result is all students said the lesson gives them a knowledge and skills that useful for their life, they are clear with the explanation given, they didn’t find difficulties to understand the lesson and can complete the assignment given. At the end of the study, it is reveal that the students who are learned by Multiple Intelligence instructional approach have more enhance to the lesson given. It’s also found out that the students participated in the learning process which Multiple Intelligence approach was applied enjoyed the activities and have great fun.
Wahyudin; Riza, L. S.; Putro, B. L.
E-learning as a learning activity conducted online by the students with the usual tools is favoured by students. The use of computer media in learning provides benefits that are not owned by other learning media that is the ability of computers to interact individually with students. But the weakness of many learning media is to assume that all students have a uniform ability, when in reality this is not the case. The concept of Intelligent Tutorial System (ITS) combined with cyberblog application can overcome the weaknesses in neglecting diversity. An Intelligent Tutorial System-based Cyberblog application (ITS) is a web-based interactive application program that implements artificial intelligence which can be used as a learning and evaluation media in the learning process. The use of ITS-based Cyberblog in learning is one of the alternative learning media that is interesting and able to help students in measuring ability in understanding the material. This research will be associated with the improvement of logical thinking ability (logical thinking) of students, especially in algorithm subjects.
Full Text Available With the development of mobile platform, such as smart cellphone and pad, the E-Learning model has been rapidly developed. However, due to the low completion rate for E-Learning platform, it is very necessary to analyze the behavior characteristics of online learners to intelligently adjust online education strategy and enhance the quality of learning. In this paper, we analyzed the relation indicators of E-Learning to build the student profile and gave countermeasures. Adopting the similarity computation and Jaccard coefficient algorithm, we designed a system model to clean and dig into the educational data and also the students’ learning attitude and the duration of learning behavior to establish student profile. According to the E-Learning resources and learner behaviors, we also present the intelligent guide model to guide both E-Learning platform and learners to improve learning things. The study on student profile can help the E-Learning platform to meet and guide the students’ learning behavior deeply and also to provide personalized learning situation and promote the optimization of the E-Learning.
The concept of learning objects has been applied in the e-learning field to promote the accessibility, reusability, and interoperability of learning content. Learning Object Metadata (LOM) was developed to achieve these goals by describing learning objects in order to provide meaningful metadata. Unfortunately, the conventional LOM lacks the…
Weber, David Jay
Today’s public health crises, as exemplified by the Ebola outbreak, lead to dramatic calls to action that typically include improved electronic monitoring systems to better prepare for, and respond to, similar occurrences in the future. Even a preliminary public health informatics evaluation of the current Ebola crisis exposes the need for enhanced coordination and sharing of trustworthy public health intelligence. We call for a consumer-centric model of public health intelligence and the formation of a national center to guide public health intelligence gathering and synthesis. Sharing accurate and actionable information with government agencies, health care practitioners, policymakers, and, critically, the general public, will mark a shift from doing public health surveillance on people to doing public health surveillance for people. PMID:26180978
Full Text Available This article presents results of a research project in which we attempted to determine the relationship between efficient E-learning and teaching materials adapted based on students’ structure of intelligence. The project was conducted on approximately 500 students, 23 classes, nine elementary schools, with ten teachers of history, informatics and several licensed psychologists. E-teaching material was prepared for the subject of History for eight-grade students of elementary school. Students were tested for the structure of intelligence, and based on their most prominent component, they were divided into groups, using teaching materials adapted to their most prominent intelligence component. The results have shown that use of the adapted teaching materials achieved 6-12% better results than E-materials not adapted to students’ structure of intelligence.
Buzdar, Muhammad Ayub; Ali, Akhtar; Tariq, Riaz Ul Haq
Students' performance in online learning environments is associated with their readiness to adopt a digital learning approach. Traditional concept of readiness for online learning is connected with students' competencies of using technology for learning purposes. We in this research, however, investigated psychometric aspects of students'…
Barakova, E.I.; Hu, J.
The present day society requires specialists with multidisciplinary knowledge and skills. We discuss the possibilities to educate professionals that design intelligent products and systems as a result of a competency based education. In particular this paper features a teaching method that makes the
Basu, Anamitra; Mermillod, Martial
The term "EI (emotional intelligence)" was first used in 1990 by Salovey and Mayer. EI involves: (1) the ability to perceive accurately, appraise and express emotion; (2) the ability to access and/or generate feelings when they facilitate thought; (3) the ability to understand emotion and emotional knowledge; and (4) the ability to regulate…
Albrecht, Nancy Jean
The gap between a student's home culture and that of classroom science may create challenges for students and families, especially those from recent immigrant cultures, including refugees. As a result, science learning in schools may require a form of cultural border crossing between home cultures and the culture of classroom science. Given this, as educators, how do we make these borders more porous for better science learning experiences? Using the frameworks of funds of knowledge, culturally relevant pedagogy, and socio-constructivism, this study focuses on the perspectives of Somali-American elders and parents about school science. Designed as an in-depth interview study, five purposefully selected participants were interviewed over a period of two years. The guiding questions for the study included: 1) What are the perceptions of Somali elders about school science? and 2) How do Somali elders believe science teaching and learning can facilitate Somali students' engagement in science?. Analysis of the interview data revealed that Somali-American adults have complicated perceptions of school science that include both conflicts and acceptance with current pedagogy and content. For example, science education was highly valued by both individuals and the Somali community, both as a way for individuals to attain economic prosperity and respect, but also as a way to lift up the Somali diaspora, both here and in their native homeland. On the other hand, science was also viewed as an abstract discipline with little connection to students' and families' everyday home lives. Moreover, due to the intrinsic role that Islam plays in traditional and contemporary Somali culture, several areas of science education, including geology, evolution and sex education, were viewed as problematic and unresolvable. Various potential areas of funds of knowledge and culturally relevant pedagogy were discussed including nutrition, food preparation and storage, health education, and
Tajmir, Shahein H; Alkasab, Tarik K
Radiology practice will be altered by the coming of artificial intelligence, and the process of learning in radiology will be similarly affected. In the short term, radiologists will need to understand the first wave of artificially intelligent tools, how they can help them improve their practice, and be able to effectively supervise their use. Radiology training programs will need to develop curricula to help trainees acquire the knowledge to carry out this new supervisory duty of radiologists. In the longer term, artificially intelligent software assistants could have a transformative effect on the training of residents and fellows, and offer new opportunities to bring learning into the ongoing practice of attending radiologists. Copyright © 2018 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.
Heift, Trude; Schulze, Mathias
This book provides the first comprehensive overview of theoretical issues, historical developments and current trends in ICALL (Intelligent Computer-Assisted Language Learning). It assumes a basic familiarity with Second Language Acquisition (SLA) theory and teaching, CALL and linguistics. It is of interest to upper undergraduate and/or graduate…
Crowe, Dale; LaPierre, Martin; Kebritchi, Mansureh
With augmented intelligence/knowledge based system (KBS) it is now possible to develop distance learning applications to support both curriculum and administrative tasks. Instructional designers and information technology (IT) professionals are now moving from the programmable systems era that started in the 1950s to the cognitive computing era.…
Alrabah, Sulaiman; Wu, Shu-hua; Alotaibi, Abdullah M.
The study aimed to investigate the learning styles and multiple intelligences of English as foreign language (EFL) college-level students. "Convenience sampling" (Patton, 2015) was used to collect data from a population of 250 students enrolled in seven different academic departments at the College of Basic Education in Kuwait. The data…
Zheng, Zhi; Warren, Zachary; Weitlauf, Amy; Fu, Qiang; Zhao, Huan; Swanson, Amy; Sarkar, Nilanjan
Researchers are increasingly attempting to develop and apply innovative technological platforms for early detection and intervention of autism spectrum disorder (ASD). This pilot study designed and evaluated a novel technologically-mediated intelligent learning environment with relevance to early social orienting skills. The environment was…
Alahdadi, Shadi; Ghanizadeh, Afsaneh
A key objective of education is to prepare individuals to be fully-functioning learners. This entails developing the cognitive, metacognitive, motivational, cultural, and emotional competencies. The present study aimed to examine the interrelationships among adaptability, tolerance of ambiguity, cultural intelligence, learning approach, and…
McLaren, Bruce M.; DeLeeuw, Krista E.; Mayer, Richard E.
Should an intelligent software tutor be polite, in an effort to motivate and cajole students to learn, or should it use more direct language? If it should be polite, under what conditions? In a series of studies in different contexts (e.g., lab versus classroom) with a variety of students (e.g., low prior knowledge versus high prior knowledge),…
Sistani, Mahsa; Hashemian, Mahmood
This study, first, examined whether there was any relationship between Iranian L2 learners' vocabulary learning strategies (VLSs), on the one hand, and their multiple intelligences (MI) types, on the other hand. In so doing, it explored the extent to which MI would predict L2 learners' VLSs. To these ends, 40 L2 learners from Isfahan University of…
Liu, Hui-ju; Chen, Ting-Han
This study mainly investigates language anxiety and its relationship to the use of learning strategies and multiple intelligences among young learners in an EFL educational context. The participants were composed of 212 fifth- and sixth-graders from elementary schools in central Taiwan. Findings indicated that most participants generally…
Wu, Shu-hua; Alrabah, Sulaiman
The purpose of the present study was to relate the findings of a survey of learning styles and multiple intelligences that was distributed among two different cultural groups of Freshman-level EFL students in Taiwan and Kuwait in order to confirm its consistency for developing teaching techniques appropriate for each group's general profiles. Data…
Baleghizadeh, Sasan; Shayeghi, Rose
The purpose of the present study is to investigate the relationships between preferences of Multiple Intelligences and perceptual/social learning styles. Two self-report questionnaires were administered to a total of 207 male and female participants. Pearson correlation results revealed statistically significant positive relations between…
Han, Heeyoung; Johnson, Scott D.
The purpose of the study was to investigate the relationship between students' emotional intelligence, social bond, and their interactions in an online learning environment. The research setting in this study was a 100% online master's degree program within a university located in the Midwest of the United States. Eighty-four students participated…
Graesser, Arthur C.; Hu, Xiangen; Nye, Benjamin D.; VanLehn, Kurt; Kumar, Rohit; Heffernan, Cristina; Heffernan, Neil; Woolf, Beverly; Olney, Andrew M.; Rus, Vasile; Andrasik, Frank; Pavlik, Philip; Cai, Zhiqiang; Wetzel, Jon; Morgan, Brent; Hampton, Andrew J.; Lippert, Anne M.; Wang, Lijia; Cheng, Qinyu; Vinson, Joseph E.; Kelly, Craig N.; McGlown, Cadarrius; Majmudar, Charvi A.; Morshed, Bashir; Baer, Whitney
Background: The Office of Naval Research (ONR) organized a STEM Challenge initiative to explore how intelligent tutoring systems (ITSs) can be developed in a reasonable amount of time to help students learn STEM topics. This competitive initiative sponsored four teams that separately developed systems that covered topics in mathematics,…
Adams, Thomasenia Lott
Focuses on the National Council of Teachers of Mathematics 2000 process-oriented standards of problem solving, reasoning and proof, communication, connections, and representation as providing a framework for using the multiple intelligences that children bring to mathematics learning. Presents ideas for mathematics lessons and activities to…
This paper examines how Piaget, Werner, and Gardner differ regarding the roles of cognition, intelligence, and learning in the developmental process. Piaget believes in the predominance of genetic factors. Werner stresses the influence of biological factors, while Gardner proposes that the environment plays a greater influence in how intelligence…
The proliferation of smartphones has given rise to intelligent personal assistants (IPAs), software that helps users accomplish day-to-day tasks. However, little is known about IPAs in the context of second language (L2) learning. Therefore, the primary objectives of this case study were twofold: to assess the ability of Amazon's IPA, Alexa, to…
Aliakbari, Mohammad; Abol-Nejadian, Rezvan
Although a large body of research has been dedicated to examining emotional intelligence (EI) and learning styles in relation to different factors in academic setting, the relationship between these two variables still necessitates more exploration and deeper study, especially in the Iranian context. To this end, 60 English for Academic Purposes…
Swanson, H. Lee
An information processing approach to the assessment of learning disabled students' intellectual performance is presented. The model is based on the assumption that intelligent behavior is comprised of a variety of problem- solving strategies. An account of child problem solving is explained and illustrated with a "thinking aloud" protocol.…
Bahrami, Mohammad Amin; Kiani, Mohammad Mehdi; Montazeralfaraj, Raziye; Zadeh, Hossein Fallah; Zadeh, Morteza Mohammad
Objectives Organizational learning is defined as creating, absorbing, retaining, transferring, and application of knowledge within an organization. This article aims to examine the mediating role of organizational learning in the relationship of organizational intelligence and organizational agility. Methods This analytical and cross-sectional study was conducted in 2015 at four teaching hospitals of Yazd city, Iran. A total of 370 administrative and medical staff contributed to the study. We...
Chen, ZhiHang; Masrur, M. A; Murphey, Yi L
.... A machine learning algorithm, LOPPS, has been developed to learn about optimal power source combinations with respect to minimum power loss for all possible load requests and various system power states...
Full Text Available The Community must develop and integrate into regular use new tools that can assist analysts in filtering and correlating the vast quantities of information that threaten to overwhelm the analytic process…—Commission on the Intelligence Capabilities of the United States.Regarding Weapons of Mass Destruction (The WMD Report1Unlike the other social sciences and, particularly, the physical sciences, where scientists get to choose the questions they wish to answer and experiments are carefully designed to confirm or negate hypotheses, intelligence analysis requires analysts to deal with the demands of decision makers and estimate the intentions of foreign actors, criminals or business competitors in an environment filled with uncertainty and even deliberate deception.
Chakraborty, Udit Kr.; Konar, Debanjan; Roy, Samir; Choudhury, Sankhayan
Evaluating Learners' Response in an e-Learning environment has been the topic of current research in areas of Human Computer Interaction, e-Learning, Education Technology and even Natural Language Processing. The current paper presents a twofold strategy to evaluate single word response of a learner in an e-Learning environment. The response of…
Al Rekhawi , Hazem Awni; Abu Naser , Samy S
International audience; The paper describes the design of a web based intelligent tutoring system for teaching Android Applications Development to students to overcome the difficulties they face. The basic idea of this system is a systematic introduction into the concept of Android Application Development. The system presents the topic of Android Application Development and administers automatically generated problems for the students to solve. The system is automatically adapted at run time ...
Brown Wright, Gloria Aileen
Howard Gardner's Theory of Multiple Intelligences identifies linguistic, spatial and logical-mathematical intelligences as necessary for learning in the physical sciences. He has identified nine intelligences which all persons possess to varying degrees, and says that learning is most effective when learners receive information in formats that correspond to their intelligence strengths. This research investigated the importance of the multiple intelligences of students in first-year college chemistry to the learning of chemistry concepts. At three pre-selected intervals during the first-semester course each participant received a tutorial on a chemistry topic, each time in a format corresponding to a different one of the three intelligences, just before the concept was introduced by the class lecturer. At the end of the experiment all subjects had experienced each of the three topics once and each format once, after which they were administered a validated instrument to measure their relative strengths in these three intelligences. The difference between a pre- and post-tutorial quiz administered on each occasion was used as a measure of learning. Most subjects were found to have similar strengths in the three intelligences and to benefit from the tutorials regardless of format. Where a difference in the extent of benefit occurred the difference was related to the chemistry concept. Data which indicate that students' preferences support these findings are also included and recommendations for extending this research to other intelligences are made.
Mohammed Abdallh Otair
Full Text Available Attempting to deliver a monolithic mobile learning system is too inflexible in view of the heterogeneous mixture of hardware and services available and the desirability of facility blended approaches to learning delivery, and how to build learning materials to run on all platforms. This paper proposes a framework of mobile learning system using an intelligent method (IP-MLI . A fuzzy matching method is used to find suitable learning material design. It will provide a best matching for each specific platform type for each learner. The main contribution of the proposed method is to use software layer to insulate learning materials from device-specific features. Consequently, many versions of learning materials can be designed to work on many platform types.
Othman O KHALIFA
Full Text Available The main issue concerned in education system is whether the typical way of teaching martial such as whiteboard in normal classroom is capable of deliver must of the new course martial (curriculum with best result of learning. Mobile technology have a high potential for improved learning (T. Liu, 2003(J. Massy ,2002. Mobile devices can enhance learning and it could be through Mobile Learning (M-Learning which is an approach to electronic learning (E-Learning (A. Kukulska-Hulme, 2005. This paper is focusing on the main problem exists in the classroom which is how a student can copy all the material written on the white board without losing the concentration of the lecturer's speech. Also the paper is explores what factors and design requirements are needed for M-Learning environment and suggests how M-Learning application can be designed. The following section definition of the mobile network is given. In the section three, reviews the literature review and previous work for M-Learning applications. Section four designs and analysis of the M-Learning environment is described. The final section provide conclusion and future work
Wiguna, B. J. P. K.; Suwarma, I. R.; Liliawati, W.
Science and technology are rapidly developing needs to be balanced with the human resources that have the qualified ability. Not only cognitive ability, but also have the soft skills that support 21st century skills. Science, Technology, Engineering, and Mathematics (STEM) Education is a solution to improve the quality of learning and prepare students may be able to trained 21st century skills. This study aims to analyse the implementation of STEM-based science learning on Newton’s law of motion by identifying the personal intelligences profile junior high school students. The method used in this research is pre experiment with the design of the study one group pre-test post-test. Samples in this study were 26 junior high school students taken using Convenience Sampling. Students personal intelligences profile after learning STEM-based science uses two instruments, self-assessment and peer assessment. Intrapersonal intelligence profile based self-assessment and peer assessment are respectively 69.38; and 64.08. As for interpersonal intelligence for self-assessment instrument is 73 and the peer assessment is 60.23.
Kim, Dong Yun
In this research, we propose a fuzzy gain scheduler (FGS) with an intelligent learning algorithm for a reactor control. In the proposed algorithm, the gradient descent method is used in order to generate the rule bases of a fuzzy algorithm by learning. These rule bases are obtained by minimizing an objective function, which is called a performance cost function. The objective of the FGS with an intelligent learning algorithm is to generate adequate gains, which minimize the error of system. The proposed algorithm can reduce the time and efforts required for obtaining the fuzzy rules through the intelligent learning function. The evolutionary programming algorithm is modified and adopted as the method in order to find the optimal gains which are used as the initial gains of FGS with learning function. It is applied to reactor control of nuclear power plant (NPP), and the results are compared with those of a conventional PI controller with fixed gains. As a result, it is shown that the proposed algorithm is superior to the conventional PI controller
Gennari, Rosella; Mascio, Tania; Rodríguez, Sara; Prieta, Fernando; Ramos, Carlos; Silveira, Ricardo
This book presents the outcomes of the 7th International Conference in Methodologies and Intelligent Systems for Technology Enhanced Learning (MIS4TEL'17), hosted by the Polytechnic of Porto, Portugal from 21 to 23 June 2017. Expanding on the topics of the previous conferences, it provided an open forum for discussing intelligent systems for technology enhanced learning (TEL) and their roots in novel learning theories, empirical methodologies for their design or evaluation, stand-alone and web-based solutions, and makerspaces. It also fostered entrepreneurship and business startup ideas, bringing together researchers and developers from industry, education and the academic world to report on the latest scientific research, technical advances and methodologies.
Full Text Available Introduction: Nowadays the incorporation and validation of learning styles and multiple intelligences enable teachers to obtain positive results in academic performance. This new approach has allowed to appreciate personal differences in dental students and strengthen their underdeveloped aspects, improving teaching and learning skills. Objective: To compare learning styles and multiple intelligences in a sample of Mexican dental students in their first and tenth semester. Materials and Methods: A cross-sectional study using questionnaires on learning styles (Honey-Alonso and Gardner’s multiple intelligences was performed. The study was applied to 123 students in their first semester and 157 in their tenth semester at the School of Dentistry at Universidad Autónoma de Nuevo León, evaluating differences between age and sex. Results: Logical-Mathematical intelligence (p=0.044 and Kinesthetic-Corporal intelligence (p=0.042 showed significant differences between students of both semesters, with intrapersonal and interpersonal intelligences being more prevalent. Within learning styles, the prevalent were Reflexive and Theoretical, showing a significant difference between semesters (p=0.005. Conclusion: The most prevalent learning styles in both groups were Reflexive and Theoretical, with no difference between both sexes. The most prevalent types of multiple intelligences in both sexes and groups were interpersonal and intrapersonal.
Kommers, Petrus A.M.; Mizzoguchi, Riichiro
Learning is an active process clearly distinguished from simply being taught. Active involvement in learning helps learners build knowledge in their heads, which is one of the key issues advocated by constructivists. However, learners still need other kinds of help that instructivists might suggest.
Samigulina, Galina A.; Shayakhmetova, Assem S.
Research objective is the creation of intellectual innovative technology and information Smart-system of distance learning for visually impaired people. The organization of the available environment for receiving quality education for visually impaired people, their social adaptation in society are important and topical issues of modern education.The proposed Smart-system of distance learning for visually impaired people can significantly improve the efficiency and quality of education of this category of people. The scientific novelty of proposed Smart-system is using intelligent and statistical methods of processing multi-dimensional data, and taking into account psycho-physiological characteristics of perception and awareness learning information by visually impaired people.
Saw, Anne; Kim, Jin; Lim, Joyce; Powell, Catherine; Tong, Elisa K.
Engagement in modifiable risk behaviors, such as tobacco use, substantially contributes to early mortality rates in individuals with serious mental illness (SMI). There is an alarmingly high prevalence of tobacco use among subgroups of Asian Americans, such as immigrants and individuals with SMI, yet there are no empirically supported effective smoking cessation interventions that have been tailored to meet the unique cultural, cognitive, and psychological needs of Asian immigrants with SMI. In this article, we share the experiences of clinicians in the delivery of smoking cessation counseling to Asian American immigrants with SMI, in the context of an Asian-focused integrated primary care and behavioral health setting. Through a qualitative analysis of clinician perspectives organized with the RE-AIM framework, we outline challenges, lessons learned, and promising directions for delivering smoking cessation counseling to Asian American immigrant clients with SMI. PMID:23667056
Saw, Anne; Kim, Jin; Lim, Joyce; Powell, Catherine; Tong, Elisa K
Engagement in modifiable risk behaviors, such as tobacco use, substantially contributes to early mortality rates in individuals with serious mental illness (SMI). There is an alarmingly high prevalence of tobacco use among subgroups of Asian Americans, such as immigrants and individuals with SMI, yet there are no empirically supported effective smoking cessation interventions that have been tailored to meet the unique cultural, cognitive, and psychological needs of Asian immigrants with SMI. In this article, we share the experiences of clinicians in the delivery of smoking cessation counseling to Asian American immigrants with SMI, in the context of an Asian-focused integrated primary care and behavioral health setting. Through a qualitative analysis of clinician perspectives organized with the RE-AIM framework, we outline challenges, lessons learned, and promising directions for delivering smoking cessation counseling to Asian American immigrant clients with SMI.
Abdul Kadir Ritonga
Full Text Available STAD cooperative learning method which is considered effective in achieving the goal of learning the English language, especially for students majoring in Tourism Academy who are required to master English for Specific Purposes (ESP in accordance with their needs. This study uses factorial design 2x3x3 version of the non-equivalent control group design with ANOVA 3 Ways. The subjects were students MDK III / 5 A and B courses MDK III.5 Rooms Division department Hospitality Academy Year 2015/2016. The samples are saturated samples. Data were collected through a pretest, posttest, and instrument of Language Aptitude and Intelligence parametric statistics analyzed by parametric statistics with significance level of 0.05%. The results showed that: (1 there are differences between method STAD cooperative learning and expository on Hospitality English achievement, (2 there are differences between the students who have high language aptitude and low language aptitude on English achievement, (3 there are differences between students who have high language aptitude and medium on Hospitality English achievement, (4 there are differences between students who have the medium language aptitude and low language aptitude on Hospitality English achievement, (5 there are differences between students who have high intelligence and low intelligence\\ on Hospitality English achievement, (6 there are no differences between who have high intelligence and medium intelligence on Hospitality English achievement, (7 there are differences between students who have the medium intelligence and low intelligence on Hospitality English achievement, (8 there is no interaction between the learning method and language aptitude on Hospitality English achievement, (9 there is an interaction between the learning method and the intelligence on Hospitality English achievement, (10 there is no interaction between intelligence and language aptitude on Hospitality English achievement. (11
Dehkordi, Behzad Mirzaeian; Parsapoor, Amir; Moallem, Mehdi; Lucas, Caro
In this paper, a brain emotional learning based intelligent controller (BELBIC) is developed to control the switched reluctance motor (SRM) speed. Like other intelligent controllers, BELBIC is model free and is suitable to control nonlinear systems. Motor parameter changes, operating point changes, measurement noise, open circuit fault in one phase and asymmetric phases in SRM are also simulated to show the robustness and superior performance of BELBIC. To compare the BELBIC performance with other intelligent controllers, Fuzzy Logic Controller (FLC) is developed. System responses with BELBIC and FLC are compared. Furthermore, by eliminating the position sensor, a method is introduced to estimate the rotor position. This method is based on Adaptive Neuro Fuzzy Inference System (ANFIS). The estimator inputs are four phase flux linkages. Suggested rotor position estimator is simulated in different conditions. Simulation results confirm the accurate rotor position estimation in different loads and speeds.
Dehkordi, Behzad Mirzaeian, E-mail: email@example.com [Department of Electrical Engineering, Faculty of Engineering, University of Isfahan, Hezar-Jerib St., Postal code 8174673441, Isfahan (Iran, Islamic Republic of); Parsapoor, Amir, E-mail: firstname.lastname@example.org [Department of Electrical Engineering, Faculty of Engineering, University of Isfahan, Hezar-Jerib St., Postal code 8174673441, Isfahan (Iran, Islamic Republic of); Moallem, Mehdi, E-mail: email@example.com [Department of Electrical Engineering, Isfahan University of Technology, Isfahan (Iran, Islamic Republic of); Lucas, Caro, E-mail: firstname.lastname@example.org [Centre of Excellence for Control and Intelligent Processing, Electrical and Computer Engineering Faculty, College of Engineering, University of Tehran, Tehran (Iran, Islamic Republic of)
In this paper, a brain emotional learning based intelligent controller (BELBIC) is developed to control the switched reluctance motor (SRM) speed. Like other intelligent controllers, BELBIC is model free and is suitable to control nonlinear systems. Motor parameter changes, operating point changes, measurement noise, open circuit fault in one phase and asymmetric phases in SRM are also simulated to show the robustness and superior performance of BELBIC. To compare the BELBIC performance with other intelligent controllers, Fuzzy Logic Controller (FLC) is developed. System responses with BELBIC and FLC are compared. Furthermore, by eliminating the position sensor, a method is introduced to estimate the rotor position. This method is based on Adaptive Neuro Fuzzy Inference System (ANFIS). The estimator inputs are four phase flux linkages. Suggested rotor position estimator is simulated in different conditions. Simulation results confirm the accurate rotor position estimation in different loads and speeds.
