Marshall, Thomas; Champagne-Langabeer, Tiffiany; Castelli, Darla; Hoelscher, Deanna
2017-12-01
To present research models based on artificial intelligence and discuss the concept of cognitive computing and eScience as disruptive factors in health and life science research methodologies. The paper identifies big data as a catalyst to innovation and the development of artificial intelligence, presents a framework for computer-supported human problem solving and describes a transformation of research support models. This framework includes traditional computer support; federated cognition using machine learning and cognitive agents to augment human intelligence; and a semi-autonomous/autonomous cognitive model, based on deep machine learning, which supports eScience. The paper provides a forward view of the impact of artificial intelligence on our human-computer support and research methods in health and life science research. By augmenting or amplifying human task performance with artificial intelligence, cognitive computing and eScience research models are discussed as novel and innovative systems for developing more effective adaptive obesity intervention programs.
Cognitive Correlates of Performance in Algorithms in a Computer Science Course for High School
ERIC Educational Resources Information Center
Avancena, Aimee Theresa; Nishihara, Akinori
2014-01-01
Computer science for high school faces many challenging issues. One of these is whether the students possess the appropriate cognitive ability for learning the fundamentals of computer science. Online tests were created based on known cognitive factors and fundamental algorithms and were implemented among the second grade students in the…
2005-12-01
Computational Learning in the Department of Brain & Cognitive Sciences and in the Computer Science and Artificial Intelligence Laboratory at the Massachusetts...physiology and cognitive science . . . . . . . . . . . . . . . . . . . . . 67 2 CONTENTS A Appendices 68 A.1 Detailed model implementation and...physiol- ogy to cognitive science. The original model [Riesenhuber and Poggio, 1999b] made also a few predictions ranging from biophysics to psychophysics
The tractable cognition thesis.
Van Rooij, Iris
2008-09-01
The recognition that human minds/brains are finite systems with limited resources for computation has led some researchers to advance the Tractable Cognition thesis: Human cognitive capacities are constrained by computational tractability. This thesis, if true, serves cognitive psychology by constraining the space of computational-level theories of cognition. To utilize this constraint, a precise and workable definition of "computational tractability" is needed. Following computer science tradition, many cognitive scientists and psychologists define computational tractability as polynomial-time computability, leading to the P-Cognition thesis. This article explains how and why the P-Cognition thesis may be overly restrictive, risking the exclusion of veridical computational-level theories from scientific investigation. An argument is made to replace the P-Cognition thesis by the FPT-Cognition thesis as an alternative formalization of the Tractable Cognition thesis (here, FPT stands for fixed-parameter tractable). Possible objections to the Tractable Cognition thesis, and its proposed formalization, are discussed, and existing misconceptions are clarified. 2008 Cognitive Science Society, Inc.
Information processing, computation, and cognition.
Piccinini, Gualtiero; Scarantino, Andrea
2011-01-01
Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both - although others disagree vehemently. Yet different cognitive scientists use 'computation' and 'information processing' to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In this paper, we address this unsatisfactory state of affairs by presenting a general and theory-neutral account of computation and information processing. We also apply our framework by analyzing the relations between computation and information processing on one hand and classicism, connectionism, and computational neuroscience on the other. We defend the relevance to cognitive science of both computation, at least in a generic sense, and information processing, in three important senses of the term. Our account advances several foundational debates in cognitive science by untangling some of their conceptual knots in a theory-neutral way. By leveling the playing field, we pave the way for the future resolution of the debates' empirical aspects.