Moafian, Fatemeh; Ebrahimi, Mohammad Reza
The current study investigated the association between multiple intelligences and language learning efficacy expectations among TEFL (Teaching English as a Foreign Language) university students. To fulfill the aim of the study, 108 junior and senior TEFL students were asked to complete the "Multiple Intelligence Developmental Assessment…
Ozgen, Kemal; Tataroglu, Berna; Alkan, Huseyin
The present study aims to identify pre-service mathematics teachers' multiple intelligence domains and learning style profiles, and to establish relationships between them. Employing the survey model, the study was conducted with the participation of 243 pre-service mathematics teachers. The study used the "multiple intelligence domains…
Ritchie, Stuart J.; Bates, Timothy C.; Plomin, Robert
Evidence from twin studies points to substantial environmental influences on intelligence, but the specifics of this influence are unclear. This study examined one developmental process that potentially causes intelligence differences: learning to read. In 1,890 twin pairs tested at 7, 9, 10, 12, and 16 years, a cross-lagged…
Full Text Available Deep learning has become the most popular research subject in the fields of artificial intelligence (AI and machine learning. In October 2013, MIT Technology Review commented that deep learning was a breakthrough technology. Deep learning has made progress in voice and image recognition, image classification, and natural language processing. Prior to deep learning, decision tree, linear discriminant analysis (LDA, support vector machines (SVM, k-nearest neighbors algorithm (K-NN, and ensemble learning were popular in solving classification problems. In this paper, we applied the previously mentioned and deep learning techniques to hairy scalp images. Hairy scalp problems are usually diagnosed by non-professionals in hair salons, and people with such problems may be advised by these non-professionals. Additionally, several common scalp problems are similar; therefore, non-experts may provide incorrect diagnoses. Hence, scalp problems have worsened. In this work, we implemented and compared the deep-learning method, the ImageNet-VGG-f model Bag of Words (BOW, with machine-learning classifiers, and histogram of oriented gradients (HOG/pyramid histogram of oriented gradients (PHOG with machine-learning classifiers. The tools from the classification learner apps were used for hairy scalp image classification. The results indicated that deep learning can achieve an accuracy of 89.77% when the learning rate is 1 × 10−4, and this accuracy is far higher than those achieved by BOW with SVM (80.50% and PHOG with SVM (53.0%.
Full Text Available Skill learning autonomously through interactions with the environment is a crucial ability for intelligent robot. A perception-action integration or sensorimotor cycle, as an important issue in imitation learning, is a natural mechanism without the complex program process. Recently, neurocomputing model and developmental intelligence method are considered as a new trend for implementing the robot skill learning. In this paper, based on research of the human brain neocortex model, we present a skill learning method by perception-action integration strategy from the perspective of hierarchical temporal memory (HTM theory. The sequential sensor data representing a certain skill from a RGB-D camera are received and then encoded as a sequence of Sparse Distributed Representation (SDR vectors. The sequential SDR vectors are treated as the inputs of the perception-action HTM. The HTM learns sequences of SDRs and makes predictions of what the next input SDR will be. It stores the transitions of the current perceived sensor data and next predicted actions. We evaluated the performance of this proposed framework for learning the shaking hands skill on a humanoid NAO robot. The experimental results manifest that the skill learning method designed in this paper is promising.
A Monte Carlo learning and biasing technique is described that does its learning and biasing in the random number space rather than the physical phase-space. The technique is probably applicable to all linear Monte Carlo problems, but no proof is provided here. Instead, the technique is illustrated with a simple Monte Carlo transport problem. Problems encountered, problems solved, and speculations about future progress are discussed. 12 refs
Dunjko, Vedran; Briegel, Hans J
Quantum information technologies, on the one hand, and intelligent learning systems, on the other, are both emergent technologies that are likely to have a transformative impact on our society in the future. The respective underlying fields of basic research-quantum information versus machine learning (ML) and artificial intelligence (AI)-have their own specific questions and challenges, which have hitherto been investigated largely independently. However, in a growing body of recent work, researchers have been probing the question of the extent to which these fields can indeed learn and benefit from each other. Quantum ML explores the interaction between quantum computing and ML, investigating how results and techniques from one field can be used to solve the problems of the other. Recently we have witnessed significant breakthroughs in both directions of influence. For instance, quantum computing is finding a vital application in providing speed-ups for ML problems, critical in our 'big data' world. Conversely, ML already permeates many cutting-edge technologies and may become instrumental in advanced quantum technologies. Aside from quantum speed-up in data analysis, or classical ML optimization used in quantum experiments, quantum enhancements have also been (theoretically) demonstrated for interactive learning tasks, highlighting the potential of quantum-enhanced learning agents. Finally, works exploring the use of AI for the very design of quantum experiments and for performing parts of genuine research autonomously, have reported their first successes. Beyond the topics of mutual enhancement-exploring what ML/AI can do for quantum physics and vice versa-researchers have also broached the fundamental issue of quantum generalizations of learning and AI concepts. This deals with questions of the very meaning of learning and intelligence in a world that is fully described by quantum mechanics. In this review, we describe the main ideas, recent developments and
Many studies suggest that classical music can inccrease the listeners’ intelligence, including mathematical intelligence [3, 12, 2, 11]. In this research, we used the classical music of Baroque era as the backsound during math learning. The research method used was quasi experiment with nonequivalent pretest-posttest control group design to grade V SD students in Tasikmalaya city. The results show that the use of classical music of Baroque era during the learning of mathematics gave a high co...
Demetriadis, Stavros; Xhafa, Fatos
Adaptation and personalization have been extensively studied in CSCL research community aiming to design intelligent systems that adaptively support eLearning processes and collaboration. Yet, with the fast development in Internet technologies, especially with the emergence of new data technologies and the mobile technologies, new opportunities and perspectives are opened for advanced adaptive and personalized systems. Adaptation and personalization are posing new research and development challenges to nowadays CSCL systems. In particular, adaptation should be focused in a multi-dimensional way (cognitive, technological, context-aware and personal). Moreover, it should address the particularities of both individual learners and group collaboration. As a consequence, the aim of this book is twofold. On the one hand, it discusses the latest advances and findings in the area of intelligent adaptive and personalized learning systems. On the other hand it analyzes the new implementation perspectives for intelligen...
Prieta, Fernando; Mascio, Tania; Gennari, Rosella; Rodríguez, Javier; Vittorini, Pierpaolo
The 6th International Conference in Methodologies and intelligent Systems for Technology Enhanced Learning held in Seville (Spain) is host by the University of Seville from 1st to 3rd June, 2016. The 6th edition of this conference expands the topics of the evidence-based TEL workshops series in order to provide an open forum for discussing intelligent systems for TEL, their roots in novel learning theories, empirical methodologies for their design or evaluation, stand-alone solutions or web-based ones. It intends to bring together researchers and developers from industry, the education field and the academic world to report on the latest scientific research, technical advances and methodologies.
This successful book provides in its second edition an interactive and illustrative guide from two-dimensional curve fitting to multidimensional clustering and machine learning with neural networks or support vector machines. Along the way topics like mathematical optimization or evolutionary algorithms are touched. All concepts and ideas are outlined in a clear cut manner with graphically depicted plausibility arguments and a little elementary mathematics. The major topics are extensively outlined with exploratory examples and applications. The primary goal is to be as illustrative as possible without hiding problems and pitfalls but to address them. The character of an illustrative cookbook is complemented with specific sections that address more fundamental questions like the relation between machine learning and human intelligence. All topics are completely demonstrated with the computing platform Mathematica and the Computational Intelligence Packages (CIP), a high-level function library developed with M...
Yerizon, Y.; Putra, A. A.; Subhan, M.
Students have a low mathematical ability because they are used to learning to hear the teacher's explanation. For that students are given activities to sharpen his ability in math. One way to do that is to create discovery learning based work sheet. The development of this worksheet took into account specific student learning styles including in schools that have classified students based on multiple intelligences. The dominant learning styles in the classroom were intrapersonal and interpersonal. The purpose of this study was to discover students’ responses to the mathematics work sheets of the junior high school with a discovery learning approach suitable for students with Intrapersonal and Interpersonal Intelligence. This tool was developed using a development model adapted from the Plomp model. The development process of this tools consists of 3 phases: front-end analysis/preliminary research, development/prototype phase and assessment phase. From the results of the research, it is found that students have good response to the resulting work sheet. The worksheet was understood well by students and its helps student in understanding the concept learned.
Blanchet-Cohen, Natasha; Reilly, Rosemary C.
This paper examines the potential of culturally-responsive environmental education to engage immigrant early adolescents. Our study suggests that environmental involvement can become a means and an end for children to bridge their school and home in agential ways. Drawing from a multi-phase study involving focus groups with children, parents, and…
Duff, Patricia A.; Wong, Ping; Early, Margaret
Discusses research in English-as-a-Second-Language in the workplace, identifying gaps in the existing literature and promising directions for new explorations. Reports on a qualitative study conducted in one type of program for immigrant women and men in Western Canada seeking to become long-term resident care aides or home support workers.…
Shappeck, Marco; Moss, Glenda
For this creative scholarly project, preservice teachers were invited to participate with two instructors by offering their sociopolitical autobiographies and reflective-reflexive reading responses for group discussion and analysis to explore the journal's theme "Immigration and Teacher Education: The Crisis and the Opportunity." The goal was to…
Chen, Yen-Ching; Wei, Shu-Hui; Yeh, Kuo-Wei; Chen, Mei-Yen
Many studies have indicated that most immigrant women come from underdeveloped countries, and this can have negative effects on their lives, children's adaptation to school, and medical care utilization. However, there is insufficient literature about differences in infant caretaking, pre-postpartum health care, and health outcome between immigrant and native Taiwanese populations. The aim of this study was to investigate the differences between Southern Asia immigrants and Taiwanese women in their access to medical care, postnatal growth, and infant care throughout the first six months postpartum. Comparative and descriptive designs were applied. Immigrant women were eligible if they visited three suburban settings of the Outpatient Department of Obstetrics and Gynecology and the Outpatient Department of Pediatrics in Northern Taiwan during the period up to six months postpartum. Immigrant women appeared to have a lower frequency of antenatal examinations and obtained less health information from health care providers. However, they did not differ significantly from native Taiwanese women in maternal body size, postnatal growth curves, exclusive breastfeeding rates or vaccination awareness at the 6th month postpartum. Learning strengths from cultural differences between immigrant and native women and closing the gaps in health inequality are important issues. Despite the limitation of small sample size, the present findings can be used as references to help health care providers to develop further health policies in Taiwan.
Classifying observations from a mixture distribution is considered a simple model for learning. Existing results are integrated to obtain asymptotically optimal estimators of the classification rule. The asymptotic relative efficiencies show that a tutored learner is considerably more efficient on difficult problems, but only slightly more efficient on easy problems. This suggests a combined method that seeks instruction on hard cases
Martinez, Luz M.
The changing social and economic reality of our world continues to shape how learning is conducted and acquired in the adult classroom and beyond. Given the pivotal importance for an adult to develop a variety of cognitive and emotional skills and given the need to work in collaboration with others, within educational environments and the…
Nacheva-Skopalik, Lilyana; Green, Steve
Access to education is one of the main human rights. Everyone should have access to education and be capable of benefiting from it. However there are a number who are excluded, not because of a lack of ability but simply because they have a disability or specific need which current education systems do not address. A learning system in which…
Full Text Available The continuous optimization of business processes is still a challenge for companies. In times of digital transformation, faster changing internal and external framework conditions and new customer expectations for fastest delivery and best quality of goods and many more, companies should set up their internal process at the best way. But what to do if framework conditions changed unexpectedly? The purpose of the paper is to analyse how the digital transformation will impact the Business Process Management (BPM while using methods like machine learning or artificial intelligence. Therefore, the core components will be explained, compared and set up in relation. To identify application areas interviews and analysis will be held up with digital companies. The finding of the paper will be recommendation for action in the field of BPM and process optimization through machine learning and artificial intelligence. The Approach of optimizing and management processes via machine learning and artificial intelligence will support companies to decide which tool will be the best for automated BPM.
M. H. El-Saify
Full Text Available The distillation process is vital in many fields of chemical industries, such as the two-coupled distillation columns that are usually highly nonlinear Multi-Input Multi-Output (MIMO coupled processes. The control of MIMO process is usually implemented via a decentralized approach using a set of Single-Input Single-Output (SISO loop controllers. Decoupling the MIMO process into group of single loops requires proper input-output pairing and development of decoupling compensator unit. This paper proposes a novel intelligent decoupling approach for MIMO processes based on new MIMO brain emotional learning architecture. A MIMO architecture of Brain Emotional Learning Based Intelligent Controller (BELBIC is developed and applied as a decoupler for 4 input/4 output highly nonlinear coupled distillation columns process. Moreover, the performance of the proposed Brain Emotional Learning Based Intelligent Decoupler (BELBID is enhanced using Particle Swarm Optimization (PSO technique. The performance is compared with the PSO optimized steady state decoupling compensation matrix. Mathematical models of the distillation columns and the decouplers are built and tested in simulation environment by applying the same inputs. The results prove remarkable success of the BELBID in minimizing the loops interactions without degrading the output that every input has been paired with.
Manapa, I. Y. H.; Budiyono; Subanti, S.
The aim of this research is to determine the effect of TAI or direct learning (DL) on student’s mathematics achievement viewed from spatial intelligence. This research was quasi experiment. The population was 10th grade senior high school students in Alor Regency on academic year of 2015/2016 chosen by stratified cluster random sampling. The data were collected through achievement and spatial intelligence test. The data were analyzed by two ways, ANOVA with unequal cell and scheffe test. This research showed that student’s mathematics achievement used in TAI had better results than DL models one. In spatial intelligence category, student’s mathematics achievement with high spatial intelligence has better result than the other spatial intelligence category and students with high spatial intelligence have better results than those with middle spatial intelligence category. At TAI, student’s mathematics achievement with high spatial intelligence has better result than those with the other spatial intelligence category and students with middle spatial intelligence have better results than students with low spatial intelligence. In DL model, student’s mathematics achievement with high and middle spatial intelligence has better result than those with low spatial intelligence, but students with high spatial intelligence and middle spatial intelligence have no significant difference. In each category of spatial intelligence and learning model, mathematics achievement has no significant difference.
Qiu, Guoqing; Kou, Qianqian; Niu, Ting
With the development of artificial intelligence and data mining technology, big data has gradually entered people's field of vision. In the process of dealing with large data, clustering is an important processing method. By introducing the reverse learning method in the clustering process of PAM clustering algorithm, to further improve the limitations of one-time clustering in unsupervised clustering learning, and increase the diversity of clustering clusters, so as to improve the quality of clustering. The algorithm analysis and experimental results show that the algorithm is feasible.
Schneider, Michael K.; Alford, Mark; Babko-Malaya, Olga; Blasch, Erik; Chen, Lingji; Crespi, Valentino; HandUber, Jason; Haney, Phil; Nagy, Jim; Richman, Mike; Von Pless, Gregory; Zhu, Howie; Rhodes, Bradley J.
Our Multi-INT Data Association Tool (MIDAT) learns patterns of life (POL) of a geographical area from video analyst observations called out in textual reporting. Typical approaches to learning POLs from video make use of computer vision algorithms to extract locations in space and time of various activities. Such approaches are subject to the detection and tracking performance of the video processing algorithms. Numerous examples of human analysts monitoring live video streams annotating or "calling out" relevant entities and activities exist, such as security analysis, crime-scene forensics, news reports, and sports commentary. This user description typically corresponds with textual capture, such as chat. Although the purpose of these text products is primarily to describe events as they happen, organizations typically archive the reports for extended periods. This archive provides a basis to build POLs. Such POLs are useful for diagnosis to assess activities in an area based on historical context, and for consumers of products, who gain an understanding of historical patterns. MIDAT combines natural language processing, multi-hypothesis tracking, and Multi-INT Activity Pattern Learning and Exploitation (MAPLE) technologies in an end-to-end lab prototype that processes textual products produced by video analysts, infers POLs, and highlights anomalies relative to those POLs with links to "tracks" of related activities performed by the same entity. MIDAT technologies perform well, achieving, for example, a 90% F1-value on extracting activities from the textual reports.
Blum, Denise; de la Piedra, Maria Teresa
This article examines the use of Critical Race Pedagogy in two service-learning initiatives that prepare pre-service teachers for working with an increasing immigrant student population in California and Texas. It is not uncommon for teachers to participate in the "Othering" dominant discourse that tends to see those who are of a lower…
Ren, Xuezhu; Schweizer, Karl; Wang, Tengfei; Xu, Fen
The present study provides a new account of how fluid intelligence influences academic performance. In this account a complex learning component of fluid intelligence tests is proposed to play a major role in predicting academic performance. A sample of 2, 277 secondary school students completed two reasoning tests that were assumed to represent fluid intelligence and standardized math and verbal tests assessing academic performance. The fluid intelligence data were decomposed into a learning component that was associated with the position effect of intelligence items and a constant component that was independent of the position effect. Results showed that the learning component contributed significantly more to the prediction of math and verbal performance than the constant component. The link from the learning component to math performance was especially strong. These results indicated that fluid intelligence, which has so far been considered as homogeneous, could be decomposed in such a way that the resulting components showed different properties and contributed differently to the prediction of academic performance. Furthermore, the results were in line with the expectation that learning was a predictor of performance in school.
Gunderson, Elizabeth A; Donnellan, M Brent; Robins, Richard W; Trzesniewski, Kali H
Individuals who believe that intelligence can be improved with effort (an incremental theory of intelligence) and who approach challenges with the goal of improving their understanding (a learning goal) tend to have higher academic achievement. Furthermore, parent praise is associated with children's incremental theories and learning goals. However, the influences of parental criticism, as well as different forms of praise and criticism (e.g., process vs. person), have received less attention. We examine these associations by analyzing two existing datasets (Study 1: N = 317 first to eighth graders; Study 2: N = 282 fifth and eighth graders). In both studies, older children held more incremental theories of intelligence, but lower learning goals, than younger children. Unexpectedly, the relation between theories of intelligence and learning goals was nonsignificant and did not vary with children's grade level. In both studies, overall perceived parent praise positively related to children's learning goals, whereas perceived parent criticism negatively related to incremental theories of intelligence. In Study 2, perceived parent process praise was the only significant (positive) predictor of children's learning goals, whereas perceived parent person criticism was the only significant (negative) predictor of incremental theories of intelligence. Finally, Study 2 provided some support for our hypothesis that age-related differences in perceived parent praise and criticism can explain age-related differences in children's learning goals. Results suggest that incremental theories of intelligence and learning goals might not be strongly related during childhood and that perceived parent praise and criticism have important, but distinct, relations with each motivational construct. Copyright © 2018 Elsevier Inc. All rights reserved.
Jha, Sumit Kumar [University of Central Florida, Orlando; Pullum, Laura L [ORNL; Ramanathan, Arvind [ORNL
Embedded intelligent systems ranging from tiny im- plantable biomedical devices to large swarms of autonomous un- manned aerial systems are becoming pervasive in our daily lives. While we depend on the flawless functioning of such intelligent systems, and often take their behavioral correctness and safety for granted, it is notoriously difficult to generate test cases that expose subtle errors in the implementations of machine learning algorithms. Hence, the validation of intelligent systems is usually achieved by studying their behavior on representative data sets, using methods such as cross-validation and bootstrapping.In this paper, we present a new testing methodology for studying the correctness of intelligent systems. Our approach uses symbolic decision procedures coupled with statistical hypothesis testing to. We also use our algorithm to analyze the robustness of a human detection algorithm built using the OpenCV open-source computer vision library. We show that the human detection implementation can fail to detect humans in perturbed video frames even when the perturbations are so small that the corresponding frames look identical to the naked eye.
Raymond-Flesch, Marissa; Siemons, Rachel; Brindis, Claire D
Limited research has focused on undocumented immigrants' health and access to care. This paper describes participant engagement strategies used to investigate the health needs of immigrants eligible for Deferred Action for Childhood Arrivals (DACA). Community-based strategies engaged advocates and undocumented Californians in study design and recruitment. Outreach in diverse settings, social media, and participant-driven sampling recruited 61 DACA-eligible focus group participants. Social media, community-based organizations (CBOs), family members, advocacy groups, and participant-driven sampling were the most successful recruitment strategies. Participants felt engaging in research was instrumental for sharing their concerns with health care providers and policymakers, noteworthy in light of their previously identified fears and mistrust of government officials. Using multiple culturally responsive strategies including participant-driven sampling, engagement with CBOs, and use of social media, those eligible for DACA eagerly engage as research participants. Educating researchers and institutional review boards (IRBs) about legal and safety concerns can improve research engagement.
Chen, C. M.
Personalized curriculum sequencing is an important research issue for web-based learning systems because no fixed learning paths will be appropriate for all learners. Therefore, many researchers focused on developing e-learning systems with personalized learning mechanisms to assist on-line web-based learning and adaptively provide learning paths…
Full Text Available Many studies suggest that classical music can inccrease the listeners’ intelligence, including mathematical intelligence [3, 12, 2, 11]. In this research, we used the classical music of Baroque era as the backsound during math learning. The research method used was quasi experiment with nonequivalent pretest-posttest control group design to grade V SD students in Tasikmalaya city. The results show that the use of classical music of Baroque era during the learning of mathematics gave a high contribution to the mathematical intelligence of fifth grade elementary school students. The student's mathematical intelligence can be seen in the cognitive abilities which were at the high level in the knowledge up to analysis, and at the low level in the synthesis and evaluation. Low mathematical intelligence was shown by students in calculating amount and difference of time, and projecting word problem into the form of mathematical problems. High mathematical intelligence arose in reading and writing integers in words and numbers. Thus, the mathematical intelligence of fifth grade Elementary School students will be better if classical music of Baroque era is used as the backsound in mathematics learning about solving math problems.
Full Text Available A key objective of education is to prepare individuals to be fully-functioning learners. This entails developing the cognitive, metacognitive, motivational, cultural, and emotional competencies. The present study aimed to examine the interrelationships among adaptability, tolerance of ambiguity, cultural intelligence, learning approach, and language achievement as manifestations of the above competencies within a single model. The participants comprised one hundred eighty BA and MA Iranian university students studying English language teaching and translation. The instruments used in this study consisted of the translated versions of four questionnaires: second language tolerance of ambiguity scale, adaptability taken from emotional intelligence inventory, cultural intelligence (CQ inventory, and the revised study process questionnaire measuring surface and deep learning. The results estimated via structural equation modeling (SEM revealed that the proposed model containing the variables under study had a good fit with the data. It was found that all the variables except adaptability directly influenced language achievement with deep approach having the highest impact and ambiguity tolerance having the lowest influence. In addition, ambiguity tolerance was a positive and significant predictor of deep approach. CQ was found to be under the influence of both ambiguity tolerance and adaptability. The findings were discussed in the light of the yielded results.
Kim, Dong Yun; Seong, Poong Hyun
In this study, we proposed a fuzzy gain scheduler with intelligent learning algorithm for a reactor control. In the proposed algorithm, we used the gradient descent method to learn the rule bases of a fuzzy algorithm. These rule bases are learned toward minimizing an objective function, which is called a performance cost function. The objective of fuzzy gain scheduler with intelligent learning algorithm is the generation of adequate gains, which minimize the error of system. The condition of every plant is generally changed as time gose. That is, the initial gains obtained through the analysis of system are no longer suitable for the changed plant. And we need to set new gains, which minimize the error stemmed from changing the condition of a plant. In this paper, we applied this strategy for reactor control of nuclear power plant (NPP), and the results were compared with those of a simple PI controller, which has fixed gains. As a result, it was shown that the proposed algorithm was superior to the simple PI controller
Full Text Available Actualizing instructional intercessions to suit learner contrasts has gotten extensive consideration. Among these individual contrast factors, the observational confirmation in regards to the academic benefit of learning styles has been addressed, yet the examination on the issue proceeds. Late improvements in web-based executions have driven researchers to re-examine the learning styles in adaptive tutoring frameworks. Adaptivity in intelligent tutoring systems is strongly influenced by the learning style of a learner. This study involved extensive document analysis of adaptive tutoring systems based on learning styles. Seventy-eight studies in literature from 2001 to 2016 were collected and classified under select parameters such as main focus, purpose, research types, methods, types and levels of participants, field/area of application, learner modelling, data gathering tools used and research findings. The current studies reveal that majority of the studies defined a framework or architecture of adaptive intelligent tutoring system (AITS while others focused on impact of AITS on learner satisfaction and academic outcomes. Currents trends, gaps in literature and ications were discussed.
Tong, Fang; Fu, Tong
To evaluate the differences in fluid intelligence tests between normal children and children with learning difficulties in China. PubMed, MD Consult, and other Chinese Journal Database were searched from their establishment to November 2012. After finding comparative studies of Raven measurements of normal children and children with learning difficulties, full Intelligent Quotation (FIQ) values and the original values of the sub-measurement were extracted. The corresponding effect model was selected based on the results of heterogeneity and parallel sub-group analysis was performed. Twelve documents were included in the meta-analysis, and the studies were all performed in mainland of China. Among these, two studies were performed at child health clinics, the other ten sites were schools and control children were schoolmates or classmates. FIQ was evaluated using a random effects model. WMD was -13.18 (95% CI: -16.50- -9.85). Children with learning difficulties showed significantly lower FIQ scores than controls (Pintelligence of children with learning difficulties was lower than that of normal children. Delayed development in sub-items of C, D, and E was more obvious.