Cognitive Model Exploration and Optimization: A New Challenge for Computational Science
2010-01-01
Introduction Research in cognitive science often involves the generation and analysis of computational cognitive models to explain various...HPC) clusters and volunteer computing for large-scale computational resources. The majority of applications on the Department of Defense HPC... clusters focus on solving partial differential equations (Post, 2009). These tend to be lean, fast models with little noise. While we lack specific
Bechtel, William; Abrahamsen, Adele
2010-09-01
We consider computational modeling in two fields: chronobiology and cognitive science. In circadian rhythm models, variables generally correspond to properties of parts and operations of the responsible mechanism. A computational model of this complex mechanism is grounded in empirical discoveries and contributes a more refined understanding of the dynamics of its behavior. In cognitive science, on the other hand, computational modelers typically advance de novo proposals for mechanisms to account for behavior. They offer indirect evidence that a proposed mechanism is adequate to produce particular behavioral data, but typically there is no direct empirical evidence for the hypothesized parts and operations. Models in these two fields differ in the extent of their empirical grounding, but they share the goal of achieving dynamic mechanistic explanation. That is, they augment a proposed mechanistic explanation with a computational model that enables exploration of the mechanism's dynamics. Using exemplars from circadian rhythm research, we extract six specific contributions provided by computational models. We then examine cognitive science models to determine how well they make the same types of contributions. We suggest that the modeling approach used in circadian research may prove useful in cognitive science as researchers develop procedures for experimentally decomposing cognitive mechanisms into parts and operations and begin to understand their nonlinear interactions.
ERIC Educational Resources Information Center
van Merrienboer, Jeroen J. G.
The contributions of instructional design to cognitive science are discussed. It is argued that both sciences have their own object of study, but share a common interest in human cognition and performance as part of instructional systems. From a case study based on experience in teaching introductory computer programming, it is concluded that both…
Information processing, computation, and cognition
Scarantino, Andrea
2010-01-01
Computation and information processing are among the most fundamental notions in cognitive science. They are also among the most imprecisely discussed. Many cognitive scientists take it for granted that cognition involves computation, information processing, or both – although others disagree vehemently. Yet different cognitive scientists use ‘computation’ and ‘information processing’ to mean different things, sometimes without realizing that they do. In addition, computation and information processing are surrounded by several myths; first and foremost, that they are the same thing. In this paper, we address this unsatisfactory state of affairs by presenting a general and theory-neutral account of computation and information processing. We also apply our framework by analyzing the relations between computation and information processing on one hand and classicism, connectionism, and computational neuroscience on the other. We defend the relevance to cognitive science of both computation, at least in a generic sense, and information processing, in three important senses of the term. Our account advances several foundational debates in cognitive science by untangling some of their conceptual knots in a theory-neutral way. By leveling the playing field, we pave the way for the future resolution of the debates’ empirical aspects. PMID:22210958
Cognitive Enhancement and Education
ERIC Educational Resources Information Center
Buchanan, Allen
2011-01-01
Cognitive enhancement--augmenting normal cognitive capacities--is not new. Literacy, numeracy, computers, and the practices of science are all cognitive enhancements. Science is now making new cognitive enhancements possible. Biomedical cognitive enhancements (BCEs) include the administration of drugs, implants of genetically engineered or…
Computational modeling in cognitive science: a manifesto for change.
Addyman, Caspar; French, Robert M
2012-07-01
Computational modeling has long been one of the traditional pillars of cognitive science. Unfortunately, the computer models of cognition being developed today have not kept up with the enormous changes that have taken place in computer technology and, especially, in human-computer interfaces. For all intents and purposes, modeling is still done today as it was 25, or even 35, years ago. Everyone still programs in his or her own favorite programming language, source code is rarely made available, accessibility of models to non-programming researchers is essentially non-existent, and even for other modelers, the profusion of source code in a multitude of programming languages, written without programming guidelines, makes it almost impossible to access, check, explore, re-use, or continue to develop. It is high time to change this situation, especially since the tools are now readily available to do so. We propose that the modeling community adopt three simple guidelines that would ensure that computational models would be accessible to the broad range of researchers in cognitive science. We further emphasize the pivotal role that journal editors must play in making computational models accessible to readers of their journals. Copyright © 2012 Cognitive Science Society, Inc.