Wallace, Scott A.; McCartney, Robert; Russell, Ingrid
Project MLeXAI (Machine Learning eXperiences in Artificial Intelligence (AI)) seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense - a simple real-time strategy game and Checkers - a classic turn-based board game. From the instructors' prospective, we examine aspects of design and implementation as well as the challenges and rewards of using the curricula. We explore students' responses to the projects via the results of a common survey. Finally, we compare the student perceptions from the game-based projects to non-game based projects from the first phase of Project MLeXAI.
Gallardo, Carmen Ecija; Velasco, Lilian
This paper reports on the first test of the value of an online curriculum in social intelligence (SI). Built from current social and cognitive neuroscience research findings, the 50 session SI program was administered, with facilitation in Spanish by classroom instructors, to 207 students from Universidad Rey Juan Carlos in Madrid as part of their undergraduate classes. All materials were translated into Castilian Spanish, including outcome measures of SI that have been used in prior studies to provide valid estimates of two key components of social intelligence: 1) Sensitivity to others and 2) confidence in one’s capacity to manage social situations. Pre- and Posttest were administered to participants in the SI training, and also to 87 students in similar classes who did not receive the program who served as the control group. Gender and emotional intelligence levels at pretest also were examined as potential individual differences that might affect the impact of the program on study outcomes. Repeated measures ANOVAs on study outcomes revealed significant increases, from pre to post, in most measures of social intelligence for program participants in comparison to controls, with no effects of gender or age on program effectiveness. Prior scores on emotional intelligence were not a prerequisite for learning from the program. Some findings suggest ways the program may be improved to have stronger effects. Nonetheless, the findings indicate that the SI program tested here shows considerable promise as a means to increase the willingness of young adults to take the perspective of others and enhance their efficacy for initiating and sustaining positive social connections. PMID:26076133
Eva K Zautra
Full Text Available This paper reports on the first test of the value of an online curriculum in social intelligence (SI. Built from current social and cognitive neuroscience research findings, the 50 session SI program was administered, with facilitation in Spanish by classroom instructors, to 207 students from Universidad Rey Juan Carlos in Madrid as part of their undergraduate classes. All materials were translated into Castilian Spanish, including outcome measures of SI that have been used in prior studies to provide valid estimates of two key components of social intelligence: 1 Sensitivity to others and 2 confidence in one's capacity to manage social situations. Pre- and Posttest were administered to participants in the SI training, and also to 87 students in similar classes who did not receive the program who served as the control group. Gender and emotional intelligence levels at pretest also were examined as potential individual differences that might affect the impact of the program on study outcomes. Repeated measures ANOVAs on study outcomes revealed significant increases, from pre to post, in most measures of social intelligence for program participants in comparison to controls, with no effects of gender or age on program effectiveness. Prior scores on emotional intelligence were not a prerequisite for learning from the program. Some findings suggest ways the program may be improved to have stronger effects. Nonetheless, the findings indicate that the SI program tested here shows considerable promise as a means to increase the willingness of young adults to take the perspective of others and enhance their efficacy for initiating and sustaining positive social connections.
Zautra, Eva K; Zautra, Alex J; Gallardo, Carmen Ecija; Velasco, Lilian
This paper reports on the first test of the value of an online curriculum in social intelligence (SI). Built from current social and cognitive neuroscience research findings, the 50 session SI program was administered, with facilitation in Spanish by classroom instructors, to 207 students from Universidad Rey Juan Carlos in Madrid as part of their undergraduate classes. All materials were translated into Castilian Spanish, including outcome measures of SI that have been used in prior studies to provide valid estimates of two key components of social intelligence: 1) Sensitivity to others and 2) confidence in one's capacity to manage social situations. Pre- and Posttest were administered to participants in the SI training, and also to 87 students in similar classes who did not receive the program who served as the control group. Gender and emotional intelligence levels at pretest also were examined as potential individual differences that might affect the impact of the program on study outcomes. Repeated measures ANOVAs on study outcomes revealed significant increases, from pre to post, in most measures of social intelligence for program participants in comparison to controls, with no effects of gender or age on program effectiveness. Prior scores on emotional intelligence were not a prerequisite for learning from the program. Some findings suggest ways the program may be improved to have stronger effects. Nonetheless, the findings indicate that the SI program tested here shows considerable promise as a means to increase the willingness of young adults to take the perspective of others and enhance their efficacy for initiating and sustaining positive social connections.
Dekker, Sanne; Jolles, Jelle
This study evaluated a new teaching module about "Brain and Learning" using a controlled design. The module was implemented in high school biology classes and comprised three lessons: (1) brain processes underlying learning; (2) neuropsychological development during adolescence; and (3) lifestyle factors that influence learning performance. Participants were 32 biology teachers who were interested in "Brain and Learning" and 1241 students in grades 8-9. Teachers' knowledge and students' beliefs about learning potential were examined using online questionnaires. Results indicated that before intervention, biology teachers were significantly less familiar with how the brain functions and develops than with its structure and with basic neuroscientific concepts (46 vs. 75% correct answers). After intervention, teachers' knowledge of "Brain and Learning" had significantly increased (64%), and more students believed that intelligence is malleable (incremental theory). This emphasizes the potential value of a short teaching module, both for improving biology teachers' insights into "Brain and Learning," and for changing students' beliefs about intelligence.
Creel-Erickson, Gwen Rene
Currently the United States is home to a large and increasing immigrant population. Many of these immigrant students use community-based programs for their educational needs. Despite the large number of immigrant students who currently use alternate resources, such as churches and community centers, for education, adult language learners in…
D'Amico, Antonella; Guastaferro, Teresa
The purpose of this study was to analyse adjustment problems in a group of adolescents with a Specific Learning Disorder (SLD), examining to what extent they depend on the severity level of the learning disorder and/or on the individual's level of emotional intelligence. Adjustment problems,, perceived severity levels of SLD, and emotional and…
Sandberg, J.; Maris, M.; Hoogendoorn, P.
Two groups participated in a study on the added value of a gaming context and intelligent adaptation for a mobile learning application. The control group worked at home for a fortnight with the original Mobile English Learning application (MEL-original) developed in a previous project. The
Yukay Yuksel, Muge
In this study, to what extent 7-9-year old primary school children's' social behaviors at school vary depending on their grade, gender and learning disability was investigated. In addition, the predictive value of the intelligence scores of children with normal development and with learning disability was explored for their negative and positive…
A viewgraph presentation on the lessons learned and flight results from the F15 Intelligent Flight Control System (IFCS) project is shown. The topics include: 1) F-15 IFCS Project Goals; 2) Motivation; 3) IFCS Approach; 4) NASA F-15 #837 Aircraft Description; 5) Flight Envelope; 6) Limited Authority System; 7) NN Floating Limiter; 8) Flight Experiment; 9) Adaptation Goals; 10) Handling Qualities Performance Metric; 11) Project Phases; 12) Indirect Adaptive Control Architecture; 13) Indirect Adaptive Experience and Lessons Learned; 14) Gen II Direct Adaptive Control Architecture; 15) Current Status; 16) Effect of Canard Multiplier; 17) Simulated Canard Failure Stab Open Loop; 18) Canard Multiplier Effect Closed Loop Freq. Resp.; 19) Simulated Canard Failure Stab Open Loop with Adaptation; 20) Canard Multiplier Effect Closed Loop with Adaptation; 21) Gen 2 NN Wts from Simulation; 22) Direct Adaptive Experience and Lessons Learned; and 23) Conclusions
Utilizing high-resolution remote sensing images for earth observation has become the common method of land use monitoring. It requires great human participation when dealing with traditional image interpretation, which is inefficient and difficult to guarantee the accuracy. At present, the artificial intelligent method such as deep learning has a large number of advantages in the aspect of image recognition. By means of a large amount of remote sensing image samples and deep neural network models, we can rapidly decipher the objects of interest such as buildings, etc. Whether in terms of efficiency or accuracy, deep learning method is more preponderant. This paper explains the research of deep learning method by a great mount of remote sensing image samples and verifies the feasibility of building extraction via experiments.
Full Text Available The purpose of this study was to analyse adjustment problems in a group of adolescents with a Specific Learning Disorder (SLD, examining to what extent they depend on the severity level of the learning disorder and/or on the individual‟s level of emotional intelligence. Adjustment problems,, perceived severity levels of SLD, and emotional and meta-emotional intelligence were examined in 34 adolescents with SLD. Results demonstrated that emotional beliefs, emotional self-concept and emotional intelligence are very important factors in the psychological adjustment of adolescents with SLD. These results provide evidence for the importance of considering meta-emotional intelligence in both diagnostic and intervention protocols, as well as in the inclusive education of students with SLD.
Javaid, Q.; Arif, F.
The rapid advancement in ICT (Information and Communication Technology) is causing a paradigm shift in eLearning domain. Traditional eLearning systems suffer from certain shortcomings like tight coupling of system components, lack of personalization, flexibility, and scalability and performance issues. This study aims at addressing these challenges through an MAS (Multi Agent System) based multi-layer architecture supported by web services. The foremost objective of this study is to enhance learning process efficiency by provision of flexibility features for learning and assessment processes. Proposed architecture consists of two sub-system namely eLearning and eAssesssment. This architecture comprises of five distinct layers for each sub-system, with active agents responsible for miscellaneous tasks including content handling, updating, resource optimization, load handling and provision of customized environments for learners and instructors. Our proposed architecture aims at establishment of a facilitation level to learners as well as instructors for convenient acquisition and dissemination of knowledge. Personalization features like customized environments, personalized content retrieval and recommendations, adaptive assessment and reduced response time, are believed to significantly enhance learning and tutoring experience. In essence characteristics like intelligence, personalization, interactivity, usability, laidback accessibility and security, signify aptness of proposed architecture for improving conventional learning and assessment processes. Finally we have evaluated our proposed architecture by means of analytical comparison and survey considering certain quality attributes. (author)
Nuallaong, Winitra; Nuallaong, Thanya; Preechadirek, Nongluck
To measure academic achievement of the multiple intelligence-based learning medium via a tablet device. This is a quasi-experimental research study (non-randomized control group pretest-posttest design) in 62 grade 1 elementary students (33 males and 29 females). Thirty-one students were included in an experimental group using purposive sampling by choosing a student who had highest multiple intelligence test scores in logical-mathematic. Then, this group learned by the new learning medium via a tablet which the application matched to logical-mathematic multiple intelligence. Another 31 students were included in a control group using simple random sampling and then learning by recitation. Both groups did pre-test and post-test vocabulary. Thirty students in the experimental group and 24 students in the control group increased post-test scores (odds ratio = 8.75). Both groups made significant increasing in post-test scores. The experimental group increased 9.07 marks (95% CI 8.20-9.93) significantly higher than the control group which increased 4.39 marks (95% CI 3.06-5.72) (t = -6.032, df = 51.481, p learning from either multiple intelligence-based learning medium via a tablet or recitation can contribute academic achievement, learningfrom the new medium contributed more achievement than recitation. The new learning medium group had higher post-test scores 8.75 times than the recitation group. Therefore, the new learning medium is more effective than the traditional recitation in terms of academic achievement. This study has limitations because samples came from the same school. However, the previous study in Thailand did notfind a logical-mathematical multiple intelligence difference among schools. In the future, long-term research to find how the new learning medium affects knowledge retention will support the advantage for life-long learning.
Larsen, Lasse Juel
This paper examines play, gaming and learning in regard to intelligent playware developed for outdoor use. The key questions are how does these novel artefacts influence the concept of play, gaming and learning. Up until now play and game have been understood as different activities. This paper...... examines if the sharp differentiation between the two can be uphold in regard to intelligent playware for outdoor use. Play and game activities will be analysed and viewed in conjunction with learning contexts. This paper will stipulate that intelligent playware facilitates rapid shifts in contexts...
Eissa, Mourad Ali; Mostafa, Amaal Ahmed
This study investigated the effect of using differentiated instruction by integrating multiple intelligences and learning styles on solving problems, achievement in, and attitudes towards math in six graders with learning disabilities in cooperative groups. A total of 60 students identified with LD were invited to participate. The sample was…
Full Text Available Objective: The main objective of this study is to define and operationalize the concept of immigrant capital, a key factor that differentiates immigrant from host country entrepreneurs in how they recognize and start new ventures. Research Design & Methods: A detailed analysis of contemporary immigrant entrepreneurship and opportunity recognition literature was carried out. Using grounded theory, we synthesized the outcomes from the analysis of eight Canadian and U.S. case studies of successful immigrant entrepreneurs with the key findings from the literature to define and develop a model of immigrant capital. Findings: Based on our grounded theory development process we show that the concept of immigrant capital as a distillate of human, cultural, economic and social capital that goes beyond expected opportunity recognition (OR drivers like prior knowledge and prior experience to differentiate and enhance the immigrant entrepreneur’s ability to recognize business opportunities compared to host country entrepreneurs. We found immigrant capital to be a consequence of being boundary spanners in host and home country networks. Implications & Recommendations: Understanding a unique resource like immigrant capital, will help immigrant as well as host country entrepreneurs further develop their opportunity recognition ability by bridging gaps and fulfilling the needs for both, immigrant and host country consumers. Contribution & Value Added: The main contribution is the theoretical development, identification and definition of the immigrant capital model and propositions that will articulate the factors that lead to the conceptualization and operationalization of immigrant capital. Furthermore, the immigrant capital model can serve host country entrepreneurs to develop cross-cultural networks and jump-start entrepreneurial activities in their home countries as well as learn how to expand their operations into global markets.
Full Text Available Anna Riva, Renata Nacinovich, Nadia Bertuletti, Valentina Montrasi, Sara Marchetti, Francesca Neri, Monica Bomba Child and Adolescent Mental Health Department, University of Milan Bicocca, San Gerardo Hospital, Monza, Italy Purpose: The aim of this study is to compare the Wechsler Intelligence Scale for Children® – fourth edition IV (WISC IV intellectual profile of two groups of children with specific learning disorder, a group of bilingual children and a group of monolingual Italian children, in order to identify possible significant differences between them. Patients and methods: A group of 48 bilingual children and a group of 48 Italian monolingual children were included in this study. A preliminary comparison showed the homogeneity of the two groups regarding learning disorder typology and sociodemographic characteristics (age at WISC IV assessment, sex and years of education in Italy with the exception of socioeconomic status. Socioeconomic status was then used as a covariate in the analysis. Results: Even if the two groups were comparable in specific learning disorder severity and, in particular, in the text comprehension performance, our findings showed that the WISC IV performances of the bilingual group were significantly worse than the Italian group in Full Scale Intelligence Quotient (P=0.03, in General Ability Index (P=0.03, in Working Memory Index (P=0.009 and in some subtests and clusters requiring advanced linguistic abilities. Conclusion: These results support the hypothesis of a weakness in metalinguistic abilities in bilingual children with specific learning disorders than monolinguals. If confirmed, this result must be considered in the rehabilitation treatment. Keywords: children, bilingualism, WISC IV, SLD
Full Text Available OBJECTIVE: To evaluate the differences in fluid intelligence tests between normal children and children with learning difficulties in China. METHOD: PubMed, MD Consult, and other Chinese Journal Database were searched from their establishment to November 2012. After finding comparative studies of Raven measurements of normal children and children with learning difficulties, full Intelligent Quotation (FIQ values and the original values of the sub-measurement were extracted. The corresponding effect model was selected based on the results of heterogeneity and parallel sub-group analysis was performed. RESULTS: Twelve documents were included in the meta-analysis, and the studies were all performed in mainland of China. Among these, two studies were performed at child health clinics, the other ten sites were schools and control children were schoolmates or classmates. FIQ was evaluated using a random effects model. WMD was -13.18 (95% CI: -16.50- -9.85. Children with learning difficulties showed significantly lower FIQ scores than controls (P<0.00001; Type of learning difficulty and gender differences were evaluated using a fixed-effects model (I² = 0%. The sites and purposes of the studies evaluated here were taken into account, but the reasons of heterogeneity could not be eliminated; The sum IQ of all the subgroups showed considerable heterogeneity (I² = 76.5%. The sub-measurement score of document A showed moderate heterogeneity among all documents, and AB, B, and E showed considerable heterogeneity, which was used in a random effect model. Individuals with learning difficulties showed heterogeneity as well. There was a moderate delay in the first three items (-0.5 to -0.9, and a much more pronounced delay in the latter three items (-1.4 to -1.6. CONCLUSION: In the Chinese mainland, the level of fluid intelligence of children with learning difficulties was lower than that of normal children. Delayed development in sub-items of C, D
Full Text Available The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor’s infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.
Villaverde, Monica; Perez, David; Moreno, Felix
The emergence of new horizons in the field of travel assistant management leads to the development of cutting-edge systems focused on improving the existing ones. Moreover, new opportunities are being also presented since systems trend to be more reliable and autonomous. In this paper, a self-learning embedded system for object identification based on adaptive-cooperative dynamic approaches is presented for intelligent sensor's infrastructures. The proposed system is able to detect and identify moving objects using a dynamic decision tree. Consequently, it combines machine learning algorithms and cooperative strategies in order to make the system more adaptive to changing environments. Therefore, the proposed system may be very useful for many applications like shadow tolls since several types of vehicles may be distinguished, parking optimization systems, improved traffic conditions systems, etc.
Shariati, Azadeh; Meghdari, Ali; Shariati, Parham
In this research an intelligent emotional learning controller, Takagi- Sugeno- Kang (TSK) is applied to govern the dynamics of a novel Ionic-Polymer Metal Composite (IPMC) actuated manipulator. Ionic-Polymer Metal Composites are active actuators that show very large deformation in existence of low applied voltage. In this research, a new IPMC actuator is considered and applied to a 2-dof miniature manipulator. This manipulator is designed for miniature tasks. The control system consists of a set of neurofuzzy controller whose parameters are adapted according to the emotional learning rules, and a critic with task to assess the present situation resulted from the applied control action in terms of satisfactory achievement of the control goals and provides the emotional signal (the stress). The controller modifies its characteristics so that the critic's stress decreased.
Bråten, Ivar; Strømsø, Helge I
More empirical work is needed to examine the dimensionality of personal epistemology and relations between those dimensions and motivational and strategic components of self-regulated learning. In particular, there is great need to investigate personal epistemology and its relation to self-regulated learning across cultures and academic contexts. Because the demarcation between personal epistemology and implicit theories of intelligence has been questioned, dimensions of personal epistemology should also be studied in relation to implicit theories of intelligence. The primary aim was to examine the dimensionality of personal epistemology and the relation between those dimensions and implicit theories of intelligence in the cultural context of Norwegian postsecondary education. A secondary aim was to examine the relative contribution of epistemological beliefs and theories of intelligence to motivational and strategic components of self-regulated learning in different academic contexts within that culture. The first sample included 178 business administration students in a traditional transmission-oriented instructional context; the second, 108 student teachers in an innovative pedagogical context. The dimensionality of the Schommer Epistemological Questionnaire was examined through factor analyses, and the resulting dimensions were examined in relation to implicit theories of intelligence. We performed multiple regression analyses, separately for the two academic contexts, to try to predict motivational (i.e. self-efficacy beliefs, mastery goal orientation, and interest) and strategic (i.e. self-regulatory strategy use) components of self-regulated learning with epistemological beliefs and implicit theories of intelligence. Considerable cross-cultural generalizability was found for the dimensionality of personal epistemology. Moreover, the dimensions of personal epistemology seemed to represent constructs separate from the construct of implicit theories of
Zhang, Jing; Song, Yanlin; Xia, Fan; Zhu, Chenjing; Zhang, Yingying; Song, Wenpeng; Xu, Jianguo; Ma, Xuelei
Frozen section is widely used for intraoperative pathological diagnosis (IOPD), which is essential for intraoperative decision making. However, frozen section suffers from some drawbacks, such as time consuming and high misdiagnosis rate. Recently, artificial intelligence (AI) with deep learning technology has shown bright future in medicine. We hypothesize that AI with deep learning technology could help IOPD, with a computer trained by a dataset of intraoperative lesion images. Evidences supporting our hypothesis included the successful use of AI with deep learning technology in diagnosing skin cancer, and the developed method of deep-learning algorithm. Large size of the training dataset is critical to increase the diagnostic accuracy. The performance of the trained machine could be tested by new images before clinical use. Real-time diagnosis, easy to use and potential high accuracy were the advantages of AI for IOPD. In sum, AI with deep learning technology is a promising method to help rapid and accurate IOPD. Copyright © 2017 Elsevier Ltd. All rights reserved.
Liu, Hui; Li, Yingzi; Zhang, Yingxu; Chen, Yifu; Song, Zihang; Wang, Zhenyu; Zhang, Suoxin; Qian, Jianqiang
Proportional-integral-derivative (PID) parameters play a vital role in the imaging process of an atomic force microscope (AFM). Traditional parameter tuning methods require a lot of manpower and it is difficult to set PID parameters in unattended working environments. In this manuscript, an intelligent tuning method of PID parameters based on iterative learning control is proposed to self-adjust PID parameters of the AFM according to the sample topography. This method gets enough information about the output signals of PID controller and tracking error, which will be used to calculate the proper PID parameters, by repeated line scanning until convergence before normal scanning to learn the topography. Subsequently, the appropriate PID parameters are obtained by fitting method and then applied to the normal scanning process. The feasibility of the method is demonstrated by the convergence analysis. Simulations and experimental results indicate that the proposed method can intelligently tune PID parameters of the AFM for imaging different topographies and thus achieve good tracking performance. Copyright © 2017 Elsevier Ltd. All rights reserved.
Liang, J.; Du, R.
This paper presents the design of an intelligent comfort control system by combining the human learning and minimum power control strategies for the heating, ventilating and air conditioning (HVAC) system. In the system, the predicted mean vote (PMV) is adopted as the control objective to improve indoor comfort level by considering six comfort related variables, whilst a direct neural network controller is designed to overcome the nonlinear feature of the PMV calculation for better performance. To achieve the highest comfort level for the specific user, a human learning strategy is designed to tune the user's comfort zone, and then, a VAV and minimum power control strategy is proposed to minimize the energy consumption further. In order to validate the system design, a series of computer simulations are performed based on a derived HVAC and thermal space model. The simulation results confirm the design of the intelligent comfort control system. In comparison to the conventional temperature controller, this system can provide a higher comfort level and better system performance, so it has great potential for HVAC applications in the future
Rey-Lopez, Marta; Brusilovsky, Peter; Meccawy, Maram; Diaz-Redondo, Rebeca; Fernandez-Vilas, Ana; Ashman, Helen
Current e-learning standardization initiatives have put much effort into easing interoperability between systems and the reusability of contents. For this to be possible, one of the most relevant areas is the definition of a run-time environment, which allows Learning Management Systems to launch, track and communicate with learning objects.…
Veermans, K.H.; de Jong, Anthonius J.M.; van Joolingen, Wouter
Providing learners with computer-generated feedback on their learning process in simulationbased discovery environments cannot be based on a detailed model of the learning process due to the “open” character of discovery learning. This paper describes a method for generating adaptive feedback for
Ng, Roxana; Shan, Hongxia
Critiques of lifelong learning have focused on the neo-liberal underpinning of state policy, where individuals are expected to take responsibility for meeting the needs of changing labour market conditions in the post-Fordist economy. We treat lifelong learning as an "ideological frame" that (re)shapes how people see and understand…
Antinah; Kusmayadi, T. A.; Husodo, B.
This study aimed to determine the effect of learning model on student achievement in terms of interpersonal intelligence. The compared learning models are LC7E and Direct learning model. This type of research is a quasi-experimental with 2x3 factorial design. The population in this study is a Grade XI student of Wonogiri Vocational Schools. The sample selection had done by stratified cluster random sampling. Data collection technique used questionnaires, documentation and tests. The data analysis technique used two different unequal cell variance analysis which previously conducted prerequisite analysis for balance test, normality test and homogeneity test. he conclusions of this research are: 1) student learning achievement of mathematics given by LC7E learning model is better when compared with direct learning; 2) Mathematics learning achievement of students who have a high level of interpersonal intelligence is better than students with interpersonal intelligence in medium and low level. Students’ mathematics learning achievement with interpersonal level of intelligence is better than those with low interpersonal intelligence on linear programming; 3) LC7E learning model resulted better on mathematics learning achievement compared with direct learning model for each category of students’ interpersonal intelligence level on linear program material.
Antinah; Kusmayadi, T. A.; Husodo, B.
This study aims to determine the effect of learning model on student achievement in terms of interpersonal intelligence. The compared learning models are LC7E and Direct learning model. This type of research is a quasi-experimental with 2x3 factorial design. The population in this study is a Grade XI student of Wonogiri Vocational Schools. The sample selection had done by stratified cluster random sampling. Data collection technique used questionnaires, documentation and tests. The data analysis technique used two different unequal cell variance analysis which previously conducted prerequisite analysis for balance test, normality test and homogeneity test. he conclusions of this research are: 1) student learning achievement of mathematics given by LC7E learning model is better when compared with direct learning; 2) Mathematics learning achievement of students who have a high level of interpersonal intelligence is better than students with interpersonal intelligence in medium and low level. Students' mathematics learning achievement with interpersonal level of intelligence is better than those with low interpersonal intelligence on linear programming; 3) LC7E learning model resulted better on mathematics learning achievement compared with direct learning model for each category of students’ interpersonal intelligence level on linear program material.
Full Text Available The aim of the research was to investigate the effects of multiple intelligences supported project-based learning and traditional foreign language-teaching environment on students' achievement and their attitude towards English lesson. The research was carried out in 2009 – 2010 education-instruction year in Karatli Sehit Sahin Yilmaz Elementary School, Nigde, Turkey. Totally 50 students in two different classes in the 5th grade of this school participated in the study. The results of the research showed a significant difference between the attitude scores of the experiment group and the control group. It was also found out that the multiple intelligences approach activities were more effective in thepositive development of the students’ attitudes. At the end of the research, it is revealed that the students who are educated by multiple intelligences supported project-based learning method are more successful and have a higher motivation level than the studentswho are educated by the traditional instructional methods.