ERIC Educational Resources Information Center
Avancena, Aimee Theresa; Nishihara, Akinori; Vergara, John Paul
2012-01-01
This paper presents the online cognitive and algorithm tests, which were developed in order to determine if certain cognitive factors and fundamental algorithms correlate with the performance of students in their introductory computer science course. The tests were implemented among Management Information Systems majors from the Philippines and…
Education, Information Technology and Cognitive Science.
ERIC Educational Resources Information Center
Scaife, M.
1989-01-01
Discusses information technology and its effects on developmental psychology and children's education. Topics discussed include a theory of child-computer interaction (CCI); programing; communication and computers, including electronic mail; cognitive science; artificial intelligence; modeling the user-system interaction; and the future of…
Role of cognitive assessment for high school graduates prior to choosing their college major.
AlAbdulwahab, Sami S; Kachanathu, Shaji John; AlSaeed, Abdullah Saad
2018-02-01
[Purpose] Academic performance of college students can be impacted by the efficacy of students' ability and teaching methods. It is important to assess the progression of college students' cognitive abilities among different college majors and as they move from junior to senior levels. However, dearth of studies have been examined the role of cognitive ability tests as a tool to determine the aptitude of the perspective students. Therefore, this study assessed cognitive abilities of computer science and ART students. [Subjects and Methods] Participants were 130 college students (70 computer and 60 art students) in their first and final years of study at King Saud University. Cognitive ability was assessed using the Test of Nonverbal Intelligence, Third Edition. [Results] The cognitive ability of computer science students were statistically better than that of art students and were shown improvement from junior to senior levels, while the cognitive ability of art students did not. [Conclusion] The cognitive ability of computer science college students was superior compared to those in art, indicating the importance of cognitive ability assessment for high school graduates prior to choosing a college major. Cognitive scales should be included as an aptitude assessment tool for decision-makers and prospective students to determine an appropriate career, which might reduce the rate of university drop out.
Empirical Determination of Competence Areas to Computer Science Education
ERIC Educational Resources Information Center
Zendler, Andreas; Klaudt, Dieter; Seitz, Cornelia
2014-01-01
The authors discuss empirically determined competence areas to K-12 computer science education, emphasizing the cognitive level of competence. The results of a questionnaire with 120 professors of computer science serve as a database. By using multi-dimensional scaling and cluster analysis, four competence areas to computer science education…
Cognitive science as an interface between rational and mechanistic explanation.
Chater, Nick
2014-04-01
Cognitive science views thought as computation; and computation, by its very nature, can be understood in both rational and mechanistic terms. In rational terms, a computation solves some information processing problem (e.g., mapping sensory information into a description of the external world; parsing a sentence; selecting among a set of possible actions). In mechanistic terms, a computation corresponds to causal chain of events in a physical device (in engineering context, a silicon chip; in biological context, the nervous system). The discipline is thus at the interface between two very different styles of explanation--as the papers in the current special issue well illustrate, it explores the interplay of rational and mechanistic forces. Copyright © 2014 Cognitive Science Society, Inc.
Cognitive Model Exploration and Optimization: A New Challenge for Computational Science
2010-03-01
the generation and analysis of computational cognitive models to explain various aspects of cognition. Typically the behavior of these models...computational scale of a workstation, so we have turned to high performance computing (HPC) clusters and volunteer computing for large-scale...computational resources. The majority of applications on the Department of Defense HPC clusters focus on solving partial differential equations (Post
Why cognitive science needs philosophy and vice versa.
Thagard, Paul
2009-04-01
Contrary to common views that philosophy is extraneous to cognitive science, this paper argues that philosophy has a crucial role to play in cognitive science with respect to generality and normativity. General questions include the nature of theories and explanations, the role of computer simulation in cognitive theorizing, and the relations among the different fields of cognitive science. Normative questions include whether human thinking should be Bayesian, whether decision making should maximize expected utility, and how norms should be established. These kinds of general and normative questions make philosophical reflection an important part of progress in cognitive science. Philosophy operates best, however, not with a priori reasoning or conceptual analysis, but rather with empirically informed reflection on a wide range of findings in cognitive science. Copyright © 2009 Cognitive Science Society, Inc.