Davila, Liv Thorstensson
This study analyzes the goals and realities of four educated, working, adult Latina, English as a Second language (ESL) students living in North Carolina, a region seeing particularly intense migration of Latino immigrants. The study conceptually frames adjustment issues confronted by these Latina immigrants in terms of gender, language,…
Bas, Gökhan; Beyhan, Ömer
The aim of the research was to investigate the effects of multiple intelligences supported project-based learning and traditional foreign language-teaching environment on students' achievement and their attitude towards English lesson. The research was carried out in 2009-2010 education-instruction year in Karatli Sehit Sahin Yilmaz Elementary…
The relationship between intelligence, language, and learning is a challenging field of study. One way to study how this relationship occurs and works is to investigate the perceptions of advanced language learners. Therefore, this paper reports a study that was conducted to explore 160 pre-service English language teachers' perceptions about…
Bringula, Rex P.; Basa, Roselle S.; Dela Cruz, Cecilio; Rodrigo, Ma. Mercedes T.
This study attempted to determine the influence of prior knowledge in mathematics of students on learner-interface interactions in a learning-by-teaching intelligent tutoring system. One hundred thirty-nine high school students answered a pretest (i.e., the prior knowledge in mathematics) and a posttest. In between the pretest and posttest, they…
Perry, Chris; Ball, Ian
This study explores issues in teacher education that increase our understanding of, and response to, the individual differences displayed by learners. A large undergraduate teacher education cohort provided evidence of the range and distribution of preferences in learning styles, psychological types and multiple intelligences. This information…
Danner, Daniel; Hagemann, Dirk; Schankin, Andrea; Hager, Marieke; Funke, Joachim
The present study investigated cognitive performance measures beyond IQ. In particular, we investigated the psychometric properties of dynamic decision making variables and implicit learning variables and their relation with general intelligence and professional success. N = 173 employees from different companies and occupational groups completed…
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
Steenbergen-Hu, Saiying; Cooper, Harris
In this study, we meta-analyzed empirical research of the effectiveness of intelligent tutoring systems (ITS) on K-12 students' mathematical learning. A total of 26 reports containing 34 independent samples met study inclusion criteria. The reports appeared between 1997 and 2010. The majority of included studies compared the effectiveness of ITS…
Beasley, Robert; Bryant, Nathan L.; Dodson, Phillip T.; Entwistle, Kevin C.
The purpose of this study was to investigate the effects of textisms (i.e., abbreviated spellings, acronyms, and other shorthand notations) on learning, study time, and instructional perceptions in an online artificial intelligence instructional module. The independent variable in this investigation was experimental condition. For the control…
Miguel A. Santos
Full Text Available The international assessment studies of key competences, such as the PISA report of the OECD, have revealed that the academic performance of Spanish students is significantly below the OECD average; in addition, it has also been confirmed that the results of immigrant students are consistently lower than those of their native counterparts. Given the context, the first objective of this work is to observe the variables (support, control, school satisfaction and learning environment which distinguish between native and immigrant students with high and low academic performance; the second objective is to check, by comparing the native and immigrant students with high and low performance and separating the two levels, to find out which of the selected variables clearly differentiate the two groups. To this end, a sample of 1359 students was used (79.8% native students and 20.2% immigrant students of Latin American origin, who were enrolled in the 5th and 6th year of Primary Education (aged 10-11 years and in the 1st and 2nd year of Secondary Education (aged 12-13 years. The origin and the fact of being a retained student or not were estimated as independent variables, whereas their responses to the variables of perceived family support and control (paternal and maternal separately, their school satisfaction and assessment of the learning environment were taken into account as dependent variables. Considering that the reliability of the scales used is adequate, along with the optimal factorization in a series of coherent constructs, it was revealed that the main differences consisted of individual dimensions (perception of family support and control and, to a lesser extent, of dimensions related to the context (assessment of the school and learning environments. Given the results obtained, our intention is to provide solid evidence that would facilitate the design of family involvement programs, helping to improve students' educational performance.
Bahrami, Mohammad Amin; Kiani, Mohammad Mehdi; Montazeralfaraj, Raziye; Zadeh, Hossein Fallah; Zadeh, Morteza Mohammad
Organizational learning is defined as creating, absorbing, retaining, transferring, and application of knowledge within an organization. This article aims to examine the mediating role of organizational learning in the relationship of organizational intelligence and organizational agility. This analytical and cross-sectional study was conducted in 2015 at four teaching hospitals of Yazd city, Iran. A total of 370 administrative and medical staff contributed to the study. We used stratified-random method for sampling. Required data were gathered using three valid questionnaires including Alberkht (2003) organizational intelligence, Neefe (2001) organizational learning, and Sharifi and Zhang (1999) organizational agility questionnaires. Data analysis was done through R and SPSS 18 statistical software. The results showed that organizational learning acts as a mediator in the relationship of organizational intelligence and organizational agility (path coefficient = 0.943). Also, organizational learning has a statistical relationship with organizational agility (path coefficient = 0.382). Our findings suggest that the improvement of organizational learning abilities can affect an organization's agility which is crucial for its survival.
Takahashi, Hidenori; Tampo, Hironobu; Arai, Yusuke; Inoue, Yuji; Kawashima, Hidetoshi
Disease staging involves the assessment of disease severity or progression and is used for treatment selection. In diabetic retinopathy, disease staging using a wide area is more desirable than that using a limited area. We investigated if deep learning artificial intelligence (AI) could be used to grade diabetic retinopathy and determine treatment and prognosis. The retrospective study analyzed 9,939 posterior pole photographs of 2,740 patients with diabetes. Nonmydriatic 45° field color fundus photographs were taken of four fields in each eye annually at Jichi Medical University between May 2011 and June 2015. A modified fully randomly initialized GoogLeNet deep learning neural network was trained on 95% of the photographs using manual modified Davis grading of three additional adjacent photographs. We graded 4,709 of the 9,939 posterior pole fundus photographs using real prognoses. In addition, 95% of the photographs were learned by the modified GoogLeNet. Main outcome measures were prevalence and bias-adjusted Fleiss' kappa (PABAK) of AI staging of the remaining 5% of the photographs. The PABAK to modified Davis grading was 0.64 (accuracy, 81%; correct answer in 402 of 496 photographs). The PABAK to real prognosis grading was 0.37 (accuracy, 96%). We propose a novel AI disease-staging system for grading diabetic retinopathy that involves a retinal area not typically visualized on fundoscopy and another AI that directly suggests treatments and determines prognoses.
Du, Junping; Li, Hongbo; Zhang, Weicun; CISC’15
This book presents selected research papers from the 2015 Chinese Intelligent Systems Conference (CISC’15), held in Yangzhou, China. The topics covered include multi-agent systems, evolutionary computation, artificial intelligence, complex systems, computation intelligence and soft computing, intelligent control, advanced control technology, robotics and applications, intelligent information processing, iterative learning control, and machine learning. Engineers and researchers from academia, industry and the government can gain valuable insights into solutions combining ideas from multiple disciplines in the field of intelligent systems.
Maxwell, Andrew; Li, Runzhi; Yang, Bei; Weng, Heng; Ou, Aihua; Hong, Huixiao; Zhou, Zhaoxian; Gong, Ping; Zhang, Chaoyang
Multi-label classification of data remains to be a challenging problem. Because of the complexity of the data, it is sometimes difficult to infer information about classes that are not mutually exclusive. For medical data, patients could have symptoms of multiple different diseases at the same time and it is important to develop tools that help to identify problems early. Intelligent health risk prediction models built with deep learning architectures offer a powerful tool for physicians to identify patterns in patient data that indicate risks associated with certain types of chronic diseases. Physical examination records of 110,300 anonymous patients were used to predict diabetes, hypertension, fatty liver, a combination of these three chronic diseases, and the absence of disease (8 classes in total). The dataset was split into training (90%) and testing (10%) sub-datasets. Ten-fold cross validation was used to evaluate prediction accuracy with metrics such as precision, recall, and F-score. Deep Learning (DL) architectures were compared with standard and state-of-the-art multi-label classification methods. Preliminary results suggest that Deep Neural Networks (DNN), a DL architecture, when applied to multi-label classification of chronic diseases, produced accuracy that was comparable to that of common methods such as Support Vector Machines. We have implemented DNNs to handle both problem transformation and algorithm adaption type multi-label methods and compare both to see which is preferable. Deep Learning architectures have the potential of inferring more information about the patterns of physical examination data than common classification methods. The advanced techniques of Deep Learning can be used to identify the significance of different features from physical examination data as well as to learn the contributions of each feature that impact a patient's risk for chronic diseases. However, accurate prediction of chronic disease risks remains a challenging
Zuhrie, M. S.; Basuki, I.; Asto B, I. G. P.; Anifah, L.
The focus of the research is the teaching module which incorporates manufacturing, planning mechanical designing, controlling system through microprocessor technology and maneuverability of the robot. Computer interactive and computer-assisted learning is strategies that emphasize the use of computers and learning aids (computer assisted learning) in teaching and learning activity. This research applied the 4-D model research and development. The model is suggested by Thiagarajan, et.al (1974). 4-D Model consists of four stages: Define Stage, Design Stage, Develop Stage, and Disseminate Stage. This research was conducted by applying the research design development with an objective to produce a tool of learning in the form of intelligent robot modules and kit based on Computer Interactive Learning and Computer Assisted Learning. From the data of the Indonesia Robot Contest during the period of 2009-2015, it can be seen that the modules that have been developed confirm the fourth stage of the research methods of development; disseminate method. The modules which have been developed for students guide students to produce Intelligent Robot Tool for Teaching Based on Computer Interactive Learning and Computer Assisted Learning. Results of students’ responses also showed a positive feedback to relate to the module of robotics and computer-based interactive learning.
Roy V., Manoj; Ghosh, Chimoy Kumar
In recent times Information and Communication Technology (ICT) has been able to make inroads into the ways information is disseminated among those involved in direct farming and farming related enterprises. This paper arose from a two-year study of the KissanKerala, the e-learning project underway in Kerala, a small state in India. It is more…
between technical and artistic minded students is, however, increased once the students reach the sixth semester. The complex algorithms of the artificial intelligence course seemed to demotivate the artistic minded students even before the course began. This paper will present the extensive changes made...... to the sixth semester artificial intelligence programming course, in order to provide a highly motivating direct visual feedback, and thereby remove the steep initial learning curve for artistic minded students. The framework was developed with close dialog to both the game industry and experienced master...
Lai, Ying-Hui; Tsao, Yu; Lu, Xugang; Chen, Fei; Su, Yu-Ting; Chen, Kuang-Chao; Chen, Yu-Hsuan; Chen, Li-Ching; Po-Hung Li, Lieber; Lee, Chin-Hui
We investigate the clinical effectiveness of a novel deep learning-based noise reduction (NR) approach under noisy conditions with challenging noise types at low signal to noise ratio (SNR) levels for Mandarin-speaking cochlear implant (CI) recipients. The deep learning-based NR approach used in this study consists of two modules: noise classifier (NC) and deep denoising autoencoder (DDAE), thus termed (NC + DDAE). In a series of comprehensive experiments, we conduct qualitative and quantitative analyses on the NC module and the overall NC + DDAE approach. Moreover, we evaluate the speech recognition performance of the NC + DDAE NR and classical single-microphone NR approaches for Mandarin-speaking CI recipients under different noisy conditions. The testing set contains Mandarin sentences corrupted by two types of maskers, two-talker babble noise, and a construction jackhammer noise, at 0 and 5 dB SNR levels. Two conventional NR techniques and the proposed deep learning-based approach are used to process the noisy utterances. We qualitatively compare the NR approaches by the amplitude envelope and spectrogram plots of the processed utterances. Quantitative objective measures include (1) normalized covariance measure to test the intelligibility of the utterances processed by each of the NR approaches; and (2) speech recognition tests conducted by nine Mandarin-speaking CI recipients. These nine CI recipients use their own clinical speech processors during testing. The experimental results of objective evaluation and listening test indicate that under challenging listening conditions, the proposed NC + DDAE NR approach yields higher intelligibility scores than the two compared classical NR techniques, under both matched and mismatched training-testing conditions. When compared to the two well-known conventional NR techniques under challenging listening condition, the proposed NC + DDAE NR approach has superior noise suppression capabilities and gives less distortion
Santos, Miguel A; Godás, Agustín; Ferraces, María J; Lorenzo, Mar
The international assessment studies of key competences, such as the PISA report of the OECD, have revealed that the academic performance of Spanish students is significantly below the OECD average. In addition, it has also been confirmed that the results of immigrant students are consistently lower than those of their native counterparts. Given the context, the first objective of this work is to observe the variables (support, control, school satisfaction, and learning environment) which distinguish between retained and non-retained native and immigrant students. The second objective is to check, by comparing the retained and non-retained native and immigrant students and separating the two levels, in order to find out which of the selected variables clearly differentiate the two groups. A sample of 1359 students was used (79.8% native students and 20.2% immigrant students of Latin American origin), who were enrolled in the 5th and 6th year of Primary Education (aged 10-11 years) and in the 1st and 2nd year of Secondary Education (aged 12-13 years). The measurement scales, which undergo a psychometric analysis in the current work, have been developed in a previous research study (Lorenzo et al., 2009). The construct validity and reliability are reported (obtaining alpha indices between 0.705 and 0.787). Subsequently, and depending on the results of this analysis, inferential analyses are performed, using as independent variables the ethno-cultural origin and being retained or not, whereas, as dependent variables, the indices referring to students' perception of family support and control, as well as the assessment of the school and learning environment. Among other results, the Group × Being retained/Not being retained [ F (1, 1315) = 4.67, p family support. Given the results obtained, our intention is to provide solid evidence that would facilitate the design of family involvement programs, helping to improve students' educational performance.
Aarts, E.H.L.; Korst, J.H.M.; Verhaegh, W.F.J.; Verhaegh, W.F.J.; Aarts, E.H.L.; Korst, J.H.M.
In this chapter, we discuss the new paradigm for user-centered computing known as ambient intelligence and its relation with methods and techniques from the field of computational intelligence, including problem solving, machine learning, and expert systems.
Aparicio, Fernando; Morales-Botello, María Luz; Rubio, Margarita; Hernando, Asunción; Muñoz, Rafael; López-Fernández, Hugo; Glez-Peña, Daniel; Fdez-Riverola, Florentino; de la Villa, Manuel; Maña, Manuel; Gachet, Diego; Buenaga, Manuel de
Student participation and the use of active methodologies in classroom learning are being increasingly emphasized. The use of intelligent systems can be of great help when designing and developing these types of activities. Recently, emerging disciplines such as 'educational data mining' and 'learning analytics and knowledge' have provided clear examples of the importance of the use of artificial intelligence techniques in education. The main objective of this study was to gather expert opinions regarding the benefits of using complementary methods that are supported by intelligent systems, specifically, by intelligent information access systems, when processing texts written in natural language and the benefits of using these methods as companion tools to the learning activities that are employed by biomedical and health sciences teachers. Eleven teachers of degree courses who belonged to the Faculties of Biomedical Sciences (BS) and Health Sciences (HS) of a Spanish university in Madrid were individually interviewed. These interviews were conducted using a mixed methods questionnaire that included 66 predefined close-ended and open-ended questions. In our study, three intelligent information access systems (i.e., BioAnnote, CLEiM and MedCMap) were successfully used to evaluate the teacher's perceptions regarding the utility of these systems and their different methods in learning activities. All teachers reported using active learning methods in the classroom, most of which were computer programs that were used for initially designing and later executing learning activities. All teachers used case-based learning methods in the classroom, with a specific emphasis on case reports written in Spanish and/or English. In general, few or none of the teachers were familiar with the technical terms related to the technologies used for these activities such as "intelligent systems" or "concept/mental maps". However, they clearly realized the potential applicability of such
Jain, G. Panka; Gurupur, Varadraj P.; Schroeder, Jennifer L.; Faulkenberry, Eileen D.
In this paper, we describe a tool coined as artificial intelligence-based student learning evaluation tool (AISLE). The main purpose of this tool is to improve the use of artificial intelligence techniques in evaluating a student's understanding of a particular topic of study using concept maps. Here, we calculate the probability distribution of…
The present investigation explored the stability of scores on the Wechsler Intelligence Scale for Children-IV (WISC-IV) over approximately a three-year period. Previous research has suggested that some children with Learning Disabilities (LD) do not demonstrate long-term stability of intelligence. Legally, school districts are no longer required…
Sahli, Sanem; Laszig, Roland; Aschendorff, Antje; Kroeger, Stefanie; Wesarg, Thomas; Belgin, Erol
The aim of the study is to determinate the using dominant multiple intelligence types and compare the learning preferences of Turkish cochlear implanted children aged four to ten in Turkey and Germany according to Theory of multiple intelligence. The study has been conducted on a total of 80 children and four groups in Freiburg/Germany and Ankara/Turkey. The applications have been done in University of Freiburg, Cochlear Implant Center in Germany, and University of Hacettepe, ENT Department, Audiology and Speech Pathology Section in Turkey. In this study, the data have been collected by means of General Information Form and Cochlear Implant Information Form applied to parents. To determine the dominant multiple intelligence types of children, the TIMI (Teele Inventory of Multiple Intelligences) which was developed by Sue Teele have been used. The study results exposed that there was not a statistically significant difference on dominant intelligence areas and averages of scores of multiple intelligence types in control groups (p>0.05). Although, the dominant intelligence areas were different (except for first dominant intelligence) in cochlear implanted children in Turkey and Germany, there was not a statistically significant difference on averages of scores of dominant multiple intelligence types. Every hearing impaired child who started training, should be evaluated in terms of multiple intelligence areas and identified strengths and weaknesses. Multiple intelligence activities should be used in their educational programs. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Paula MARCHENA CRUZ
Full Text Available Currently, the Spanish educational system focuses its attention on the development of priority subjects such as language and mathematics versus other secondary such as music (Palacios, 2006, without considering numerous neuropsychological research that provides new theories of mind and learning that can positively influence the transformation of current educational models (Martin-Lobo, 2015. This research aims to determine the relation between musical intelligence, bodily-kinesthetic intelligence, intelligence visuospatial and motor creativity in a sample among 5 years old students from the last year of Early Childhood Education. The instrument used to assess the three intelligences, based on Gardner’s theory, was the Multiple Intelligences questionnaire for children of pre-school age (Prieto and Ballester, 2003; for the evaluation of motor creativity was used Test of Creative Thinking in Action and Movement (Torrance, Reisman and Floyd, 1981. A descriptive and correlational statistical analysis (using the Pearson correlation index applying the Microsoft Excel program along with the supplement known as Ezanalyze. The results indicated no significant relationship between musical intelligence and motor creativity (p = 0.988; the visuospatial intelligence and motor creativity (p = 0.992; and the bodily-kinesthetic intelligence and motor creativity (p = 0.636. Although there was significant relation between the musical and visuospatial intelligence (p = 0.000; the musical and bodily-kinesthetic intelligence (p = 0.000; and the bodily-kinesthetic and visuospatial intelligence (p = 0.025.
Wang, Yue; Yu, Lei; Fu, Jianming; Fang, Qiang
In order to realize an individualized and specialized rehabilitation assessment of remoteness and intelligence, we set up a remote intelligent assessment system of upper limb movement function of post-stroke patients during rehabilitation. By using the remote rehabilitation training sensors and client data sampling software, we collected and uploaded the gesture data from a patient's forearm and upper arm during rehabilitation training to database of the server. Then a remote intelligent assessment system, which had been developed based on the extreme learning machine (ELM) algorithm and Brunnstrom stage assessment standard, was used to evaluate the gesture data. To evaluate the reliability of the proposed method, a group of 23 stroke patients, whose upper limb movement functions were in different recovery stages, and 4 healthy people, whose upper limb movement functions were normal, were recruited to finish the same training task. The results showed that, compared to that of the experienced rehabilitation expert who used the Brunnstrom stage standard table, the accuracy of the proposed remote Brunnstrom intelligent assessment system can reach a higher level, as 92.1%. The practical effects of surgery have proved that the proposed system could realize the intelligent assessment of upper limb movement function of post-stroke patients remotely, and it could also make the rehabilitation of the post-stroke patients at home or in a community care center possible.
Santos, Miguel A.; Godás, Agustín; Ferraces, María J.; Lorenzo, Mar
The international assessment studies of key competences, such as the PISA report of the OECD, have revealed that the academic performance of Spanish students is significantly below the OECD average. In addition, it has also been confirmed that the results of immigrant students are consistently lower than those of their native counterparts. Given the context, the first objective of this work is to observe the variables (support, control, school satisfaction, and learning environment) which distinguish between retained and non-retained native and immigrant students. The second objective is to check, by comparing the retained and non-retained native and immigrant students and separating the two levels, in order to find out which of the selected variables clearly differentiate the two groups. A sample of 1359 students was used (79.8% native students and 20.2% immigrant students of Latin American origin), who were enrolled in the 5th and 6th year of Primary Education (aged 10–11 years) and in the 1st and 2nd year of Secondary Education (aged 12–13 years). The measurement scales, which undergo a psychometric analysis in the current work, have been developed in a previous research study (Lorenzo et al., 2009). The construct validity and reliability are reported (obtaining alpha indices between 0.705 and 0.787). Subsequently, and depending on the results of this analysis, inferential analyses are performed, using as independent variables the ethno-cultural origin and being retained or not, whereas, as dependent variables, the indices referring to students' perception of family support and control, as well as the assessment of the school and learning environment. Among other results, the Group × Being retained/Not being retained [F(1, 1315) = 4.67, p < 0.01] interaction should be pointed out, indicating that native non-retained subjects perceive more control than immigrants, as well as the Group × Being retained/Not being retained [F(1, 1200) = 5.49, p < 0
Muñoz, Diana C; Ortiz, Alexandra; González, Carolina; López, Diego M; Blobel, Bernd
Current e-learning systems are still inadequate to support the level of interaction, personalization and engagement demanded by clinicians, care givers, and the patient themselves. For effective e-learning to be delivered in the health context, collaboration between pedagogy and technology is required. Furthermore, e-learning systems should be flexible enough to be adapted to the students' needs, evaluated regularly, easy to use and maintain and provide students' feedback, guidelines and supporting material in different formats. This paper presents the implementation of an Intelligent Tutoring System (SIAS-ITS), and its evaluation compared to a traditional virtual learning platform (Moodle). The evaluation was carried out as a case study, in which the participants were separated in two groups, each group attending a virtual course on the WHO Integrated Management of Childhood Illness (IMCI) strategy supported by one of the two e-learning platforms. The evaluation demonstrated that the participants' knowledge level, pedagogical strategies used, learning efficiency and systems' usability were improved using the Intelligent Tutoring System.
Myneni, Lakshman Sundeep
Students in middle school science classes have difficulty mastering physics concepts such as energy and work, taught in the context of simple machines. Moreover, students' naive conceptions of physics often remain unchanged after completing a science class. To address this problem, I developed an intelligent tutoring system, called the Virtual Physics System (ViPS), which coaches students through problem solving with one class of simple machines, pulley systems. The tutor uses a unique cognitive based approach to teaching simple machines, and includes innovations in three areas. (1) It employs a teaching strategy that focuses on highlighting links among concepts of the domain that are essential for conceptual understanding yet are seldom learned by students. (2) Concepts are taught through a combination of effective human tutoring techniques (e.g., hinting) and simulations. (3) For each student, the system identifies which misconceptions he or she has, from a common set of student misconceptions gathered from domain experts, and tailors tutoring to match the correct line of scientific reasoning regarding the misconceptions. ViPS was implemented as a platform on which students can design and simulate pulley system experiments, integrated with a constraint-based tutor that intervenes when students make errors during problem solving to teach them and to help them. ViPS has a web-based client-server architecture, and has been implemented using Java technologies. ViPS is different from existing physics simulations and tutoring systems due to several original features. (1). It is the first system to integrate a simulation based virtual experimentation platform with an intelligent tutoring component. (2) It uses a novel approach, based on Bayesian networks, to help students construct correct pulley systems for experimental simulation. (3) It identifies student misconceptions based on a novel decision tree applied to student pretest scores, and tailors tutoring to
Kinch, Martin W.; Melis, Wim J.C.; Keates, Simeon
This paper will consider the current state of Machine Learning for Artificial Intelligence, more specifically for applications, such as: Speech Recognition, Game Playing and Image Processing. The artificial world tends to make limited use of context in comparison to what currently happens in human life, while it would benefit from improvements in this area. Additionally, the process of transferring knowledge between application domains is another important area where artificial system can imp...
Dunleavy M, Dede C. Augmented reality teaching and learning. Handbook of research on educational communications and technology . New York (NY): Springer...taxonomy of mixed reality visual displays. IEICE Transactions on Information and Systems. 1994;77(12):1321–1329. Noordzij ML, Scholten P, Laroy-Noordzij...Generalized Intelligent Framework for Tutoring (GIFT) and Augmented REality Sandtable (ARES) by Michael W Boyce, Ramsamooj J Reyes, Deeja E Cruz, Charles
Liliawati, W.; Utama, J. A.; Ramalis, T. R.; Rochman, A. A.
Validation of the Earth and Space Science learning the material in the chapter of the Earth's Protector based on experts (media & content expert and practitioners) and junior high school students' responses are presented. The data came from the development phase of the 4D method (Define, Design, Develop, Dissemination) which consist of two steps: expert appraisal and developmental testing. The instrument employed is rubric of suitability among the book contents with multiple intelligences activities, character education, a standard of book assessment, a questionnaires and close procedure. The appropriateness of the book contents with multiple intelligences, character education and standard of book assessment is in a good category. Meanwhile, students who used the book in their learning process gave a highly positive response; the book was easy to be understood. In general, the result of cloze procedure indicates high readability of the book. As our conclusion is the book chapter of the Earth's Protector can be used as a learning material accommodating students’ multiple intelligences and character internalization.