Sign use and cognition in automated scientific discovery: are computers only special kinds of signs?
NASA Astrophysics Data System (ADS)
Giza, Piotr
2018-04-01
James Fetzer criticizes the computational paradigm, prevailing in cognitive science by questioning, what he takes to be, its most elementary ingredient: that cognition is computation across representations. He argues that if cognition is taken to be a purposive, meaningful, algorithmic problem solving activity, then computers are incapable of cognition. Instead, they appear to be signs of a special kind, that can facilitate computation. He proposes the conception of minds as semiotic systems as an alternative paradigm for understanding mental phenomena, one that seems to overcome the difficulties of computationalism. Now, I argue, that with computer systems dealing with scientific discovery, the matter is not so simple as that. The alleged superiority of humans using signs to stand for something other over computers being merely "physical symbol systems" or "automatic formal systems" is only easy to establish in everyday life, but becomes far from obvious when scientific discovery is at stake. In science, as opposed to everyday life, the meaning of symbols is, apart from very low-level experimental investigations, defined implicitly by the way the symbols are used in explanatory theories or experimental laws relevant to the field, and in consequence, human and machine discoverers are much more on a par. Moreover, the great practical success of the genetic programming method and recent attempts to apply it to automatic generation of cognitive theories seem to show, that computer systems are capable of very efficient problem solving activity in science, which is neither purposive nor meaningful, nor algorithmic. This, I think, undermines Fetzer's argument that computer systems are incapable of cognition because computation across representations is bound to be a purposive, meaningful, algorithmic problem solving activity.
Griffiths, Thomas L; Lieder, Falk; Goodman, Noah D
2015-04-01
Marr's levels of analysis-computational, algorithmic, and implementation-have served cognitive science well over the last 30 years. But the recent increase in the popularity of the computational level raises a new challenge: How do we begin to relate models at different levels of analysis? We propose that it is possible to define levels of analysis that lie between the computational and the algorithmic, providing a way to build a bridge between computational- and algorithmic-level models. The key idea is to push the notion of rationality, often used in defining computational-level models, deeper toward the algorithmic level. We offer a simple recipe for reverse-engineering the mind's cognitive strategies by deriving optimal algorithms for a series of increasingly more realistic abstract computational architectures, which we call "resource-rational analysis." Copyright © 2015 Cognitive Science Society, Inc.
Visual analytics as a translational cognitive science.
Fisher, Brian; Green, Tera Marie; Arias-Hernández, Richard
2011-07-01
Visual analytics is a new interdisciplinary field of study that calls for a more structured scientific approach to understanding the effects of interaction with complex graphical displays on human cognitive processes. Its primary goal is to support the design and evaluation of graphical information systems that better support cognitive processes in areas as diverse as scientific research and emergency management. The methodologies that make up this new field are as yet ill defined. This paper proposes a pathway for development of visual analytics as a translational cognitive science that bridges fundamental research in human/computer cognitive systems and design and evaluation of information systems in situ. Achieving this goal will require the development of enhanced field methods for conceptual decomposition of human/computer cognitive systems that maps onto laboratory studies, and improved methods for conducting laboratory investigations that might better map onto real-world cognitive processes in technology-rich environments. Copyright © 2011 Cognitive Science Society, Inc.
Building machines that adapt and compute like brains.
Kriegeskorte, Nikolaus; Mok, Robert M
2017-01-01
Building machines that learn and think like humans is essential not only for cognitive science, but also for computational neuroscience, whose ultimate goal is to understand how cognition is implemented in biological brains. A new cognitive computational neuroscience should build cognitive-level and neural-level models, understand their relationships, and test both types of models with both brain and behavioral data.
The Computational and Neural Basis of Cognitive Control: Charted Territory and New Frontiers
ERIC Educational Resources Information Center
Botvinick, Matthew M.; Cohen, Jonathan D.
2014-01-01
Cognitive control has long been one of the most active areas of computational modeling work in cognitive science. The focus on computational models as a medium for specifying and developing theory predates the PDP books, and cognitive control was not one of the areas on which they focused. However, the framework they provided has injected work on…
A Cognitive Model for Problem Solving in Computer Science
ERIC Educational Resources Information Center
Parham, Jennifer R.
2009-01-01
According to industry representatives, computer science education needs to emphasize the processes involved in solving computing problems rather than their solutions. Most of the current assessment tools used by universities and computer science departments analyze student answers to problems rather than investigating the processes involved in…
Computer Science Majors: Sex Role Orientation, Academic Achievement, and Social Cognitive Factors
ERIC Educational Resources Information Center
Brown, Chris; Garavalia, Linda S.; Fritts, Mary Lou Hines; Olson, Elizabeth A.
2006-01-01
This study examined the sex role orientations endorsed by 188 male and female students majoring in computer science, a male-dominated college degree program. The relations among sex role orientation and academic achievement and social cognitive factors influential in career decision-making self-efficacy were explored. Findings revealed that…
Cognitive Asymmetry, Computer Science Students, and Professional Programmers.
ERIC Educational Resources Information Center
Gordon, Harold W.
1990-01-01
Discussion of right brain versus left brain skills focuses on a study that compared the performances of computer science students, professional programers, and bank employees on eight tests of brain function. Results are reported which suggest that the cognitive profile may be an important indicator for success in certain occupations. (16…
ERIC Educational Resources Information Center
Flannery, Kathleen A.; Malita, Mihaela
2014-01-01
We present our case study of an interdisciplinary team project for students taking either a psychology or computer science (CS) course. The project required psychology and CS students to combine their knowledge and skills to create an online cognitive task. Each interdisciplinary project team included two psychology students who conducted library…
Complex systems and health behavior change: insights from cognitive science.
Orr, Mark G; Plaut, David C
2014-05-01
To provide proof-of-concept that quantum health behavior can be instantiated as a computational model that is informed by cognitive science, the Theory of Reasoned Action, and quantum health behavior theory. We conducted a synthetic review of the intersection of quantum health behavior change and cognitive science. We conducted simulations, using a computational model of quantum health behavior (a constraint satisfaction artificial neural network) and tested whether the model exhibited quantum-like behavior. The model exhibited clear signs of quantum-like behavior. Quantum health behavior can be conceptualized as constraint satisfaction: a mitigation between current behavioral state and the social contexts in which it operates. We outlined implications for moving forward with computational models of both quantum health behavior and health behavior in general.
Cognitive Computational Neuroscience: A New Conference for an Emerging Discipline.
Naselaris, Thomas; Bassett, Danielle S; Fletcher, Alyson K; Kording, Konrad; Kriegeskorte, Nikolaus; Nienborg, Hendrikje; Poldrack, Russell A; Shohamy, Daphna; Kay, Kendrick
2018-05-01
Understanding the computational principles that underlie complex behavior is a central goal in cognitive science, artificial intelligence, and neuroscience. In an attempt to unify these disconnected communities, we created a new conference called Cognitive Computational Neuroscience (CCN). The inaugural meeting revealed considerable enthusiasm but significant obstacles remain. Copyright © 2018 Elsevier Ltd. All rights reserved.
Let's Use Cognitive Science to Create Collaborative Workstations.
Reicher, Murray A; Wolfe, Jeremy M
2016-05-01
When informed by an understanding of cognitive science, radiologists' workstations could become collaborative to improve radiologists' performance and job satisfaction. The authors review relevant literature and present several promising areas of research, including image toggling, eye tracking, cognitive computing, intelligently restricted messaging, work habit tracking, and innovative input devices. The authors call for more research in "perceptual design," a promising field that can complement advances in computer-aided detection. Copyright © 2016 American College of Radiology. Published by Elsevier Inc. All rights reserved.