Fu, Szu-Wei; Li, Pei-Chun; Lai, Ying-Hui; Yang, Cheng-Chien; Hsieh, Li-Chun; Tsao, Yu
Objective: This paper focuses on machine learning based voice conversion (VC) techniques for improving the speech intelligibility of surgical patients who have had parts of their articulators removed. Because of the removal of parts of the articulator, a patient's speech may be distorted and difficult to understand. To overcome this problem, VC methods can be applied to convert the distorted speech such that it is clear and more intelligible. To design an effective VC method, two key points must be considered: 1) the amount of training data may be limited (because speaking for a long time is usually difficult for postoperative patients); 2) rapid conversion is desirable (for better communication). Methods: We propose a novel joint dictionary learning based non-negative matrix factorization (JD-NMF) algorithm. Compared to conventional VC techniques, JD-NMF can perform VC efficiently and effectively with only a small amount of training data. Results: The experimental results demonstrate that the proposed JD-NMF method not only achieves notably higher short-time objective intelligibility (STOI) scores (a standardized objective intelligibility evaluation metric) than those obtained using the original unconverted speech but is also significantly more efficient and effective than a conventional exemplar-based NMF VC method. Conclusion: The proposed JD-NMF method may outperform the state-of-the-art exemplar-based NMF VC method in terms of STOI scores under the desired scenario. Significance: We confirmed the advantages of the proposed joint training criterion for the NMF-based VC. Moreover, we verified that the proposed JD-NMF can effectively improve the speech intelligibility scores of oral surgery patients. Objective: This paper focuses on machine learning based voice conversion (VC) techniques for improving the speech intelligibility of surgical patients who have had parts of their articulators removed. Because of the removal of parts of the articulator, a patient
Cella, C. E.
This manifesto paper will introduce machine listening intelligence, an integrated research framework for acoustic and musical signals modelling, based on signal processing, deep learning and computational musicology.
ARTIFICIAL INTELLIGENCE , GAME THEORY, DECISION MAKING, BIONICS, AUTOMATA, SPEECH RECOGNITION, GEOMETRIC FORMS, LEARNING MACHINES, MATHEMATICAL MODELS, PATTERN RECOGNITION, SERVOMECHANISMS, SIMULATION, BIBLIOGRAPHIES.
Thrall, James H; Li, Xiang; Li, Quanzheng; Cruz, Cinthia; Do, Synho; Dreyer, Keith; Brink, James
Worldwide interest in artificial intelligence (AI) applications, including imaging, is high and growing rapidly, fueled by availability of large datasets ("big data"), substantial advances in computing power, and new deep-learning algorithms. Apart from developing new AI methods per se, there are many opportunities and challenges for the imaging community, including the development of a common nomenclature, better ways to share image data, and standards for validating AI program use across different imaging platforms and patient populations. AI surveillance programs may help radiologists prioritize work lists by identifying suspicious or positive cases for early review. AI programs can be used to extract "radiomic" information from images not discernible by visual inspection, potentially increasing the diagnostic and prognostic value derived from image datasets. Predictions have been made that suggest AI will put radiologists out of business. This issue has been overstated, and it is much more likely that radiologists will beneficially incorporate AI methods into their practices. Current limitations in availability of technical expertise and even computing power will be resolved over time and can also be addressed by remote access solutions. Success for AI in imaging will be measured by value created: increased diagnostic certainty, faster turnaround, better outcomes for patients, and better quality of work life for radiologists. AI offers a new and promising set of methods for analyzing image data. Radiologists will explore these new pathways and are likely to play a leading role in medical applications of AI. Copyright © 2017 American College of Radiology. Published by Elsevier Inc. All rights reserved.
the difficulties that integration practitioners encounter in their attempts. I then highlight how the initial necessity of social spaces that are culturally and linguistically familiar to recent immigrants has, in conjunction with other factors, led to the establishment of at times solidified Russian-language...... fieldwork in socio-economically marginalized neighborhoods of eastern Berlin-Marzahn which are a home to a large number of Russian-speaking immigrants of German origin, I examine these projects’ attempts to construct communal social spaces shared by migrants and local residents. I start by noting...
Gary G. Huang
Full Text Available In this study, I examined academic achievement of immigrant children in the United States, Canada, England, Australia, and New Zealand. Analyzing data from the Third International Mathematics and Science Study (TIMSS, I gauged the performance gaps relating to the generation of immigration and the home language background. I found immigrant children's math and science achievement to be lower than the others only in England, the U.S., and Canada. Non-English language background was found in each country to relate to poor math and science learning and this disadvantage was stronger among native-born childrenpresumably children of indigenous groupsthan among immigrant children. I also examined the school variation in math performance gaps, using hierarchical linear modeling (HLM to each country's data. The patterns in which language- and generation-related math achievement gaps varied between schools are different in the five countries.
Kurpis, Lada Helen; Hunter, James
Business schools can increase their competitiveness by offering students intercultural skills development opportunities integrated into the traditional curricula. This article makes a contribution by proposing an approach to developing students' cultural intelligence that is based on the cultural intelligence (CQ) model, experiential learning…
Full Text Available The aim of the research was to investigate the effects of multiple intelligences supported project-based learning and traditional foreign language-teaching environment on students’ achievement and their attitude towards English lesson. The research was carried out in 2009 – 2010 education-instruction year in Karatli Sehit Sahin Yilmaz Elementary School, Nigde, Turkey. Totally 50 students in two different classes in the 5th grade of this school participated in the study. The results of the research showed a significant difference between the attitude scores of the experiment group and the control group. It was also found out that the multiple intelligences approach activities were more effective in the positive development of the students’ attitudes. At the end of the research, it is revealed that the students who are educated by multiple intelligences supported project-based learning method are more successful and have a higher motivation level than the students who are educated by the traditional instructional methods.
Clarken, Rodney H.
Moral intelligence is newer and less studied than the more established cognitive, emotional and social intelligences, but has great potential to improve our understanding of learning and behavior. Moral intelligence refers to the ability to apply ethical principles to personal goals, values and actions. The construct of moral intelligence consists…
Hilal Seda YILDIZ AYBEK
Full Text Available With the rapid development of Internet technologies, various paradigms of learning can be adapted to e-learning environments. One of these paradigms, Computer-Supported Collaborative Learning (CSCL, can be presented to learners through web-based systems such as LMS while incorporating peer-to-peer (P2P learning, measurement, and evaluation strategies. In this book titled Intelligent Data Analysis for e-Learning Enhancing Security and Trustworthiness in Online Learning Systems, various strategies and applications are presented to ensure trustworthiness in e-learning environments, especially where the CSCL paradigm is adopted. A comprehensive literature review on student security, privacy, and trustworthiness has been presented in a very detailed and comprehensive way. This allowed readers to conceptually prepare for detailed applications in the later parts of the book and case studies at the Universitat Oberta de Catalunya. In addition to the applications that are presented in detail, the approaches and techniques such as Learning Analytics, Educational Data Mining, distributed computing, and massive data processing are shared through detailed applications of how to adapt to the measurement and evaluation applications offered in online learning environments in the context of trustworthiness.
Trevors, Gregory; Duffy, Melissa; Azevedo, Roger
Hypermedia learning environments (HLE) unevenly present new challenges and opportunities to learning processes and outcomes depending on learner characteristics and instructional supports. In this experimental study, we examined how one such HLE--MetaTutor, an intelligent, multi-agent tutoring system designed to scaffold cognitive and…
Recent research suggests that chewing gum may increase alertness and lead to changes in cognitive performance. The present study examined effects of chewing gum on these functions within the context of a single study. This study had four main aims. The first was to examine whether chewing gum improved learning and memory of information in a story. The second aim was to determine whether chewing gum improved test performance on a validated intellectual task (the Alice Heim task). A third aim was to determine whether chewing gum improved performance on short memory tasks (immediate and delayed recall of a list of words, delayed recognition memory, retrieval from semantic memory, and a working memory task). The final aim was to determine whether chewing gum improved mood (alertness, calm and hedonic tone). A cross-over design was used with gum and no-gum sessions being on consecutive weeks. In each week, volunteers attended for two sessions, two days apart. The first session assessed mood, immediate recall of information from a story and performance on short memory tasks. The second session assessed mood, delayed recall of information from a story and performance of an intelligence test (the Alice Heim test). There were no significant effects of chewing gum on any aspect of recall of the story. Chewing gum improved the accuracy of performing the Alice Heim test which confirms the benefits of gum on test performance seen in an earlier study. Chewing gum had no significant effect on the short memory tasks. Chewing gum increased alertness at the end of the test session in both parts of the study. This effect was in the region of a 10% increase and was highly significant (P increases alertness. In contrast, no significant effects of chewing gum were observed in the memory tasks. Intellectual performance was improved in the gum condition. Overall, the results suggest further research on the alerting effects of chewing gum and possible improved test performance in these
MacLean, Hannah Ng On-Nar
Background: Support for the four factor construct validity of the third edition of the Wechsler Adult Intelligence Scale (WAIS-III) has been found in clinical and non clinical populations but some studies question whether more complex models consistent with the concepts of fluid and crystallised intelligence provide a better explanation of the data. The WAIS-III is frequently used in the diagnosis of learning disability, however, previous exploratory factor analysis of data from a population ...
Irwin, J David
Technology has now progressed to the point that intelligent systems are replacing humans in the decision making processes as well as aiding in the solution of very complex problems. In many cases intelligent systems are already outperforming human activities. Artificial neural networks are not only capable of learning how to classify patterns, such images or sequence of events, but they can also effectively model complex nonlinear systems. Their ability to classify sequences of events is probably more popular in industrial applications where there is an inherent need to model nonlinear system
Full Text Available This research analyses the relationship between academic procrastination and emotional intelligence taking also into account the gender and age influence. Psychology undergraduates from the UAB (Universitat Autónoma de Barcelona, Spain and the UIB (Universitat de les Illes Balears, Spain, 45 males and 147 females constituted the sample of the study. Academic procrastination was assessed by means of the D scale (CLARIANA & MARTÍN, 2008 and emotional intelligence by means of the EQ–i (BAR–ON, 1997. The results show that academic procrastination has a significant negative relationship with intrapersonal intelligence, emotional quotient and mood. Moreover, female students scored significantly higher than males both in intrapersonal and interpersonal Intelligence while males obtained higher scores in both stress management and adaptability.
Datta, Shoumen Palit Austin
The elusive quest for intelligence in artificial intelligence prompts us to consider that instituting human-level intelligence in systems may be (still) in the realm of utopia. In about a quarter century, we have witnessed the winter of AI (1990) being transformed and transported to the zenith of tabloid fodder about AI (2015). The discussion at hand is about the elements that constitute the canonical idea of intelligence. The delivery of intelligence as a pay-per-use-service, popping out of ...
Liliawati, W.; Utama, J. A.; Mursydah, L. S.
The purpose of this study is to identify gender-based concept mastery differences of junior high school students after the implementation of multiple intelligences-based integrated earth and space science learning. Pretest-posttest group design was employed to two different classes at one of junior high school on eclipse theme in Tasikmalaya West Java: one class for boys (14 students) and one class of girls (18 students). The two-class received same treatment. The instrument of concepts mastery used in this study was open-ended eight essay questions. Reliability test result of this instrument was 0.9 (category: high) while for validity test results were high and very high category. We used instruments of multiple intelligences identification and learning activity observation sheet for our analysis. The results showed that normalized N-gain of concept mastery for boys and girls were improved, respectively 0.39 and 0.65. Concept mastery for both classes differs significantly. The dominant multiple intelligences for boys were in kinesthetic while girls dominated in the rest of multiple intelligences. Therefor we concluded that the concept mastery was influenced by gender and student’s multiple intelligences. Based on this finding we suggested to considering the factor of gender and students’ multiple intelligences given in the learning activity.
Ghadirli, Hossein Movafegh; Rastgarpour, Maryam
Nowadays, Intelligent Tutoring Systems (ITSs) are so regarded in order to improve education quality via new technologies in this area. One of the problems is that the language of ITSs is different from the learner's. It forces the learners to learn the system language. This paper tries to remove this necessity by using an Automatic Translator Component in system structure like Google Translate API. This system carry out a pre-test and post-test by using Expert System and Jackson Model before ...
Ryoo, Young; Jang, Moon-soo; Bae, Young-Chul
Intelligent systems have been initiated with the attempt to imitate the human brain. People wish to let machines perform intelligent works. Many techniques of intelligent systems are based on artificial intelligence. According to changing and novel requirements, the advanced intelligent systems cover a wide spectrum: big data processing, intelligent control, advanced robotics, artificial intelligence and machine learning. This book focuses on coordinating intelligent systems with highly integrated and foundationally functional components. The book consists of 19 contributions that features social network-based recommender systems, application of fuzzy enforcement, energy visualization, ultrasonic muscular thickness measurement, regional analysis and predictive modeling, analysis of 3D polygon data, blood pressure estimation system, fuzzy human model, fuzzy ultrasonic imaging method, ultrasonic mobile smart technology, pseudo-normal image synthesis, subspace classifier, mobile object tracking, standing-up moti...
Germany has about the same proportion of foreigners in its population as the United States, it is an immigration country. In a way, Germany has let immigration happen, but it did not really have an explicit immigration policy in the past. Now it has to make up its mind on its immigration policy in the future. The paper looks at the experience with immigration in the past, at the integration of foreigners and at the issues of immigration policy.
The constant growth of methods of education that incorporate the Internet into teaching-learning processes has opened up a wide range of opportunities for students across the world to gain entry to undergraduate or graduate degree programs. However, if the enrolling student is a digital immigrant, the chances of success may be limited by the…
Meeuws, Matthias; Pascoal, David; Bermejo, Iñigo; Artaso, Miguel; De Ceulaer, Geert; Govaerts, Paul J
The software application FOX ('Fitting to Outcome eXpert') is an intelligent agent to assist in the programing of cochlear implant (CI) processors. The current version utilizes a mixture of deterministic and probabilistic logic which is able to improve over time through a learning effect. This study aimed at assessing whether this learning capacity yields measurable improvements in speech understanding. A retrospective study was performed on 25 consecutive CI recipients with a median CI use experience of 10 years who came for their annual CI follow-up fitting session. All subjects were assessed by means of speech audiometry with open set monosyllables at 40, 55, 70, and 85 dB SPL in quiet with their home MAP. Other psychoacoustic tests were executed depending on the audiologist's clinical judgment. The home MAP and the corresponding test results were entered into FOX. If FOX suggested to make MAP changes, they were implemented and another speech audiometry was performed with the new MAP. FOX suggested MAP changes in 21 subjects (84%). The within-subject comparison showed a significant median improvement of 10, 3, 1, and 7% at 40, 55, 70, and 85 dB SPL, respectively. All but two subjects showed an instantaneous improvement in their mean speech audiometric score. Persons with long-term CI use, who received a FOX-assisted CI fitting at least 6 months ago, display improved speech understanding after MAP modifications, as recommended by the current version of FOX. This can be explained only by intrinsic improvements in FOX's algorithms, as they have resulted from learning. This learning is an inherent feature of artificial intelligence and it may yield measurable benefit in speech understanding even in long-term CI recipients.
Ruan, Da [The Belgian Nuclear Research Centre (SCK.CEN), Mol (Belgium)]. E-mail: email@example.com
Full text of publication follows: In this lecture, an overview on artificial intelligence (AI) from control to decision making in nuclear engineering will be given mainly based on the 10 years progress of the FLINS forum (Fuzzy Logic and Intelligent Technology in Nuclear Science). Some FLINS concrete examples on nuclear reactor operation, nuclear safeguards information management, and cost estimation under uncertainty for a large nuclear project will be illustrated for the potential use of AI in nuclear engineering. Recommendations and future research directions on AI in nuclear engineering will be suggested from a practical point of view. (author)
Full text of publication follows: In this lecture, an overview on artificial intelligence (AI) from control to decision making in nuclear engineering will be given mainly based on the 10 years progress of the FLINS forum (Fuzzy Logic and Intelligent Technology in Nuclear Science). Some FLINS concrete examples on nuclear reactor operation, nuclear safeguards information management, and cost estimation under uncertainty for a large nuclear project will be illustrated for the potential use of AI in nuclear engineering. Recommendations and future research directions on AI in nuclear engineering will be suggested from a practical point of view. (author)
The purpose of the study was to compare 2D and 3D visual presentation styles, both still frame and animation, on subjects' brain activity measured by the amplitude of EEG alpha wave and on their recall to see if alpha power and recall differ significantly by depth and movement of visual presentation style and by spatial intelligence. In addition,…
Huang, Yueh-Min; Liu, Chien-Hung
One of the key challenges in the promotion of web-based learning is the development of effective collaborative learning environments. We posit that the structuration process strongly influences the effectiveness of technology used in web-based collaborative learning activities. In this paper, we propose an ant swarm collaborative learning (ASCL)…
Primi, Ricardo; Ferrao, Maria Eugenia; Almeida, Leandro S.
The association between fluid intelligence and inter-individual differences was investigated using multilevel growth curve modeling applied to data measuring intra-individual improvement on math achievement tests. A sample of 166 students (88 boys and 78 girls), ranging in age from 11 to 14 (M = 12.3, SD = 0.64), was tested. These individuals took…
Sigmar, Lucia; Hynes, Geraldine E.; Cooper, Tab
This study investigates the effect of Emotional Intelligence (EQ) training on student satisfaction with the collaborative writing process and product. Business communication students at an AACSB-accredited state university worked collaboratively on writing assignments in pre-and post-EQ-training sessions. Pre-and post-training surveys measured…
Zeidner, Moshe; Matthews, Gerald; Roberts, Richard D.
Emotional intelligence (or EI)--the ability to perceive, regulate, and communicate emotions, to understand emotions in ourselves and others--has been the subject of best-selling books, magazine cover stories, and countless media mentions. It has been touted as a solution for problems ranging from relationship issues to the inadequacies of local…
Boonma, Malai; Phaiboonnugulkij, Malinee
This article calls for a strong need to propose the theoretical framework of the Multiple Intelligences theory (MI) and provide a suitable answer of the doubt in part of foreign language teaching. The article addresses the application of MI theory following various sources from Howard Gardner and the authors who revised this theory for use in the…
This report summarizes and interprets the discussions at a seminar on artificial intelligence (AI) training domains and knowledge representations which was sponsored by the United Kingdom Training Commission. The following broad areas are addressed: (1) the context, process, and diversity of requirements of training and training needs; (2)…
Khatun, Nazma; Miwa, Jouji
This research project was aimed to develop an intelligent Bengali handwriting education system to improve the literacy level in Bangladesh. Due to the socio-economical limitation, all of the population does not have the chance to go to school. Here, we developed a prototype of web-based (iPhone/smartphone or computer browser) intelligent…
Ercan, Orhan; Ural, Evrim; Köse, Sinan
For a sustainable world, it is very important for students to develop positive environmental attitudes and to have awareness of energy use. The study aims to investigate the effect of web assisted instruction with emotional intelligence content on 8th grade students' emotional intelligence, attitudes towards environment and energy saving, academic…
Dix, Annika; Wartenburger, Isabell; van der Meer, Elke
This study on analogical reasoning evaluates the impact of fluid intelligence on adaptive changes in neural efficiency over the course of an experiment and specifies the underlying cognitive processes. Grade 10 students (N=80) solved unfamiliar geometric analogy tasks of varying difficulty. Neural efficiency was measured by the event-related desynchronization (ERD) in the alpha band, an indicator of cortical activity. Neural efficiency was defined as a low amount of cortical activity accompanying high performance during problem-solving. Students solved the tasks faster and more accurately the higher their FI was. Moreover, while high FI led to greater cortical activity in the first half of the experiment, high FI was associated with a neurally more efficient processing (i.e., better performance but same amount of cortical activity) in the second half of the experiment. Performance in difficult tasks improved over the course of the experiment for all students while neural efficiency increased for students with higher but decreased for students with lower fluid intelligence. Based on analyses of the alpha sub-bands, we argue that high fluid intelligence was associated with a stronger investment of attentional resource in the integration of information and the encoding of relations in this unfamiliar task in the first half of the experiment (lower-2 alpha band). Students with lower fluid intelligence seem to adapt their applied strategies over the course of the experiment (i.e., focusing on task-relevant information; lower-1 alpha band). Thus, the initially lower cortical activity and its increase in students with lower fluid intelligence might reflect the overcoming of mental overload that was present in the first half of the experiment. Copyright © 2016 Elsevier Inc. All rights reserved.
Wong, Morrison G.; Hirschman, Charles
In the early 1960s, Asian immigration to the United States was severely limited. The passage of the Immigration Act of 1965 expanded Asian immigration and ended a policy of racial discrimination and exclusion. Currently, over one third of the total immigrant population to the United States is from Asia, particularly China, Japan, Korea, the…
Jing, Yankang; Bian, Yuemin; Hu, Ziheng; Wang, Lirong; Xie, Xiang-Qun Sean
Over the last decade, deep learning (DL) methods have been extremely successful and widely used to develop artificial intelligence (AI) in almost every domain, especially after it achieved its proud record on computational Go. Compared to traditional machine learning (ML) algorithms, DL methods still have a long way to go to achieve recognition in small molecular drug discovery and development. And there is still lots of work to do for the popularization and application of DL for research purpose, e.g., for small molecule drug research and development. In this review, we mainly discussed several most powerful and mainstream architectures, including the convolutional neural network (CNN), recurrent neural network (RNN), and deep auto-encoder networks (DAENs), for supervised learning and nonsupervised learning; summarized most of the representative applications in small molecule drug design; and briefly introduced how DL methods were used in those applications. The discussion for the pros and cons of DL methods as well as the main challenges we need to tackle were also emphasized.
Full Text Available We propose to use a supervised machine learning technique to track the location of a mobile agent in real time. Hidden Markov Models are used to build artificial intelligence that estimates the unknown position of a mobile target moving in a defined environment. This narrow artificial intelligence performs two distinct tasks. First, it provides real-time estimation of the mobile agent’s position using the forward algorithm. Second, it uses the Baum–Welch algorithm as a statistical learning tool to gain knowledge of the mobile target. Finally, an experimental environment is proposed, namely, a video game that we use to test our artificial intelligence. We present statistical and graphical results to illustrate the efficiency of our method.
Mohammadzadeh, Ahmad; Sarkhosh, Mehdi
The current study attempted to investigate the effects of self-regulatory learning through computer-assisted intelligent tutoring system on the improvement of speaking ability. The participants of the study, who spoke Azeri Turkish as their mother tongue, were students of Applied Linguistics at BA level at Pars Abad's Azad University, Ardebil,…
Gomaa, Omema Mostafa Kamel
This study investigated the effect of using differentiated instruction using multiple intelligences on achievement in and attitudes towards science in middle school students with learning disabilities. A total of 61 students identified with LD participated. The sample was randomly divided into two groups; experimental (n= 31 boys )and control (n=…
Waalkens, Maaike; Aleven, Vincent; Taatgen, Niels
Intelligent tutoring systems (ITS) support students in learning a complex problem-solving skill. One feature that makes an ITS architecturally complex, and hard to build, is support for strategy freedom, that is, the ability to let students pursue multiple solution strategies within a given problem.
Contrasts exploratory learning with exploitative learning to argue for the importance of both and not just the latter. Discusses a case for organization studies that situates itself within a classical tradition of sociology. (CCM)
Full Text Available This article calls for a strong need to propose the theoretical framework of the Multiple Intelligences theory (MI and provide a suitable answer of the doubt in part of foreign language teaching. The article addresses the application of MI theory following various sources from Howard Gardner and the authors who revised this theory for using in the field of the English speaking improvement domain. In other word, this article combines and summarizes appropriate elements for the person on how to start teaching with this theory. The article also describes sequences and implication of the theory into practice. MI theory with the description of eight intelligences characteristic is presented. Following is the parts of activities catering and the processes of teaching with MI are provided. This article ends with the reviews of the ways for assessment and examples of lesson plan integrated with MI theory.
Lipavská, Helena; Žárský, Viktor
The concept of plant intelligence, as proposed by Anthony Trewavas, has raised considerable discussion. However, plant intelligence remains loosely defined; often it is either perceived as practically synonymous to Darwinian fitness, or reduced to a mere decorative metaphor. A more strict view can be taken, emphasizing necessary prerequisites such as memory and learning, which requires clarifying the definition of memory itself. To qualify as memories, traces of past events have to be not only stored, but also actively accessed. We propose a criterion for eliminating false candidates of possible plant intelligence phenomena in this stricter sense: an “intelligent” behavior must involve a component that can be approximated by a plausible algorithmic model involving recourse to stored information about past states of the individual or its environment. Re-evaluation of previously presented examples of plant intelligence shows that only some of them pass our test. “You were hurt?” Kumiko said, looking at the scar. Sally looked down. “Yeah.” “Why didn't you have it removed?” “Sometimes it's good to remember.” “Being hurt?” “Being stupid.”—(W. Gibson: Mona Lisa Overdrive) PMID:19816094
Emotional Intelligence (EI) was popularised in 1990s by Daniel Goleman’s bestselling book of the same name (Goleman 1996). EI has been criticised by scholars in the psychological community for lack of a clear definition or empirical evidence that it is anything more than a combination of already known cognitive and personality factors. Despite this controversy, there are many proponents of EI in higher education who highlight the folly of trying to separate the cognitive from the emotional. T...
J. (1979). Causal and teleological reasoning in circuit recognition. TR-529. MIT’ Artificial Intelligence Laboratory. Cambridge. MA. deler. J. (1995...Soloway. E. (1984). Intention-based diagnosis of progranming errors. In Procedings of the National Conference on Artificial jn~ience. Austin. Texas: NCAI...examples. Cognitive Psychology 17, 26-65. O’Shea, T. (1982). A sell-improving quadratic tutor. in Sleeman. D., & Brown. 3. S. (Eds.). Inteligent Tutoring
Computers have long been utilised in the legal environment. The main use of computers however, has merely been to automate office tasks. More exciting is the prospect of using artificial intelligence (AI) technology to create computers that can emulate the substantive legal jobs performed by lawyers, to create computers that can autonomously reason with the law to determine legal solutions, for example: structuring and support of Partnership for Peace (PfP) mandate. Such attempts have not bee...
This paper attempts to replicate the results of evaluating several artificial agents using the Algorithmic Intelligence Quotient test originally reported by Legg and Veness. Three experiments were conducted: One using default settings, one in which the action space was varied and one in which the observation space was varied. While the performance of freq, Q0, Qλ, and HLQλ corresponded well with the original results, the resulting values differed, when using MC-AIXI. Varying the observation space seems to have no qualitative impact on the results as reported, while (contrary to the original results) varying the action space seems to have some impact. An analysis of the impact of modifying parameters of MC-AIXI on its performance in the default settings was carried out with the help of data mining techniques used to identifying highly performing configurations. Overall, the Algorithmic Intelligence Quotient test seems to be reliable, however as a general artificial intelligence evaluation method it has several limits. The test is dependent on the chosen reference machine and also sensitive to changes to its settings. It brings out some differences among agents, however, since they are limited in size, the test setting may not yet be sufficiently complex. A demanding parameter sweep is needed to thoroughly evaluate configurable agents that, together with the test format, further highlights computational requirements of an agent. These and other issues are discussed in the paper along with proposals suggesting how to alleviate them. An implementation of some of the proposals is also demonstrated.