Representing, Running, and Revising Mental Models: A Computational Model
ERIC Educational Resources Information Center
Friedman, Scott; Forbus, Kenneth; Sherin, Bruce
2018-01-01
People use commonsense science knowledge to flexibly explain, predict, and manipulate the world around them, yet we lack computational models of how this commonsense science knowledge is represented, acquired, utilized, and revised. This is an important challenge for cognitive science: Building higher order computational models in this area will…
NASA Astrophysics Data System (ADS)
Fitch, W. Tecumseh
2014-09-01
Progress in understanding cognition requires a quantitative, theoretical framework, grounded in the other natural sciences and able to bridge between implementational, algorithmic and computational levels of explanation. I review recent results in neuroscience and cognitive biology that, when combined, provide key components of such an improved conceptual framework for contemporary cognitive science. Starting at the neuronal level, I first discuss the contemporary realization that single neurons are powerful tree-shaped computers, which implies a reorientation of computational models of learning and plasticity to a lower, cellular, level. I then turn to predictive systems theory (predictive coding and prediction-based learning) which provides a powerful formal framework for understanding brain function at a more global level. Although most formal models concerning predictive coding are framed in associationist terms, I argue that modern data necessitate a reinterpretation of such models in cognitive terms: as model-based predictive systems. Finally, I review the role of the theory of computation and formal language theory in the recent explosion of comparative biological research attempting to isolate and explore how different species differ in their cognitive capacities. Experiments to date strongly suggest that there is an important difference between humans and most other species, best characterized cognitively as a propensity by our species to infer tree structures from sequential data. Computationally, this capacity entails generative capacities above the regular (finite-state) level; implementationally, it requires some neural equivalent of a push-down stack. I dub this unusual human propensity "dendrophilia", and make a number of concrete suggestions about how such a system may be implemented in the human brain, about how and why it evolved, and what this implies for models of language acquisition. I conclude that, although much remains to be done, a neurally-grounded framework for theoretical cognitive science is within reach that can move beyond polarized debates and provide a more adequate theoretical future for cognitive biology.
Fitch, W Tecumseh
2014-09-01
Progress in understanding cognition requires a quantitative, theoretical framework, grounded in the other natural sciences and able to bridge between implementational, algorithmic and computational levels of explanation. I review recent results in neuroscience and cognitive biology that, when combined, provide key components of such an improved conceptual framework for contemporary cognitive science. Starting at the neuronal level, I first discuss the contemporary realization that single neurons are powerful tree-shaped computers, which implies a reorientation of computational models of learning and plasticity to a lower, cellular, level. I then turn to predictive systems theory (predictive coding and prediction-based learning) which provides a powerful formal framework for understanding brain function at a more global level. Although most formal models concerning predictive coding are framed in associationist terms, I argue that modern data necessitate a reinterpretation of such models in cognitive terms: as model-based predictive systems. Finally, I review the role of the theory of computation and formal language theory in the recent explosion of comparative biological research attempting to isolate and explore how different species differ in their cognitive capacities. Experiments to date strongly suggest that there is an important difference between humans and most other species, best characterized cognitively as a propensity by our species to infer tree structures from sequential data. Computationally, this capacity entails generative capacities above the regular (finite-state) level; implementationally, it requires some neural equivalent of a push-down stack. I dub this unusual human propensity "dendrophilia", and make a number of concrete suggestions about how such a system may be implemented in the human brain, about how and why it evolved, and what this implies for models of language acquisition. I conclude that, although much remains to be done, a neurally-grounded framework for theoretical cognitive science is within reach that can move beyond polarized debates and provide a more adequate theoretical future for cognitive biology. Copyright © 2014. Published by Elsevier B.V.
Multilayer Networks of Self-Interested Adaptive Units.
1987-07-01
T. J. Sejnowski. A learning algorithm for Boltzmann machines. Cognitive Science, 9:147-169, 1985. 121 S. Amarel. Problems of Representation in...Barto and C. W. Anderson. Structural learning in connectionist sys- tems. In Proceedings of the Seventh Annual Conference of the Cognitive Science...E. Hinton and T. J. Sejnowski. Analyzing cooperative computation. In Proceedings of the Fifth Annual Conference of the Cognitive Science Society
Critical thinking traits of top-tier experts and implications for computer science education
NASA Astrophysics Data System (ADS)
Bushey, Dean E.
A documented shortage of technical leadership and top-tier performers in computer science jeopardizes the technological edge, security, and economic well-being of the nation. The 2005 President's Information and Technology Advisory Committee (PITAC) Report on competitiveness in computational sciences highlights the major impact of science, technology, and innovation in keeping America competitive in the global marketplace. It stresses the fact that the supply of science, technology, and engineering experts is at the core of America's technological edge, national competitiveness and security. However, recent data shows that both undergraduate and postgraduate production of computer scientists is falling. The decline is "a quiet crisis building in the United States," a crisis that, if allowed to continue unchecked, could endanger America's well-being and preeminence among the world's nations. Past research on expert performance has shown that the cognitive traits of critical thinking, creativity, and problem solving possessed by top-tier performers can be identified, observed and measured. The studies show that the identified attributes are applicable across many domains and disciplines. Companies have begun to realize that cognitive skills are important for high-level performance and are reevaluating the traditional academic standards they have used to predict success for their top-tier performers in computer science. Previous research in the computer science field has focused either on programming skills of its experts or has attempted to predict the academic success of students at the undergraduate level. This study, on the other hand, examines the critical-thinking skills found among experts in the computer science field in order to explore the questions, "What cognitive skills do outstanding performers possess that make them successful?" and "How do currently used measures of academic performance correlate to critical-thinking skills among students?" The results of this study suggest a need to examine how critical-thinking abilities are learned in the undergraduate computer science curriculum and the need to foster these abilities in order to produce the high-level, critical-thinking professionals necessary to fill the growing need for these experts. Due to the fact that current measures of academic performance do not adequately depict students' cognitive abilities, assessment of these skills must be incorporated into existing curricula.
ERIC Educational Resources Information Center
Boyer, Kristy Elizabeth; Phillips, Robert; Wallis, Michael D.; Vouk, Mladen A.; Lester, James C.
2009-01-01
The majority of computer science education research to date has focused on purely cognitive student outcomes. Understanding the "motivational" states experienced by students may enhance our understanding of the computer science learning process, and may reveal important instructional interventions that could benefit student engagement and…
Montague, P. Read; Dolan, Raymond J.; Friston, Karl J.; Dayan, Peter
2013-01-01
Computational ideas pervade many areas of science and have an integrative explanatory role in neuroscience and cognitive science. However, computational depictions of cognitive function have had surprisingly little impact on the way we assess mental illness because diseases of the mind have not been systematically conceptualized in computational terms. Here, we outline goals and nascent efforts in the new field of computational psychiatry, which seeks to characterize mental dysfunction in terms of aberrant computations over multiple scales. We highlight early efforts in this area that employ reinforcement learning and game theoretic frameworks to elucidate decision-making in health and disease. Looking forwards, we emphasize a need for theory development and large-scale computational phenotyping in human subjects. PMID:22177032
Building Cognition: The Construction of Computational Representations for Scientific Discovery
ERIC Educational Resources Information Center
Chandrasekharan, Sanjay; Nersessian, Nancy J.