Christodoulou, Joanna A.
The ideas of multiple intelligences introduced by Howard Gardner of Harvard University more than 25 years ago have taken form in many ways, both in schools and in other sometimes-surprising settings. The silver anniversary of Gardner's learning theory provides an opportunity to reflect on the ways multiple intelligences theory has taken form and…
Describes the investigation of the effects of a four-step model program used with third through fifth grade students to implement Gardener's concepts of seven human intelligences--linguistic, logical/mathematical, visual/spatial, musical, kinesthetic, intrapersonal, and interpersonal intelligence--into daily learning. (BB)
Full Text Available This paper is a reflective discussion that critically describes the role of the Olympic Intelligence Centre (OIC played in the delivery of a safe and secure London 2012 Olympic and Paralympic Games. In particular, it examines how the OIC worked with the Olympic Sponsors and the wider private sector to provide them with the classified intelligence and information they needed to play their role in the safety and security operation effectively. Issues discussed include the cultural, statutory and systemic challenges that had to be overcome; how relationships were built to allay concerns and build trust and confidence; and the process that was put into place to allow the exchange of classified intelligence that supported the Sponsors and private sector in their operation. It details how the OIC worked with Sponsors to allow them in turn to exchange intelligence they held in their systems with the OIC, thus completing the intelligence cycle, enhancing the security operation. The article concludes with an outline of the lessons learned that were deduced through a reflective process and are offered to practitioners for consideration in future intelligence work involving the private sector.
Hen, Meirav; Goroshit, Marina
Academic procrastination has been seen as an impediment to students' academic success. Research findings suggest that it is related to lower levels of self-regulated learning and academic self-efficacy and associated with higher levels of anxiety, stress, and illness. Emotional intelligence (EI) is the ability to assess, regulate, and utilize emotions and has been found to be associated with academic self-efficacy and a variety of better outcomes, including academic performance. Students with learning disabilities (LD) are well acquainted with academic difficulty and maladaptive academic behavior. In comparison to students without LD, they exhibit high levels of learned helplessness, including diminished persistence, lower academic expectations, and negative affect. This study examined the relationships among academic procrastination, EI, and academic performance as mediated by academic self-efficacy in 287 LD and non-LD students. Results indicated that the indirect effect of EI on academic procrastination and GPA was stronger in LD students than in non-LD students. In addition, results indicated that LD students scored lower than non-LD students on both EI and academic self-efficacy and higher on academic procrastination. No difference was found in GPA.
Intelligent agents, intelligent software applications and artificial intelligent applications from artificial intelligence service providers may make their way onto the Web in greater number as adaptive software, dynamic programming languages and Learning Algorithms are introduced into Web Services. The evolution of Web architecture may allow intelligent applications to run directly on the Web by introducing XML, RDF and logic layer. The Intelligent Wireless Web’s significant potential for ra...
Sandhu, Sima; Bjerre, Neele V; Dauvrin, Marie
PURPOSE: While there has been systematic research on the experiences of immigrant patients in mental health services within certain European countries, little research has explored the experiences of mental health professionals in the delivery of services to immigrants across Europe. This study...... sought to explore professionals' experiences of delivering care to immigrants in districts densely populated with immigrants across Europe. METHODS: Forty-eight semi-structured interviews were conducted with mental health care professionals working in 16 European countries. Professionals in each country...... were recruited from three areas with the highest proportion of immigrants. For the purpose of this study, immigrants were defined as first-generation immigrants born outside the country of current residence, including regular immigrants, irregular immigrants, asylum seekers, refugees and victims...
Smith, Richard L.
Annotates reference material on artificial intelligence, mostly at an introductory level, with applications to education and learning. Topics include: (1) programing languages; (2) expert systems; (3) language instruction; (4) tutoring systems; and (5) problem solving and reasoning. (JM)
Deploy deep learning solutions in production with ease using TensorFlow. You'll also develop the mathematical understanding and intuition required to invent new deep learning architectures and solutions on your own. Pro Deep Learning with TensorFlow provides practical, hands-on expertise so you can learn deep learning from scratch and deploy meaningful deep learning solutions. This book will allow you to get up to speed quickly using TensorFlow and to optimize different deep learning architectures. All of the practical aspects of deep learning that are relevant in any industry are emphasized in this book. You will be able to use the prototypes demonstrated to build new deep learning applications. The code presented in the book is available in the form of iPython notebooks and scripts which allow you to try out examples and extend them in interesting ways. You will be equipped with the mathematical foundation and scientific knowledge to pursue research in this field and give back to the community.
Hansen, Steven Stenberg
The rapid advancement of machine learning techniques has re-energized research into general artificial intelligence. While the idea of domain-agnostic meta-learning is appealing, this emerging field must come to terms with its relationship to human cognition and the statistics and structure of the tasks humans perform. The position of this article is that only by aligning our agents' abilities and environments with those of humans do we stand a chance at developing general artificial intellig...
Full Text Available Background: Organizational intelligence has been defined as the capacity of an organization to direct its mental abilities and use these capabilities to achieve its mission and agility means ability to react quickly to environmental changes and it is an important factor for hospital effectiveness. This study was aimed to Evaluate Organizational Intelligence and Organizational learning and Organizational Agility in Teaching Hospitals of Yazd City. Methods: this descriptive, analytical, cross-sectional study was conducted in 2015 .the study population included administrative and medical staff in Shahid Sadoughi,, Shahid Rahnemoon,, Afshar and burning hospital. A total of 370 administrative and medical staff were contributed in the study. We used stratified-random method for sampling. The required data were gathered using 3 valid questionnaires including Albrecht- Organizational Intelligence (2002, organizational learning (neefe2001 and organizational agility questionnaire according to theory Sharifi & Zhang (1999 . data was analyzed by descriptive and inferential statistical methods in SPSS18 . Results: mean Organizational Intelligence scores hospital was 2.29, organizational learning scores hospital was 1.48 and organizational agility scores hospital was 1.52. as well as , hospital variable and Education affect on Organizational Intelligence, organizational learning and organizational agility. Conclusion: Based on the findings it can be concluded that the implementation of appropriate strategies for improving the organizational capacity to direct its employees’ mental abilities, can also improve the ability of organization’s rapid response to surrounding issues which is crucial for its survival and dynamics in today’s changing world
Wong, Lung-Hsiang; Looi, Chee-Kit
The notion of a system adapting itself to provide support for learning has always been an important issue of research for technology-enabled learning. One approach to provide adaptivity is to use social navigation approaches and techniques which involve analysing data of what was previously selected by a cluster of users or what worked for…
Yang, Ya-Ting Carolyn
This study investigates the effectiveness digital game-based learning (DGBL) on students' problem solving, learning motivation, and academic achievement. In order to provide substantive empirical evidence, a quasi-experimental design was implemented over the course of a full semester (23 weeks). Two ninth-grade Civics and Society classes, with a…
Jiang, Guo-Qian; Xie, Ping; Wang, Xiao; Chen, Meng; He, Qun
The performance of traditional vibration based fault diagnosis methods greatly depends on those handcrafted features extracted using signal processing algorithms, which require significant amounts of domain knowledge and human labor, and do not generalize well to new diagnosis domains. Recently, unsupervised representation learning provides an alternative promising solution to feature extraction in traditional fault diagnosis due to its superior learning ability from unlabeled data. Given that vibration signals usually contain multiple temporal structures, this paper proposes a multiscale representation learning (MSRL) framework to learn useful features directly from raw vibration signals, with the aim to capture rich and complementary fault pattern information at different scales. In our proposed approach, a coarse-grained procedure is first employed to obtain multiple scale signals from an original vibration signal. Then, sparse filtering, a newly developed unsupervised learning algorithm, is applied to automatically learn useful features from each scale signal, respectively, and then the learned features at each scale to be concatenated one by one to obtain multiscale representations. Finally, the multiscale representations are fed into a supervised classifier to achieve diagnosis results. Our proposed approach is evaluated using two different case studies: motor bearing and wind turbine gearbox fault diagnosis. Experimental results show that the proposed MSRL approach can take full advantages of the availability of unlabeled data to learn discriminative features and achieved better performance with higher accuracy and stability compared to the traditional approaches.
García-Floriano, Andrés; Ferreira-Santiago, Angel; Yáñez-Márquez, Cornelio; Camacho-Nieto, Oscar; Aldape-Pérez, Mario; Villuendas-Rey, Yenny
Social networking potentially offers improved distance learning environments by enabling the exchange of resources between learners. The existence of properly classified content results in an enhanced distance learning experience in which appropriate materials can be retrieved efficiently; however, for this to happen, metadata needs to be present.…
This book provides a unified framework that describes how genetic learning can be used to design pattern recognition and learning systems. It examines how a search technique, the genetic algorithm, can be used for pattern classification mainly through approximating decision boundaries. Coverage also demonstrates the effectiveness of the genetic classifiers vis-à-vis several widely used classifiers, including neural networks.
Liliawati, W.; Purwanto; Zulfikar, A.; Kamal, R. N.
This study aims to examine the effectiveness of the use of teaching materials based on multiple intelligences on the understanding of high school students’ material on the theme of global warming. The research method used is static-group pretest-posttest design. Participants of the study were 60 high school students of XI class in one of the high schools in Bandung. Participants were divided into two classes of 30 students each for the experimental class and control class. The experimental class uses compound-based teaching materials while the experimental class does not use a compound intelligence-based teaching material. The instrument used is a test of understanding of the concept of global warming with multiple choices form amounted to 15 questions and 5 essay items. The test is given before and after it is applied to both classes. Data analysis using N-gain and effect size. The results obtained that the N-gain for both classes is in the medium category and the effectiveness of the use of teaching materials based on the results of effect-size test results obtained in the high category.
Good Evening, my name is Greg Jerman and for nearly a quarter century I have been performing failure analysis on NASA's aerospace hardware. During that time I had the distinct privilege of keeping the Space Shuttle flying for two thirds of its history. I have analyzed a wide variety of failed hardware from simple electrical cables to cryogenic fuel tanks to high temperature turbine blades. During this time I have found that for all the time we spend intelligently designing things, we need to be equally intelligent about understanding why things fail. The NASA Flight Director for Apollo 13, Gene Kranz, is best known for the expression "Failure is not an option." However, NASA history is filled with failures both large and small, so it might be more accurate to say failure is inevitable. It is how we react and learn from our failures that makes the difference.
Bini, Stefano A
This article was presented at the 2017 annual meeting of the American Association of Hip and Knee Surgeons to introduce the members gathered as the audience to the concepts behind artificial intelligence (AI) and the applications that AI can have in the world of health care today. We discuss the origin of AI, progress to machine learning, and then discuss how the limits of machine learning lead data scientists to develop artificial neural networks and deep learning algorithms through biomimicry. We will place all these technologies in the context of practical clinical examples and show how AI can act as a tool to support and amplify human cognitive functions for physicians delivering care to increasingly complex patients. The aim of this article is to provide the reader with a basic understanding of the fundamentals of AI. Its purpose is to demystify this technology for practicing surgeons so they can better understand how and where to apply it. Copyright © 2018 Elsevier Inc. All rights reserved.
Rimfeld, K; Dale, P S; Plomin, R
Learning a second language is crucially important in an increasingly global society, yet surprisingly little is known about why individuals differ so substantially in second language (SL) achievement. We used the twin design to assess the nature, nurture and mediators of individual differences in SL achievement. For 6263 twin pairs, we analyzed scores from age 16 UK-wide standardized tests, the General Certificate of Secondary Education (GCSE). We estimated genetic and environmental influences on the variance of SL for specific languages, the links between SL and English and the extent to which the links between SL and English are explained by intelligence. All SL measures showed substantial heritability, although heritability was nonsignificantly lower for German (36%) than the other languages (53-62%). Multivariate genetic analyses indicated that a third of genetic influence in SL is shared with intelligence, a third with English independent of intelligence and a further third is unique to SL.
This paper forms part of a preliminary survey for work on the application of artificial intelligence theories and techniques to the learning of music composition skills. The paper deals with present day applications of computers to the teaching of music and speculations about how artificial intelligence might be used to foster music composition in…
Cardina, Bruno; Francisco, Jerónimo; Reis, Pedro; trad. Silva, Fátima
This article focuses on the generational gaps in school learning. Initially, we have tried to provide the framework in relation to the term digital native in order to understand the key aspects of the generation born after the advent and the global use of the Internet. They were found to be “multitasking” people, linked to technology and connectivity, as opposed to digital immigrants, born in an earlier period and seeking to adapt to the technological world. We also present some r...
Sarit Cohen; Zvika Eckstein
The transition pattern of post schooling individuals, displaced workers and immigrants to the labor market has similar characteristics. Unemployment falls quickly as workers first find blue-collar jobs, followed by a gradual movement to white-collar occupations. For immigrants the transition includes the learning of the new country language as well as the skills demanded by the new labor market. This paper focuses on male immigrants who moved from the former Soviet Union to Israel and are cha...
Full Text Available Today mobile technologies have become an integral part of the learning activities. With mobile technologies ―Any time, anywhere, any device‖ promise of e-learning is going to become actually applicable and mobile technologies are going to provide opportunities to be ―always on‖ and connected for twenty-first century learners and to get information on demand with ―just enough, just in time, and just for me‖ approach (Yamamoto, Ozan, & Demiray, 2010. Mobile technology includes both hardware and networking applications; hence both of them are necessary for the existence of m-Learning. Today one of the big challenges of mobile learning is technical issues. This book provides case studies and solution about technical applications of mobile learning.The book's broader audience is anyone who is interested in mobile learning systems‘ architecture. Beside this, it gives valuable information for mobile learning designers.The book is edited by The book is edited by Angel Juan , Thanasis Daradoumis, Fatos Xhafa and Santi Caballé. Angel A. Juan is an associate professor of simulation and data analysis in the computer sciences department at the Open University of Catalonia (Spain.Thanasis Daradoumis is an associate professor
Liu, Yang; Song, Fazhi; Yang, Xiaofeng; Dong, Yue; Tan, Jiubin
Due to their structural simplicity, linear motors are increasingly receiving attention for use in high velocity and high precision applications. The force ripple, as a space-periodic disturbance, however, would deteriorate the achievable dynamic performance. Conventional force ripple measurement approaches are time-consuming and have high requirements on the experimental conditions. In this paper, a novel learning identification algorithm is proposed for force ripple intelligent measurement and compensation. Existing identification schemes always use all the error signals to update the parameters in the force ripple. However, the error induced by noise is non-effective for force ripple identification, and even deteriorates the identification process. In this paper only the most pertinent information in the error signal is utilized for force ripple identification. Firstly, the effective error signals caused by the reference trajectory and the force ripple are extracted by projecting the overall error signals onto a subspace spanned by the physical model of the linear motor as well as the sinusoidal model of the force ripple. The time delay in the linear motor is compensated in the basis functions. Then, a data-driven approach is proposed to design the learning gain. It balances the trade-off between convergence speed and robustness against noise. Simulation and experimental results validate the proposed method and confirm its effectiveness and superiority.
Lau, Adela S M
Web 2.0 provides a platform or a set of tools such as blogs, wikis, really simple syndication (RSS), podcasts, tags, social bookmarks, and social networking software for knowledge sharing, learning, social interaction, and the production of collective intelligence in a virtual environment. Web 2.0 is also becoming increasingly popular in e-learning and e-social communities. The objectives were to investigate how Web 2.0 tools can be applied for knowledge sharing, learning, social interaction, and the production of collective intelligence in the nursing domain and to investigate what behavioral perceptions are involved in the adoption of Web 2.0 tools by nurses. The decomposed technology acceptance model was applied to construct the research model on which the hypotheses were based. A questionnaire was developed based on the model and data from nurses (n = 388) were collected from late January 2009 until April 30, 2009. Pearson's correlation analysis and t tests were used for data analysis. Intention toward using Web 2.0 tools was positively correlated with usage behavior (r = .60, P Web 2.0 tools and enable them to better plan the strategy of implementation of Web 2.0 tools for knowledge sharing, learning, social interaction, and the production of collective intelligence.
Background Web 2.0 provides a platform or a set of tools such as blogs, wikis, really simple syndication (RSS), podcasts, tags, social bookmarks, and social networking software for knowledge sharing, learning, social interaction, and the production of collective intelligence in a virtual environment. Web 2.0 is also becoming increasingly popular in e-learning and e-social communities. Objectives The objectives were to investigate how Web 2.0 tools can be applied for knowledge sharing, learning, social interaction, and the production of collective intelligence in the nursing domain and to investigate what behavioral perceptions are involved in the adoption of Web 2.0 tools by nurses. Methods The decomposed technology acceptance model was applied to construct the research model on which the hypotheses were based. A questionnaire was developed based on the model and data from nurses (n = 388) were collected from late January 2009 until April 30, 2009. Pearson’s correlation analysis and t tests were used for data analysis. Results Intention toward using Web 2.0 tools was positively correlated with usage behavior (r = .60, P Web 2.0 tools and enable them to better plan the strategy of implementation of Web 2.0 tools for knowledge sharing, learning, social interaction, and the production of collective intelligence. PMID:22079851
Malchow-Møller, Nikolaj; Munch, Jakob Roland; Skaksen, Jan Rose
Using the European Social Survey 2002/3, we develop a new test of whether economic self-interest influences people's attitudes towards immigration, exploiting that people have widely different perceptions of the consequences of immigration......Using the European Social Survey 2002/3, we develop a new test of whether economic self-interest influences people's attitudes towards immigration, exploiting that people have widely different perceptions of the consequences of immigration...
Immigration is one of the most important policy debates in Western countries. However, one aspect of the debate is often mischaracterized by accusations that higher levels of immigration lead to higher levels of crime. The evidence, based on empirical studies of many countries, indicates that there is no simple link between immigration and crime. Crucially, the evidence points to substantial differences in the impact on property crime, depending on the labor market opportunities of immigrant ...
Casarico, Alessandra; Facchini, Giovanni; Frattini, Tommaso
We develop a general model of legal and illegal immigration to understand the basic tradeoffs faced by a government in the decision to implement an immigration amnesty in the presence of a selective immigration policy. We show that two channels play an important role: an amnesty is more likely the more restricted are the occupational opportunities of undocumented immigrants and the less redistributive is the welfare state. Empirical evidence based on a novel panel dataset of legalizations car...
Bravo, C.; van Joolingen, W.R.; de Jong, T.
Inquiry learning is a didactic approach in which students acquire knowledge and skills through processes of theory building and experimentation. Computer modeling and simulation can play a prominent role within this approach. Students construct representations of physical systems using modeling.
Foulquier, Nathan; Redou, Pascal; Le Gal, Christophe; Rouvière, Bénédicte; Pers, Jacques-Olivier; Saraux, Alain
Big data analysis has become a common way to extract information from complex and large datasets among most scientific domains. This approach is now used to study large cohorts of patients in medicine. This work is a review of publications that have used artificial intelligence and advanced machine learning techniques to study physio pathogenesis-based treatments in pSS. A systematic literature review retrieved all articles reporting on the use of advanced statistical analysis applied to the study of systemic autoimmune diseases (SADs) over the last decade. An automatic bibliography screening method has been developed to perform this task. The program called BIBOT was designed to fetch and analyze articles from the pubmed database using a list of keywords and Natural Language Processing approaches. The evolution of trends in statistical approaches, sizes of cohorts and number of publications over this period were also computed in the process. In all, 44077 abstracts were screened and 1017 publications were analyzed. The mean number of selected articles was 101.0 (S.D. 19.16) by year, but increased significantly over the time (from 74 articles in 2008 to 138 in 2017). Among them only 12 focused on pSS but none of them emphasized on the aspect of pathogenesis-based treatments. To conclude, medicine progressively enters the era of big data analysis and artificial intelligence, but these approaches are not yet used to describe pSS-specific pathogenesis-based treatment. Nevertheless, large multicentre studies are investigating this aspect with advanced algorithmic tools on large cohorts of SADs patients.
Full Text Available In this paper, iterative learning control (ILC is combined with an optimal fractional order derivative (BBO-Da-type ILC and optimal fractional and proportional-derivative (BBO-PDa-type ILC. In the update law of Arimoto's derivative iterative learning control, a first order derivative of tracking error signal is used. In the proposed method, fractional order derivative of the error signal is stated in term of 'sa' where to update iterative learning control law. Two types of fractional order iterative learning control namely PDa-type ILC and Da-type ILC are gained for different value of a. In order to improve the performance of closed-loop control system, coefficients of both and learning law i.e. proportional , derivative and are optimized using Biogeography-Based optimization algorithm (BBO. Outcome of the simulation results are compared with those of the conventional fractional order iterative learning control to verify effectiveness of BBO-Da-type ILC and BBO-PDa-type ILC
Jacoff, Adam; Messina, Elena; Weiss, Brian A.
Urban search and rescue (USAR) is one of the most dangerous and time-critical non-wartime activities. Researchers have been developing hardware and software to enable robots to perform some search and rescue functions so as to minimize the exposure of human rescue personnel to danger and maximize the survival of victims. Significant progress has been achieved, but much work remains. USAR demands a blending of numerous specialized technologies. An effective USAR robot must be endowed with key competencies, such as being able to negotiate collapsed structures, find victims and assess their condition, identify potential hazards, generate maps of the structure and victim locations, and communicate with rescue personnel. These competencies bring to bear work in numerous sub-disciplines of intelligent systems (or artificial intelligence) such as sensory processing, world modeling, behavior generation, path planning, and human-robot interaction, in addition to work in communications, mechanism design and advanced sensors. In an attempt to stimulate progress in the field, reference USAR challenges are being developed and propagated worldwide. In order to make efficient use of finite research resources, the robotic USAR community must share a common understanding of what is required, technologically, to attain each competency, and have a rigorous measure of the current level of effectiveness of various technologies. NIST is working with partner organizations to measure the performance of robotic USAR competencies and technologies. In this paper, we describe the reference test arenas for USAR robots, assess the current challenges within the field, and discuss experiences thus far in the testing effort.
NASA also seeks to advance American education by employing the technology utilization process to develop a computerized, artificial intelligence-based Intelligent Tutoring System (ITS) to help high school and college physics students. The tutoring system is designed for use with the lecture and laboratory portions of a typical physics instructional program. Its importance lies in its ability to observe continually as a student develops problem solutions and to intervene when appropriate with assistance specifically directed at the student's difficulty and tailored to his skill level and learning style. ITS originated as a project of the Johnson Space Center (JSC). It is being developed by JSC's Software Technology Branch in cooperation with Dr. R. Bowen Loftin at the University of Houston-Downtown. Program is jointly sponsored by NASA and ACOT (Apple Classrooms of Tomorrow). Other organizations providing support include Texas Higher Education Coordinating Board, the National Research Council, Pennzoil Products Company and the George R. Brown Foundation. The Physics I class of Clear Creek High School, League City, Texas are providing the classroom environment for test and evaluation of the system. The ITS is a spinoff product developed earlier to integrate artificial intelligence into training/tutoring systems for NASA astronauts flight controllers and engineers.
Johnson, Kipp W; Torres Soto, Jessica; Glicksberg, Benjamin S; Shameer, Khader; Miotto, Riccardo; Ali, Mohsin; Ashley, Euan; Dudley, Joel T
Artificial intelligence and machine learning are poised to influence nearly every aspect of the human condition, and cardiology is not an exception to this trend. This paper provides a guide for clinicians on relevant aspects of artificial intelligence and machine learning, reviews selected applications of these methods in cardiology to date, and identifies how cardiovascular medicine could incorporate artificial intelligence in the future. In particular, the paper first reviews predictive modeling concepts relevant to cardiology such as feature selection and frequent pitfalls such as improper dichotomization. Second, it discusses common algorithms used in supervised learning and reviews selected applications in cardiology and related disciplines. Third, it describes the advent of deep learning and related methods collectively called unsupervised learning, provides contextual examples both in general medicine and in cardiovascular medicine, and then explains how these methods could be applied to enable precision cardiology and improve patient outcomes. Copyright © 2018 The Authors. Published by Elsevier Inc. All rights reserved.
The intelligent infrastructure is often the most visible manifestation of intelligent transportation systems (ITS) along with roads, freeways, and incident management is often among the first ITS elements implemented. They can significantly contribut...
Kartikasari, A.; Widjajanti, D. B.
The aim of this study is to explore the effectiveness of learning approach using problem-based learning based on multiple intelligences in developing student’s achievement, mathematical connection ability, and self-esteem. This study is experimental research with research sample was 30 of Grade X students of MIA III MAN Yogyakarta III. Learning materials that were implemented consisting of trigonometry and geometry. For the purpose of this study, researchers designed an achievement test made up of 44 multiple choice questions with respectively 24 questions on the concept of trigonometry and 20 questions for geometry. The researcher also designed a connection mathematical test and self-esteem questionnaire that consisted of 7 essay questions on mathematical connection test and 30 items of self-esteem questionnaire. The learning approach said that to be effective if the proportion of students who achieved KKM on achievement test, the proportion of students who achieved a minimum score of high category on the results of both mathematical connection test and self-esteem questionnaire were greater than or equal to 70%. Based on the hypothesis testing at the significance level of 5%, it can be concluded that the learning approach using problem-based learning based on multiple intelligences was effective in terms of student’s achievement, mathematical connection ability, and self-esteem.
Wei, Junqing; Dolan, John M.; Litkouhi, Bakhtiar
In this paper, an offline learning mechanism based on the genetic algorithm is proposed for autonomous vehicles to emulate human driver behaviors. The autonomous driving ability is implemented based on a Prediction- and Cost function-Based algorithm (PCB). PCB is designed to emulate a human driver's decision process, which is modeled as traffic scenario prediction and evaluation. This paper focuses on using a learning algorithm to optimize PCB with very limited training data, so that PCB can have the ability to predict and evaluate traffic scenarios similarly to human drivers. 80 seconds of human driving data was collected in low-speed (car-following scenarios. In the low-speed car-following tests, PCB was able to perform more human-like carfollowing after learning. A more general 120 kilometer-long simulation showed that PCB performs robustly even in scenarios that are not part of the training set.
Angelova, Iva Ventzislavova
The purpose of this study was to explore Bulgarian immigrants' narratives with respect to their perceptions of immigrant work challenges; learning at work; work or occupational preferences; immigrant careers, including job transitions and professional development; strategies with respect to work; support at work; satisfaction gained from work; and…
Deding, Mette; Hussain, Azhar; Jakobsen, Vibeke
During the last two decades most Western countries have experienced increased net immigration as well as increased income inequality. This article analyzes the effects on income inequality of an increased number of immigrants in Denmark and Germany for the 20- year period 1984-2003 and how...... the impact of the increased number of immigrants differs between the two countries. We find higher inequality for immigrants than natives in Denmark but vice versa for Germany. Over the period 1984-2003, this particular inequality gap has narrowed in both countries. At the same time, the contribution...... of immigrants to overall inequality has increased, primarily caused by increased between-group inequality. The share of immigrants in the population is more important for the change in overall inequality in Denmark than in Germany, while the opposite is the case for inequality among immigrants....
Clarke, Angela; Cripps, Peter
Curriculum and pedagogy in undergraduate fine art can promote an approach to learning creativity that is more about being an artist than knowing about art. Lecturers can provide a road map for developing particular dispositions, in relation to student ideas and perceptions, to foster personalised creativity. This requires that lecturers have an…
Hall, L.; Tazzyman, S.; Hume, C.; Endrass, B.; Lim, M.Y.; Hofstede, G.J.; Paiva, A.; Andre, E.; Kappas, A.; Aylett, R.
Providing opportunities for children to engage with intercultural learning has frequently focused on exposure to the ritual, celebrations and festivals of cultures, with the view that such experiences will result in greater acceptance of cultural differences. Intercultural conflict is often avoided,
While theoretical approaches to error correction vary in the second language acquisition (SLA) literature, most sources agree that such correction is useful and leads to learning. While some point out the relevance of the communicative context in which the correction takes place, others stress the value of consciousness-raising. Trying to…
Taylor, C. James
The paper describes the utility of a low cost, 1 m2 by 2 m forced ventilation, micro-climate test chamber, for the support of research and teaching in mechatronics. Initially developed for the evaluation of a new ventilation rate controller, the fully instrumented chamber now provides numerous learning opportunities and individual projects for both undergraduate and postgraduate research students.
Tynell, Lena Lyngholt; Wimmelmann, Camilla Lawaetz; Jervelund, Signe Smith
a language school in Copenhagen in 2012 received either a course or written information on the Danish healthcare system and subsequently evaluated this quantitatively. Results: The evaluation revealed a positive appraisal of the course/information provided. Conclusion: In times of austerity, incorporating......Objective: In most European countries, immigrants do not systematically learn about the host countries’ healthcare system when arriving. This study investigated how newly arrived immigrants perceived the information they received about the Danish healthcare system. Method: Immigrants attending...... healthcare information into an already existing language programme may be pertinent for providing immigrants with knowledge on the healthcare system....
Weld, Daniel S.; Bansal, Gagan
Since Artificial Intelligence (AI) software uses techniques like deep lookahead search and stochastic optimization of huge neural networks to fit mammoth datasets, it often results in complex behavior that is difficult for people to understand. Yet organizations are deploying AI algorithms in many mission-critical settings. In order to trust their behavior, we must make it intelligible --- either by using inherently interpretable models or by developing methods for explaining otherwise overwh...
Callahan, Rebecca; Wilkinson, Lindsey; Muller, Chandra; Frisco, Michelle
In this study, the authors explore English as a Second Language (ESL) placement as a measure of how schools label and process immigrant students. Using propensity score matching and data from the Adolescent Health and Academic Achievement Study and the National Longitudinal Study of Adolescent Health, the authors estimate the effect of ESL placement on immigrant achievement. In schools with more immigrant students, the authors find that ESL placement results in higher levels of academic performance; in schools with few immigrant students, the effect reverses. This is not to suggest a one-size-fits-all policy; many immigrant students, regardless of school composition, generational status, or ESL placement, struggle to achieve at levels sufficient for acceptance to a 4-year university. This study offers several factors to be taken into consideration as schools develop policies and practices to provide immigrant students opportunities to learn.
Erikson, Henrik; Salzmann-Erikson, Martin
It is highly likely that artificial intelligence (AI) will be implemented in nursing robotics in various forms, both in medical and surgical robotic instruments, but also as different types of droids and humanoids, physical reinforcements, and also animal/pet robots. Exploring and discussing AI and robotics in nursing and health care before these tools become commonplace is of great importance. We propose that monsters in popular culture might be studied with the hope of learning about situations and relationships that generate empathic capacities in their monstrous existences. The aim of the article is to introduce the theoretical framework and assumptions behind this idea. Both robots and monsters are posthuman creations. The knowledge we present here gives ideas about how nursing science can address the postmodern, technologic, and global world to come. Monsters therefore serve as an entrance to explore technologic innovations such as AI. Analyzing when and why monsters step out of character can provide important insights into the conceptualization of caring and nursing as a science, which is important for discussing these empathic protocols, as well as more general insight into human knowledge. The relationship between caring, monsters, robotics, and AI is not as farfetched as it might seem at first glance.
Specific primers play an important role in polymerase chain reaction (PCR) experiments, and therefore it is essential to find specific primers of outstanding quality. Unfortunately, many PCR constraints must be simultaneously inspected which makes specific primer selection difficult and time-consuming. This paper introduces a novel computational intelligence-based method, Teaching-Learning-Based Optimisation, to select the specific and feasible primers. The specified PCR product lengths of 150-300 bp and 500-800 bp with three melting temperature formulae of Wallace's formula, Bolton and McCarthy's formula and SantaLucia's formula were performed. The authors calculate optimal frequency to estimate the quality of primer selection based on a total of 500 runs for 50 random nucleotide sequences of 'Homo species' retrieved from the National Center for Biotechnology Information. The method was then fairly compared with the genetic algorithm (GA) and memetic algorithm (MA) for primer selection in the literature. The results show that the method easily found suitable primers corresponding with the setting primer constraints and had preferable performance than the GA and the MA. Furthermore, the method was also compared with the common method Primer3 according to their method type, primers presentation, parameters setting, speed and memory usage. In conclusion, it is an interesting primer selection method and a valuable tool for automatic high-throughput analysis. In the future, the usage of the primers in the wet lab needs to be validated carefully to increase the reliability of the method.
Michie, Susan; Thomas, James; Johnston, Marie; Aonghusa, Pol Mac; Shawe-Taylor, John; Kelly, Michael P; Deleris, Léa A; Finnerty, Ailbhe N; Marques, Marta M; Norris, Emma; O'Mara-Eves, Alison; West, Robert
Behaviour change is key to addressing both the challenges facing human health and wellbeing and to promoting the uptake of research findings in health policy and practice. We need to make better use of the vast amount of accumulating evidence from behaviour change intervention (BCI) evaluations and promote the uptake of that evidence into a wide range of contexts. The scale and complexity of the task of synthesising and interpreting this evidence, and increasing evidence timeliness and accessibility, will require increased computer support. The Human Behaviour-Change Project (HBCP) will use Artificial Intelligence and Machine Learning to (i) develop and evaluate a 'Knowledge System' that automatically extracts, synthesises and interprets findings from BCI evaluation reports to generate new insights about behaviour change and improve prediction of intervention effectiveness and (ii) allow users, such as practitioners, policy makers and researchers, to easily and efficiently query the system to get answers to variants of the question 'What works, compared with what, how well, with what exposure, with what behaviours (for how long), for whom, in what settings and why?'. The HBCP will: a) develop an ontology of BCI evaluations and their reports linking effect sizes for given target behaviours with intervention content and delivery and mechanisms of action, as moderated by exposure, populations and settings; b) develop and train an automated feature extraction system to annotate BCI evaluation reports using this ontology; c) develop and train machine learning and reasoning algorithms to use the annotated BCI evaluation reports to predict effect sizes for particular combinations of behaviours, interventions, populations and settings; d) build user and machine interfaces for interrogating and updating the knowledge base; and e) evaluate all the above in terms of performance and utility. The HBCP aims to revolutionise our ability to synthesise, interpret and deliver
C. S. Chin
Full Text Available The control of biofouling on marine vessels is challenging and costly. Early detection before hull performance is significantly affected is desirable, especially if “grooming” is an option. Here, a system is described to detect marine fouling at an early stage of development. In this study, an image of fouling can be transferred wirelessly via a mobile network for analysis. The proposed system utilizes transfer learning and deep convolutional neural network (CNN to perform image recognition on the fouling image by classifying the detected fouling species and the density of fouling on the surface. Transfer learning using Google’s Inception V3 model with Softmax at last layer was carried out on a fouling database of 10 categories and 1825 images. Experimental results gave acceptable accuracies for fouling detection and recognition.
Khorramabadi, Sima Seidi; Boroushaki, Mehrdad; Lucas, Caro
The design and evaluation of a novel approach to reactor core power control based on emotional learning is described. The controller includes a neuro-fuzzy system with power error and its derivative as inputs. A fuzzy critic evaluates the present situation, and provides the emotional signal (stress). The controller modifies its characteristics so that the critic's stress is reduced. Simulation results show that the controller has good convergence and performance robustness characteristics over a wide range of operational parameters
Thomas, George; Grassi, Michael A; Lee, John R; Edwards, Albert O; Gorin, Michael B; Klein, Ronald; Casavant, Thomas L; Scheetz, Todd E; Stone, Edwin M; Williams, Andrew B
To use the power of knowledge acquisition and machine learning in the development of a collaborative computer classification system based on the features of age-related macular degeneration (AMD). A vocabulary was acquired from four AMD experts who examined 100 ophthalmoscopic images. The vocabulary was analyzed, hierarchically structured, and incorporated into a collaborative computer classification system called IDOCS. Using this system, three of the experts examined images from a second set of digital images compiled from more than 1000 patients with AMD. Images were annotated, and features were identified and defined. Decision trees, a machine learning method, were trained on the data collected and used to extract patterns. Interrelationships between the data from the different clinicians were investigated. Six drusen classes in the structured vocabulary were largely sufficient to describe all the identified features. The decision trees classified the data with 76.86% to 88.5% accuracy and distilled patterns in the form of hierarchical trees composed of 5 to 15 nodes. Experts were largely consistent in their characterization of soft, and to a lesser extent, hard drusen, but diverge in definition of other drusen. Size and crystalline morphology were the main determinants of drusen type across all experts. Machine learning is a powerful tool for the characterization of disease phenotypes. The creation of a defined feature set for AMD will facilitate the development of an IDOCS-based classification system.
Abdollahi, Rohollah; Farhangi, Reza; Yarahmadi, Ali
This paper presents design and evaluation of a novel approach based on emotional learning to improve the speed control system of rotor flux oriented control of induction motor. The controller includes a neuro-fuzzy system with speed error and its derivative as inputs. A fuzzy critic evaluates the present situation, and provides the emotional signal (stress). The controller modifies its characteristics so that the critics stress is reduced. The comparative simulation results show that the proposed controller is more robust and hence found to be a suitable replacement of the conventional PI controller for the high performance industrial drive applications.
Tanaka, M; Nakazono, S; Matsuno, H; Tsujimoto, H; Kitamura, Y; Miyano, S
We have implemented a system for assisting experts in selecting MEDLINE records for database construction purposes. This system has two specific features: The first is a learning mechanism which extracts characteristics in the abstracts of MEDLINE records of interest as patterns. These patterns reflect selection decisions by experts and are used for screening the records. The second is a keyword recommendation system which assists and supplements experts' knowledge in unexpected cases. Combined with a conventional keyword-based information retrieval system, this system may provide an efficient and comfortable environment for MEDLINE record selection by experts. Some computational experiments are provided to prove that this idea is useful.
Hearing on 'Comprehensive Immigration Reform: Becoming Americans - US Immigrant Integration,' Subcommittee on Immigration, Citizenship, Refugees, Border Security, and International Law of the Committee on the Judiciary, House of Representatives, Serial No. 110-27. May 16, 2007. Abstract: In this statement to a House Hearing on comprehensive immigration reform focusing on immigrant integration, English and foreign language competencies, preferences and use among immigrants and thei...
Leibbrandt, Richard; Yang, Dongqiang; Pfitzner, Darius; Powers, David; Mitchell, Pru; Hayman, Sarah; Eddy, Helen
This paper reports on a joint proof of concept project undertaken by researchers from the Flinders University Artificial Intelligence Laboratory in partnership with information managers from the Education Network Australia (edna) team at Education Services Australia to address the question of whether artificial intelligence techniques could be…
Abbas Ali Zarei
Full Text Available The present study was an attempt to investigate the differences in the accessibility of phonological, semantic, and orthographic aspects of words in L2 vocabulary learning. For this purpose, a sample of 119 Iranian intermediate level EFL students in a private language institute in Karaj was selected. All of the participants received the same instructional treatment. At the end of the experimental period, three tests were administered based on the previously-taught words. A subset of Gardner’s’ (1983 Multiple Intelligences questionnaire was also used for data collection. A repeated measures one-way ANOVA procedure was used to analyze the obtained data. The results showed significant differences in the accessibility of phonological, semantic, and orthographic aspects of words in second language vocabulary learning. Moreover, to investigate the relationships between spatial and linguistic intelligences and the afore-mentioned aspects of lexical knowledge, a correlational analysis was used. No significant relationships were found between spatial and linguistic intelligences and the three aspects of lexical knowledge. These findings may have theoretical and pedagogical implications for researchers, teachers, and learners.
Doctoral thesis (Ph.D.) – Bodø Graduate School of Business, 2008 The purpose of this doctoral thesis is to add to the knowledge about immigrant entrepreneurship in Norway and to test the existing theories relating to immigrant entrepreneurship. In this work, an immigrant entrepreneur is defined as a business owner born outside Norway with both parents born abroad who is involved into the activities characterised by economic innovation, organisation creation, and profit-seeking in the marke...
Paolo E Giordani; Michele Ruta
We study immigration policy in a small open receiving economy under self-selection of migrants. We show that immigration policy choice affects and is affected by the migratory decisions of skilled and unskilled foreign workers. From this interaction multiple equilibria may arise, which are driven by the natives' expectations on the migrants' size and skill composition (and, hence, on the welfare effects of immigration). In particular, pessimistic (optimistic) beliefs induce a country to impos...
Hunt, Earl B
Artificial Intelligence provides information pertinent to the fundamental aspects of artificial intelligence. This book presents the basic mathematical and computational approaches to problems in the artificial intelligence field.Organized into four parts encompassing 16 chapters, this book begins with an overview of the various fields of artificial intelligence. This text then attempts to connect artificial intelligence problems to some of the notions of computability and abstract computing devices. Other chapters consider the general notion of computability, with focus on the interaction bet
Hashimoto, H. [The University of Tokyo, Tokyo (Japan). Institute of Industrial Science
Intelligent mechatronics (IM) was explained as follows: a study of IM essentially targets realization of a robot namely, but in the present stage the target is a creation of new values by intellectualization of machine, that is, a combination of the information infrastructure and the intelligent machine system. IM is also thought to be constituted of computers positively used and micromechatronics. The paper next introduces examples of IM study, mainly those the author is concerned with as shown below: sensor gloves, robot hands, robot eyes, tele operation, three-dimensional object recognition, mobile robot, magnetic bearing, construction of remote controlled unmanned dam, robot network, sensitivity communication using neuro baby, etc. 27 figs.
Kim, D H; MacKinnon, T
To identify the extent to which transfer learning from deep convolutional neural networks (CNNs), pre-trained on non-medical images, can be used for automated fracture detection on plain radiographs. The top layer of the Inception v3 network was re-trained using lateral wrist radiographs to produce a model for the classification of new studies as either "fracture" or "no fracture". The model was trained on a total of 11,112 images, after an eightfold data augmentation technique, from an initial set of 1,389 radiographs (695 "fracture" and 694 "no fracture"). The training data set was split 80:10:10 into training, validation, and test groups, respectively. An additional 100 wrist radiographs, comprising 50 "fracture" and 50 "no fracture" images, were used for final testing and statistical analysis. The area under the receiver operator characteristic curve (AUC) for this test was 0.954. Setting the diagnostic cut-off at a threshold designed to maximise both sensitivity and specificity resulted in values of 0.9 and 0.88, respectively. The AUC scores for this test were comparable to state-of-the-art providing proof of concept for transfer learning from CNNs in fracture detection on plain radiographs. This was achieved using only a moderate sample size. This technique is largely transferable, and therefore, has many potential applications in medical imaging, which may lead to significant improvements in workflow productivity and in clinical risk reduction. Copyright © 2017 The Royal College of Radiologists. Published by Elsevier Ltd. All rights reserved.
from the Table of Contents: Migration and integration - Basic concepts and definitions; Immigration and Integration policies; The legal framework for integration; Dimension of social integration; Cultural integration; Conclusions;
Third-grader Jaime of Denver, Colorado, was having a hard time concentrating in school. The son of Mexican immigrants, he had learned to speak English perfectly in his dual-language public school, but reading and writing was another story. When her mother knew about Cesar Chavez Academy, a new tuition-free charter school where the majority of…
Lin, Chin; Hsu, Chia-Jung; Lou, Yu-Sheng; Yeh, Shih-Jen; Lee, Chia-Cheng; Su, Sui-Lung; Chen, Hsiang-Cheng
Automated disease code classification using free-text medical information is important for public health surveillance. However, traditional natural language processing (NLP) pipelines are limited, so we propose a method combining word embedding with a convolutional neural network (CNN). Our objective was to compare the performance of traditional pipelines (NLP plus supervised machine learning models) with that of word embedding combined with a CNN in conducting a classification task identifying International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) diagnosis codes in discharge notes. We used 2 classification methods: (1) extracting from discharge notes some features (terms, n-gram phrases, and SNOMED CT categories) that we used to train a set of supervised machine learning models (support vector machine, random forests, and gradient boosting machine), and (2) building a feature matrix, by a pretrained word embedding model, that we used to train a CNN. We used these methods to identify the chapter-level ICD-10-CM diagnosis codes in a set of discharge notes. We conducted the evaluation using 103,390 discharge notes covering patients hospitalized from June 1, 2015 to January 31, 2017 in the Tri-Service General Hospital in Taipei, Taiwan. We used the receiver operating characteristic curve as an evaluation measure, and calculated the area under the curve (AUC) and F-measure as the global measure of effectiveness. In 5-fold cross-validation tests, our method had a higher testing accuracy (mean AUC 0.9696; mean F-measure 0.9086) than traditional NLP-based approaches (mean AUC range 0.8183-0.9571; mean F-measure range 0.5050-0.8739). A real-world simulation that split the training sample and the testing sample by date verified this result (mean AUC 0.9645; mean F-measure 0.9003 using the proposed method). Further analysis showed that the convolutional layers of the CNN effectively identified a large number of keywords and automatically
We discuss the thesis that the implementation of a moral code in the behaviour of artificial intelligent systems needs a specific form of human and artificial intelligence, not just an abstract intelligence. We present intelligence as a system with an internal structure and the structural levels of the moral system, as well as certain characteristics of artificial intelligent agents which can/must be treated as 1- individual entities (with a complex, specialized, autonomous or selfdetermined,...
Full Text Available Different species inhabit different sensory worlds and thus have evolved diverse means of processing information, learning and memory. In the escalated arms race with host defense, each pathogenic bacterium not only has evolved its individual cellular sensing and behaviour, but also collective sensing, interbacterial communication, distributed information processing, joint decision making, dissociative behaviour, and the phenotypic and genotypic heterogeneity necessary for epidemiologic success. Moreover, pathogenic populations take advantage of dormancy strategies and rapid evolutionary speed, which allow them to save co-generated intelligent traits in a collective genomic memory. This review discusses how these mechanisms add further levels of complexity to bacterial pathogenicity and transmission, and how mining for these mechanisms could help to develop new anti-infective strategies.
A new Reverse Monte Carlo (RMC) package "fullrmc" for atomic or rigid body and molecular, amorphous, or crystalline materials is presented. fullrmc main purpose is to provide a fully modular, fast and flexible software, thoroughly documented, complex molecules enabled, written in a modern programming language (python, cython, C and C++ when performance is needed) and complying to modern programming practices. fullrmc approach in solving an atomic or molecular structure is different from existing RMC algorithms and software. In a nutshell, traditional RMC methods and software randomly adjust atom positions until the whole system has the greatest consistency with a set of experimental data. In contrast, fullrmc applies smart moves endorsed with reinforcement machine learning to groups of atoms. While fullrmc allows running traditional RMC modeling, the uniqueness of this approach resides in its ability to customize grouping atoms in any convenient way with no additional programming efforts and to apply smart and more physically meaningful moves to the defined groups of atoms. In addition, fullrmc provides a unique way with almost no additional computational cost to recur a group's selection, allowing the system to go out of local minimas by refining a group's position or exploring through and beyond not allowed positions and energy barriers the unrestricted three dimensional space around a group. © 2016 Wiley Periodicals, Inc.
Cui, De-Mi; Yan, Weizhong; Wang, Xiao-Quan; Lu, Lie-Min
Low strain pile integrity testing (LSPIT), due to its simplicity and low cost, is one of the most popular NDE methods used in pile foundation construction. While performing LSPIT in the field is generally quite simple and quick, determining the integrity of the test piles by analyzing and interpreting the test signals (reflectograms) is still a manual process performed by experienced experts only. For foundation construction sites where the number of piles to be tested is large, it may take days before the expert can complete interpreting all of the piles and delivering the integrity assessment report. Techniques that can automate test signal interpretation, thus shortening the LSPIT's turnaround time, are of great business value and are in great need. Motivated by this need, in this paper, we develop a computer-aided reflectogram interpretation (CARI) methodology that can interpret a large number of LSPIT signals quickly and consistently. The methodology, built on advanced signal processing and machine learning technologies, can be used to assist the experts in performing both qualitative and quantitative interpretation of LSPIT signals. Specifically, the methodology can ease experts' interpretation burden by screening all test piles quickly and identifying a small number of suspected piles for experts to perform manual, in-depth interpretation. We demonstrate the methodology's effectiveness using the LSPIT signals collected from a number of real-world pile construction sites. The proposed methodology can potentially enhance LSPIT and make it even more efficient and effective in quality control of deep foundation construction.
Proceedings of the 2015 Chinese Intelligent Automation Conference presents selected research papers from the CIAC’15, held in Fuzhou, China. The topics include adaptive control, fuzzy control, neural network based control, knowledge based control, hybrid intelligent control, learning control, evolutionary mechanism based control, multi-sensor integration, failure diagnosis, reconfigurable control, etc. Engineers and researchers from academia, industry and the government can gain valuable insights into interdisciplinary solutions in the field of intelligent automation.
Baratta Posada, Ana Elisa
Semiotic paradigm and Carspecken's (1996) critical ethnography were used in a qualitative research study of elementary teachers' beliefs about minority and Latino/a immigrant students and the role of life experiences, culture and Umwelt in the formation and influence of beliefs. The participants were a kindergarten, first grade, and second grade…
Duguay, Annie Laurie
A growing body of literature suggests that language proficiency in the main language of the destination country is one of the most significant factors in the integration of immigrants. This study examines the overall differences in U.S. and Canadian settlement policy, using the provision of language courses as a specific example of the ways in…
To say that immigration is currently a controversial issue would be an understatement. The media is rife with misinformation and does a very poor job of making the critical distinction between legal and illegal immigration. Because of this, it is vitally important that libraries provide students with clear and unbiased material on the topic. In…
Andersson, Fredrik; García-Pérez, Mónica; Haltiwanger, John; McCue, Kristin; Sanders, Seth
Casual observation suggests that in most U.S. urban labor markets, immigrants have more immigrant coworkers than native-born workers do. While seeming obvious, this excess tendency to work together has not been precisely measured, nor have its sources been quantified. Using matched employer–employee data from the U.S. Census Bureau Longitudinal Employer-Household Dynamics (LEHD) database on a set of metropolitan statistical areas (MSAs) with substantial immigrant populations, we find that, on average, 37% of an immigrant’s coworkers are themselves immigrants; in contrast, only 14% of a native-born worker’s coworkers are immigrants. We decompose this difference into the probability of working with compatriots versus with immigrants from other source countries. Using human capital, employer, and location characteristics, we narrow the mechanisms that might explain immigrant concentration. We find that industry, language, and residential segregation collectively explain almost all the excess tendency to work with immigrants from other source countries, but they have limited power to explain work with compatriots. This large unexplained compatriot component suggests an important role for unmeasured country-specific factors, such as social networks. PMID:25425452
Given the increased number of immigrants worldwide, the determinants of immigration and the social and economic integration of immigrants into the countries of destination are of particular importance. The contributions of this dissertation address the determinants of immigration by looking at the
van Ours, J.C.; Veenman, J.M.C.
For immigrants who arrive in a country at a young age it is easier to assimilate than for teenagers.This paper investigates up to what immigration age the educational attainment of young immigrants in the Netherlands is similar to the educational attainment of secondgeneration immigrants, who were
Dinesen, Peter Thisted; Klemmensen, Robert; Nørgaard, Asbjørn Sonne
This article examines if deep-seated psychological differences add to the explanation of attitudes toward immigration. We explore whether the Big Five personality traits matter for immigration attitudes beyond the traditional situational factors of economic and cultural threat and analyze how...... individuals with different personalities react when confronted with the same situational triggers. Using a Danish survey experiment, we show that different personality traits have different effects on opposition toward immigration. We find that Openness has an unconditional effect on attitudes toward...... high on Conscientiousness are more sensitive to the skill level of immigrants. The results imply that personality is important for attitudes toward immigration, and in the conclusion, we further discuss how the observed conditional and unconditional effects of personality make sense theoretically....
Malchow-Møller, Nikolaj; Roland Munch, Jakob; Schroll, Sanne
Denne artikel belyser holdninger til immigration blandt borgere i Danmark og de øvrige EU-15 lande - herunder holdningerne til immigration, der følger af den seneste EU-udvidelse. Det analyseres, hvilke faktorer der ligger til frund for disse holdninger, samt i hvilken udstrækning danskere afviger...... fra EU-gennemsnittet. Den typiske dansker er lidt mere skeptisk overfor immigration end andre europæere. Danskerne afskiller sig desuden ved, at forholdsvis få forbinder øget immigration med negative konsekvenser for arbejdsmarkedet, men forholdsvis mange forbinder det med højere omkostninger...... for velfærdsstaten. Når der tages hensyn til opfattelserne af de økonomiske konsekvenser af immigration, kommer Danmark til at fremstå som et væsentligt mere immigrationsskeptisk land, end hvad der kommer til udtryk i de ukorrigerede holdninger....
Malchow-Møller, Nikolaj; Munch, Jakob Roland; Schroll, Sanne
Denne artikel belyser holdninger til immigration blandt borgere i Danmark og de øvrige EU-15 lande - herunder holdningerne til immigration, der følger af den seneste EU-udvidelse. Det analyseres, hvilke faktorer der ligger til frund for disse holdninger, samt i hvilken udstrækning danskere afviger...... fra EU-gennemsnittet. Den typiske dansker er lidt mere skeptisk overfor immigration end andre europæere. Danskerne afskiller sig desuden ved, at forholdsvis få forbinder øget immigration med negative konsekvenser for arbejdsmarkedet, men forholdsvis mange forbinder det med højere omkostninger...... for velfærdsstaten. Når der tages hensyn til opfattelserne af de økonomiske konsekvenser af immigration, kommer Danmark til at fremstå som et væsentligt mere immigrationsskeptisk land, end hvad der kommer til udtryk i de ukorrigerede holdninger...
Baker, Ryan S.
The initial vision for intelligent tutoring systems involved powerful, multi-faceted systems that would leverage rich models of students and pedagogies to create complex learning interactions. But the intelligent tutoring systems used at scale today are much simpler. In this article, I present hypotheses on the factors underlying this development,…
From the late nineteenth century through 1974, France permitted immigration to furnish workers and to compensate for the low level of fertility. Intense immigration from North Africa, the economic crisis of the 1970s, and other factors led to policy changes in 1974. French immigration policy since 1974 has fluctuated between guaranteeing foreigners equal rights regardless of their religion, race, culture, or national origin, and attempting to differentiate among immigrants depending on their degree of assimilability to French culture. From 1974 to 1988, France had five different policies regarding whether to permit new immigration and what to do about illegal immigrants. In July 1984, the four major political parties unanimously supported a measure in Parliament that definitively guaranteed the stay in France of legal immigrants, whose assimilation thus assumed priority. Aid for return to the homeland was no longer to be widely offered, and immigration of unskilled workers was to be terminated except for those originating in European Community countries. Major changes of government in 1988 and 1993 affected only the modalities of applying these principles. The number of immigrants has fluctuated since 1974. Unskilled workers, the only category whose entrance was specifically controlled by the 1984 measures, have declined from 174,000 in 1970 to 25,000 in the early 1990s. The number of requests for political asylum declined from 60,000 in 1989 to 27,000 in 1993, and in 1991, 15,467 persons were granted refugee status. The number of immigrants of all types permitted to remain in France declined from 250,000 or 3000 per year in the early 1970s to around 110,000 at present. Although the decline is significant, it appears insufficient to the government in power since 1993. Although migratory flows are often explained as the product of imbalance in the labor market or in demographic growth, the French experience suggests that government policies, both in the sending and
Green, H. S.; Triffet, T.
An introductory discussion of the related concepts of intelligence and consciousness suggests criteria to be met in the modeling of intelligence and the development of intelligent materials. Methods for the modeling of actual structure and activity of the animal cortex have been found, based on present knowledge of the ionic and cellular constitution of the nervous system. These have led to the development of a realistic neural network model, which has been used to study the formation of memory and the process of learning. An account is given of experiments with simple materials which exhibit almost all properties of biological synapses and suggest the possibility of a new type of computer architecture to implement an advanced type of artificial intelligence.
Siurdyban, Artur; Møller, Charles
applied to the context of organizational processes can increase the success rate of business operations. The framework is created using a set of theoretical based constructs grounded in a discussion across several streams of research including psychology, pedagogy, artificial intelligence, learning...... of deploying inapt operations leading to deterioration of profits. To address this problem, we propose a unified business process design framework based on the paradigm of intelligence. Intelligence allows humans and human-designed systems cope with environmental volatility, and we argue that its principles......, business process management and supply chain management. It outlines a number of system tasks combined in four integrated management perspectives: build, execute, grow and innovate, put forward as business process design propositions for Intelligent Supply Chains....
Kunkel, Christine D.
This article features a school built on multiple intelligences. As the first multiple intelligences school in the world, the Key Learning Community shapes its students' days to include significant time in the musical, spatial and bodily-kinesthetic intelligences, as well as the more traditional areas of logical-mathematical and linguistics. In…
Poirot, James L.; Norris, Cathleen A.
This first in a projected series of five articles discusses artificial intelligence and its impact on education. Highlights include the history of artificial intelligence and the impact of microcomputers; learning processes; human factors and interfaces; computer assisted instruction and intelligent tutoring systems; logic programing; and expert…
Tchogovadze, Gotcha G.
Describes one way of structuring an intelligent tutoring system (ITS) in light of developments in artificial intelligence. A specialized intelligent operating system (SIOS) is proposed for software for a network of microcomputers, and it is postulated that a general learning system must be used as a basic framework for the SIOS. (Author/LRW)
Full Text Available Drawing from sociological research seeking to explain variation in attitudes toward immigrants and immigration policy, it is found that knowledge and proficiency in a language other than English is associated with more favorable views towards immigrants and towards multiculturalism in contemporary America. Alvarado reviews the literature on sociological research on immigrant attitudes, explores the nexus between foreign language learning and appreciation for foreign culture(s, and presents the methodology and analysis used to test the strength of the association between knowledge in a foreign language and favorable views towards immigrants and multiculturalism in the United States.
The claim that "skilled immigration is welcome" is often associated to the increasing adoption of selective immigration policies. I study the voting over differentiated immigration policies in a two-country, three-factor general equilibrium model where there exist skilled and unskilled workers, migration decisions are endogenous, enforcing immigration restriction is costly, and natives dislike unskilled immigration. According to my findings, decisions over border closure are made to protect t...
In the past, nativists opposed immigration, period. The sharp distinction between "legal" and "illegal" immigrants emerged fairly recently, according to immigration historian David Reimers, a professor of history at New York University. "Basically, by the mid-90s 'legal' immigration was no longer an issue," he says.…
Burnett, Sara; Kugler, Eileen Gale; Tesh, Claire
Over the past decades, U.S. immigration has changed significantly, yet the way we teach about immigration in schools has changed little. The American Immigration Council has developed a two-year program on Long Island, an area experiencing an increase of new arrivals and anti-immigrant sentiment. The program empowers teachers with the knowledge to…
Jimenez, Rosa M.
Immigration is often framed as a problem, yet it is also a time of remarkable opportunity. While immigrants come to the United States from all over the world, the author focuses on the unique and urgent issues related to Latino immigration. Immigrant Latinos have changed the face of America and U.S. schools. Approximately one in five K-12 students…
Information Technology Quarterly, 1985
This issue of "Information Technology Quarterly" is devoted to the theme of "Artificial Intelligence." It contains two major articles: (1) Artificial Intelligence and Law" (D. Peter O'Neill and George D. Wood); (2) "Artificial Intelligence: A Long and Winding Road" (John J. Simon, Jr.). In addition, it contains two sidebars: (1) "Calculating and…
Bergeron, Pierrette; Hiller, Christine A.
Reviews the evolution of competitive intelligence since 1994, including terminology and definitions and analytical techniques. Addresses the issue of ethics; explores how information technology supports the competitive intelligence process; and discusses education and training opportunities for competitive intelligence, including core competencies…
Research has extensively documented the employment barriers facing immigrants in Canada. Less attention is paid to the employment strategies that immigrants deploy in the host labour market. To address this gap in the literature, two projects are conducted to examine how immigrant women learn to optimize their labour market outcomes. Both projects…
Tynell, Lena Lyngholt; Wimmelmann, Camilla Lawaetz; Jervelund, Signe Smith
Objective: In most European countries, immigrants do not systematically learn about the host countries' healthcare system when arriving. This study investigated how newly arrived immigrants perceived the information they received about the Danish healthcare system. Methods: Immigrants attending a language school in Copenhagen in 2012 received…
Andersson Joona, Pernilla; Datta Gupta, Nabanita; Wadensjo, Eskil
The utilization and reward of the human capital of immigrants in the labor market of the host country has been studied extensively. Using Swedish register data from 2001–2008, we extend the immigrant educational mismatch literature by analyzing incidence, wage effects and state dependence...... in overeducation among natives and immigrants. In line with previous research we find a higher incidence and a lower return to overeducation among immigrants indicating that immigrants lose more from being overeducated. We find a high degree of state dependence in overeducation both among natives and immigrants......, but considerably higher among immigrants....
Murray, William R; Sams, Michelle; Belleville, Michael
This intelligent tools and instructional simulations project was an investigation into the utility of a knowledge-based performance support system to support learning and on-task performance for using...
2012 International Conference on Affective Computing and Intelligent Interaction (ICACII 2012) was the most comprehensive conference focused on the various aspects of advances in Affective Computing and Intelligent Interaction. The conference provided a rare opportunity to bring together worldwide academic researchers and practitioners for exchanging the latest developments and applications in this field such as Intelligent Computing, Affective Computing, Machine Learning, Business Intelligence and HCI. This volume is a collection of 119 papers selected from 410 submissions from universities and industries all over the world, based on their quality and relevancy to the conference. All of the papers have been peer-reviewed by selected experts.
Grzegorzewski, Przemysław; Kacprzyk, Janusz; Owsiński, Jan; Penczek, Wojciech; Zadrożny, Sławomir
This volume presents recent research, challenging problems and solutions in Intelligent Systems– covering the following disciplines: artificial and computational intelligence, fuzzy logic and other non-classic logics, intelligent database systems, information retrieval, information fusion, intelligent search (engines), data mining, cluster analysis, unsupervised learning, machine learning, intelligent data analysis, (group) decision support systems, intelligent agents and multi-agent systems, knowledge-based systems, imprecision and uncertainty handling, electronic commerce, distributed systems, etc. The book defines a common ground for sometimes seemingly disparate problems and addresses them by using the paradigm of broadly perceived intelligent systems. It presents a broad panorama of a multitude of theoretical and practical problems which have been successfully dealt with using the paradigm of intelligent computing.
George J. Borjas
Self-selection plays a dominant role in determining the size and composition of immigrant flows. The United States competes with other potential host countries in the "immigration market". Host countries vary in their "offers" of economic opportunities and also differ in the way they ration entry through their immigration policies. Potential immigrants compare the various opportunities and are non-randomly sorted by the immigration market among the various host countries. This paper presents ...
For the most part, immigrants in the United States do not have access to the very safety-net benefits supported by their taxes, nor to essential due-process rights, simply because they are not citizens or legal residents. Contemporary demographics of immigration and post-9/11 security concerns have colored our traditional hospitality as a nation of immigrants and made life more difficult for immigrants. The Catholic Church has a rich history of scriptural and social teaching that addresses the question of immigration. Stories of forced migration in the Pentateuch led to commandments regarding strangers and the responsibility to be welcoming. In the New Testament, we see that the Holy Family themselves were refugees. The Gospel of St. Matthew tells us that we will be judged by the way we respond to migrants and others in need. In Exsul Familia, Pope Pius XII reaffirms the commitment of the church to care for pilgrims, aliens, exiles, and migrants. In Ecclesia in America, Pope John Paul II states that the ultimate solution to illegal immigration is the elimination of global underdevelopment and that, in the meantime, the human rights of all migrants must be respected. In 2003, the bishops of Mexico and the United States jointly issued the pastoral letter Strangers No Longer: Together on the Journey of Hope. In this letter, the bishops say that U.S. immigration policy should protect the human rights and dignity of immigrants and asylum seekers. The bishops also offer a number of proposed public policy responses toward that end. To advance the principles contained in Strangers No Longer, the bishops have decided to mount a national campaign designed to unite and mobilize a growing network of Catholic organizations and individuals, as well as others of good faith. In addition, the campaign will seek to dispel myths and misperceptions about immigrants.
Abstract This article considers the debates surrounding the "Day Without Immigrants" protests organized in major U.S. cities on 1 May 2006, prompted by H.R. 4437, the Border Protection, Anti-Terrorism, and Illegal Immigration Control Act of 2005, from the multiple perspectives of scholars, pundits...... that the rhetoric used in these discourses pitted various class-based ethnoracial groups against each other not so much to tackle the proposed immigration bill but, rather, to comment on the ramifications of an increasingly multiracial United States. Udgivelsesdato: 01 December 2009...
Deding, Mette; Jakobsen, Vibeke; Azhar, Hussain
Four income inequality measures (Gini-coefficient, 90/10-decile ratio, and two generalized entropy indices) are applied to analyse immigrants’ income position relative to natives in a comparative perspective. Administrative data is used for Denmark, while survey data is used for Germany. We find...... higher inequality among immigrants than natives in Denmark, but vice versa for Germany. Over the period 1984-2003, this inequality gap has narrowed in both countries. At the same time, the contribution of immigrants to overall inequality has increased systematically, primarily caused by the increased...... share of immigrants in the population....
Emerson, Scott D; Carbert, Nicole S
Canada has an increasingly large immigrant population. Areas of higher immigrant density, may relate to immigrants' health through reduced acculturation to Western foods, greater access to cultural foods, and/or promotion of salubrious values/practices. It is unclear, however, whether an association exists between Canada-wide regional immigrant density and obesity among immigrants. Thus, we examined whether regional immigrant density was related to obesity, among immigrants. Adult immigrant respondents (n = 15,595) to a national population-level health survey were merged with region-level immigrant density data. Multi-level logistic regression was used to model the odds of obesity associated with increased immigrant density. The prevalence of obesity among the analytic sample was 16%. Increasing regional immigrant density was associated with lower odds of obesity among minority immigrants and long-term white immigrants. Immigrant density at the region-level in Canada may be an important contextual factor to consider when examining obesity among immigrants.
Vilstrup Pedersen, Klaus
.e. local guidelines. From a knowledge management point of view, this externalization of generalized processes, gives the opportunity to learn from, evaluate and optimize the processes. "Clinical Process Intelligence" (CPI), will denote the goal of getting generalized insight into patient centered health...
Rønn, Kira Vrist
Questions concerning what constitutes a morally justified conduct of intelligence activities have received increased attention in recent decades. However, intelligence ethics is not yet homogeneous or embedded as a solid research field. The aim of this article is to sketch the state of the art...... of intelligence ethics and point out subjects for further scrutiny in future research. The review clusters the literature on intelligence ethics into two groups: respectively, contributions on external topics (i.e., the accountability of and the public trust in intelligence agencies) and internal topics (i.......e., the search for an ideal ethical framework for intelligence actions). The article concludes that there are many holes to fill for future studies on intelligence ethics both in external and internal discussions. Thus, the article is an invitation – especially, to moral philosophers and political theorists...
Kassahun, Yohannes; Yu, Bingbin; Tibebu, Abraham Temesgen; Stoyanov, Danail; Giannarou, Stamatia; Metzen, Jan Hendrik; Vander Poorten, Emmanuel
Advances in technology and computing play an increasingly important role in the evolution of modern surgical techniques and paradigms. This article reviews the current role of machine learning (ML) techniques in the context of surgery with a focus on surgical robotics (SR). Also, we provide a perspective on the future possibilities for enhancing the effectiveness of procedures by integrating ML in the operating room. The review is focused on ML techniques directly applied to surgery, surgical robotics, surgical training and assessment. The widespread use of ML methods in diagnosis and medical image computing is beyond the scope of the review. Searches were performed on PubMed and IEEE Explore using combinations of keywords: ML, surgery, robotics, surgical and medical robotics, skill learning, skill analysis and learning to perceive. Studies making use of ML methods in the context of surgery are increasingly being reported. In particular, there is an increasing interest in using ML for developing tools to understand and model surgical skill and competence or to extract surgical workflow. Many researchers begin to integrate this understanding into the control of recent surgical robots and devices. ML is an expanding field. It is popular as it allows efficient processing of vast amounts of data for interpreting and real-time decision making. Already widely used in imaging and diagnosis, it is believed that ML will also play an important role in surgery and interventional treatments. In particular, ML could become a game changer into the conception of cognitive surgical robots. Such robots endowed with cognitive skills would assist the surgical team also on a cognitive level, such as possibly lowering the mental load of the team. For example, ML could help extracting surgical skill, learned through demonstration by human experts, and could transfer this to robotic skills. Such intelligent surgical assistance would significantly surpass the state of the art in surgical
Describes Newcomers Entering Teaching, a program designed by the Portland (Maine) Public Schools to prepare recent immigrants and refugees to enter local university's 9-month teacher-certification program. (PKP)
Liberal nationalists such as David Miller and Will Kymlicka have claimed that liberal principles have implausible implications with regard to the issue of immigration. They hold that nationality should play a normative role in this regard, and that this is necessary in order to justify restrictions...... on immigration. The present chapter discusses the envisaged role for considerations of nationality with regard to admission and residence, and examines the actual implications of arguments advanced by liberal nationalists as to why nationality should play this role. It is argued that the connection between...... nationality and immigration on liberal nationalist premises is not as straightforward as one might expect, and that the addition of considerations of nationality to liberal principles makes no practical difference with regard to reasons for restricting immigration or criteria of selection among applicants...
Diana Virginia Todea
Full Text Available In this paper I investigate the libertarian account of immigration. In the first section I distinguish between right-libertarianism and left-libertarianism. In the second section I analyze the arguments focused on immigration from the perspective of self-ownership focused on Nozick’s case and Steiner’s analogy. In the third section I discuss the conflict between the collective consent on the issue of immigration and the individuals’ decision. The conclusion sets the libertarian framework as being flawed in its argumentation on the issue of immigration because it fails to provide strong arguments about the fact that the individuals are free to choose to open or close the borders.
Foged, Mette; Peri, Giovanni
Using a database that includes the universe of individuals and establishments in Denmark over the period 1991-2008 we analyze the effect of a large inflow of non-European (EU) immigrants on Danish workers. We first identify a sharp and sustained supply-driven increase in the inflow of non......-EU immigrants in Denmark, beginning in 1995 and driven by a sequence of international events such as the Bosnian, Somalian and Iraqi crises. We then look at the response of occupational complexity, job upgrading and downgrading, wage and employment of natives in the short and long run. We find...... that the increased supply of non-EU low skilled immigrants pushed native workers to pursue more complex occupations. This reallocation happened mainly through movement across firms. Immigration increased mobility of natives across firms and across municipalities but it did not increase their probability...
Galloway, Taryn Ann; Gustafsson, Björn; Pedersen, Peder J.
Immigrant and native child poverty in Denmark, Norway, and Sweden 1993–2001 is studied using large sets of panel data. While native children face yearly poverty risks of less than 10 percent in all three countries and for all years studied the increasing proportion of immigrant children...... with an origin in middle- and low-income countries have poverty risks that vary from 38 up to as much as 58 percent. At the end of the observation period, one third of the poor children in Norway and as high as about a half in Denmark and in Sweden are of immigrant origin. The strong overrepresentation...... of immigrant children from low- and middle-income countries when measured in yearly data is also found when applying a longer accounting period for poverty measurement. We find that child poverty rates are generally high shortly after arrival to the new country and typically decrease with years since...
Cet article présente une approche systémique du concept d’intelligence naturelle en ayant pour objectif de créer une intelligence artificielle. Ainsi, l’intelligence naturelle, humaine et animale non-humaine, est une fonction composée de facultés permettant de connaître et de comprendre. De plus, l'intelligence naturelle reste indissociable de la structure, à savoir les organes du cerveau et du corps. La tentation est grande de doter les systèmes informatiques d’une intelligence artificielle ...
Matt S. Whitt
Joseph H. Carens. The Ethics of Immigration(Oxford: Oxford University Press, 2013). 384 pages. ISBN 9780199933839. US$35 (Hardback).When philosophers and political theorists turn their attention to migration, they often prioritize general normative commitments, giving only secondary concern to whether these commitments are reflected in policy. As a result, pressing issues affecting the status, rights, and life-chances of immigrants can get lost in abstract debates over the right of states to ...
Full Text Available Opinion surveys on attitudes towards immigration are becoming more and more important, owing to the increasing role of political debate on migration issues in Western European countries. CNR has conducted four surveys on this topic, collecting data on the evolution of Italians attitudes towards migration issues. In fact, the ? rst survey was conducted in the second half of the eighties, when foreign immigration was in its early stages. The last survey took place in 2002, when immigration was already well established in Italy. The article focuses on three main issues: the global impact of immigration on Italian society, the immigrants role in the labour market, and immigration policy. In general, the results of the last survey con? rm a trend that appeared already in 1997, of more balanced and realistic opinion that were less of a response to circumstances perceived as special emergencies. Highly educated people, teachers and students continue to be the most open and receptive groups, whereas the less favourably inclined and more worried continue to be old people, those with less education, the unemployed, housewives, and retirees.
VanLehn, Kurt; Wetzel, Jon; Grover, Sachin; van de Sande, Brett
Constructing models of dynamic systems is an important skill in both mathematics and science instruction. However, it has proved difficult to teach. Dragoon is an intelligent tutoring system intended to quickly and effectively teach this important skill. This paper describes Dragoon and an evaluation of it. The evaluation randomly assigned…
This study examined teachers' use of the Multiple Intelligences Theory on vocabulary acquisition by preschoolers during English as a second language (ESL) classes in a K-12 school in Lebanon. Eighty kindergartners (KG II, aged 5 years) and eight teachers constituted the sample. The study used mixed methods, including observations of videotaped…
Bruin, de R.; Lu, Y.; Brombacher, A.C.; Smith, M.J.; Salvendy, G.
A growing number of products - particularly highly innovative and intelligent products - are being returned by customers, while analysis shows that many of these products are in fact functioning according to their technical specifications. Product developers are recognizing the need for information
María C. Vega-Hernández
Full Text Available Recent studies have revealed that emotional competences are relevant to the student’s learning process and, more specifically, in the use of learning strategies (LSs. The aim of this study is twofold. First, we aim to analyze the relationship between perceived emotional intelligence (PEI and LSs applying the scales TMMS-24 and Abridged ACRA to a sample of 2334 Spanish university students, whilst also exploring possible gender differences. Second, we aim to propose a methodological alternative based on the Canonical non-symmetrical correspondence analysis (CNCA, as an alternative to the methods traditionally used in Psychology and Education. Our results show that PEI has an impact on the LS of the students. Male participants with high scores on learning support strategies are positively related to high attention, clarity, and emotional repair. However, the use of cognitive and control LS is related to low values on the PEI dimensions. For women, high scores on cognitive, control, and learning support LS are related to high emotional attention, whereas dimensions such as study habits and learning support are related to adequate emotional repair. Participants in the 18–19 and 22–23 years age groups showed similar behavior. High scores on learning support strategies are related to high values on three dimensions of the PEI, and high values of study habits show high values for clarity and low values for attention and repair. The 20–21 and older than 24 years age groups behaved similarly. High scores on learning support strategies are related to low values on clarity, and study habits show high values for clarity and repair. This article presents the relationship between PEI and LS in university students, the differences by gender and age, and CNCA as an alternative method to techniques used in this field to study this association.
Vega-Hernández, María C; Patino-Alonso, María C; Cabello, Rosario; Galindo-Villardón, María P; Fernández-Berrocal, Pablo
Recent studies have revealed that emotional competences are relevant to the student's learning process and, more specifically, in the use of learning strategies (LSs). The aim of this study is twofold. First, we aim to analyze the relationship between perceived emotional intelligence (PEI) and LSs applying the scales TMMS-24 and Abridged ACRA to a sample of 2334 Spanish university students, whilst also exploring possible gender differences. Second, we aim to propose a methodological alternative based on the Canonical non-symmetrical correspondence analysis (CNCA), as an alternative to the methods traditionally used in Psychology and Education. Our results show that PEI has an impact on the LS of the students. Male participants with high scores on learning support strategies are positively related to high attention, clarity, and emotional repair. However, the use of cognitive and control LS is related to low values on the PEI dimensions. For women, high scores on cognitive, control, and learning support LS are related to high emotional attention, whereas dimensions such as study habits and learning support are related to adequate emotional repair. Participants in the 18-19 and 22-23 years age groups showed similar behavior. High scores on learning support strategies are related to high values on three dimensions of the PEI, and high values of study habits show high values for clarity and low values for attention and repair. The 20-21 and older than 24 years age groups behaved similarly. High scores on learning support strategies are related to low values on clarity, and study habits show high values for clarity and repair. This article presents the relationship between PEI and LS in university students, the differences by gender and age, and CNCA as an alternative method to techniques used in this field to study this association.
Full Text Available Vietnamese and East European immigrants face similar obstacles in the U.S. labor market. This provides for an interesting test of racial discrimination in the labor market. Does it make any difference if an immigrant is Asian or White? When Vietnamese immigrants are compared to East European immigrants, Vietnamese men earn 7-9% less than comparable East European men, with more discrimination among the less educated, and in the larger Vietnamese population centers like California. Vietnamese women earn as much as comparable East European women. Vietnamese immigrants, male and female, are much less likely to hold managerial and supervisory positions than comparable East European immigrants.
Full Text Available Vietnamese and East European immigrants face similar obstacles in the US labor market. This provides for an interesting test of racial discrimination in the labor market. Does it make any difference if an immigrant is Asian or White? When Vietnamese immigrants are compared to East European immigrants, Vietnamese men earn 7-9% less than comparable East European men, with more discrimination among the less educated, and in the larger Vietnamese population centers like California. Vietnamese women earn as much as comparable East European women. Vietnamese immigrants, male and female, are much less likely to hold managerial and supervisory positions than comparable East European immigrants.
An ITS (Intelligent Tutoring System) is a teaching-learning medium that uses artificial intelligence (AI) technology for instruction. Roberts and Park (1983) defines AI as the attempt to get computers to perform tasks that if performed by a human-being, intelligence would be required to perform the task. The design of an ITS comprises two distinct…
Winston, Patrick H.
The primary goal of the Artificial Intelligence Laboratory is to understand how computers can be made to exhibit intelligence. Two corollary goals are to make computers more useful and to understand certain aspects of human intelligence. Current research includes work on computer robotics and vision, expert systems, learning and commonsense reasoning, natural language understanding, and computer architecture.