2015-01-01
Novel computational representations, such as simulation models of complex systems and video games for scientific discovery (Foldit, EteRNA etc.), are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a…
On Evaluating Human Problem Solving of Computationally Hard Problems
ERIC Educational Resources Information Center
Carruthers, Sarah; Stege, Ulrike
2013-01-01
This article is concerned with how computer science, and more exactly computational complexity theory, can inform cognitive science. In particular, we suggest factors to be taken into account when investigating how people deal with computational hardness. This discussion will address the two upper levels of Marr's Level Theory: the computational…
ERIC Educational Resources Information Center
Feinstein, Mark; Stillings, Neil
Cognitive science has recently emerged as a new interdisciplinary field incorporating parts of psychology, computer science, philosophy, neuroscience, and linguistics. Its goal is to bring the theoretical and methodological resources of the contributing disciplines to bear on an integrated investigation of thought, meaning, language, perception,…
Recchia, Gabriel L; Louwerse, Max M
2016-11-01
Computational techniques comparing co-occurrences of city names in texts allow the relative longitudes and latitudes of cities to be estimated algorithmically. However, these techniques have not been applied to estimate the provenance of artifacts with unknown origins. Here, we estimate the geographic origin of artifacts from the Indus Valley Civilization, applying methods commonly used in cognitive science to the Indus script. We show that these methods can accurately predict the relative locations of archeological sites on the basis of artifacts of known provenance, and we further apply these techniques to determine the most probable excavation sites of four sealings of unknown provenance. These findings suggest that inscription statistics reflect historical interactions among locations in the Indus Valley region, and they illustrate how computational methods can help localize inscribed archeological artifacts of unknown origin. The success of this method offers opportunities for the cognitive sciences in general and for computational anthropology specifically. Copyright © 2015 Cognitive Science Society, Inc.
Building Cognition: The Construction of Computational Representations for Scientific Discovery.
Chandrasekharan, Sanjay; Nersessian, Nancy J
2015-11-01
Novel computational representations, such as simulation models of complex systems and video games for scientific discovery (Foldit, EteRNA etc.), are dramatically changing the way discoveries emerge in science and engineering. The cognitive roles played by such computational representations in discovery are not well understood. We present a theoretical analysis of the cognitive roles such representations play, based on an ethnographic study of the building of computational models in a systems biology laboratory. Specifically, we focus on a case of model-building by an engineer that led to a remarkable discovery in basic bioscience. Accounting for such discoveries requires a distributed cognition (DC) analysis, as DC focuses on the roles played by external representations in cognitive processes. However, DC analyses by and large have not examined scientific discovery, and they mostly focus on memory offloading, particularly how the use of existing external representations changes the nature of cognitive tasks. In contrast, we study discovery processes and argue that discoveries emerge from the processes of building the computational representation. The building process integrates manipulations in imagination and in the representation, creating a coupled cognitive system of model and modeler, where the model is incorporated into the modeler's imagination. This account extends DC significantly, and we present some of the theoretical and application implications of this extended account. Copyright © 2014 Cognitive Science Society, Inc.
The Concept of Energy in Psychological Theory. Cognitive Science Program, Technical Report No. 86-2.
ERIC Educational Resources Information Center
Posner, Michael I.; Rothbart, Mary Klevjord
This paper describes a basic framework for integration of computational and energetic concepts in psychological theory. The framework is adapted from a general effort to understand the neural systems underlying cognition. The element of the cognitive system that provides the best basis for attempting to relate energetic and computational ideas is…
Report of a Workshop on the Pedagogical Aspects of Computational Thinking
ERIC Educational Resources Information Center
National Academies Press, 2011
2011-01-01
In 2008, the Computer and Information Science and Engineering Directorate of the National Science Foundation asked the National Research Council (NRC) to conduct two workshops to explore the nature of computational thinking and its cognitive and educational implications. The first workshop focused on the scope and nature of computational thinking…
Enhancing Tele-robotics with Immersive Virtual Reality
2017-11-03
graduate and undergraduate students within the Digital Gaming and Simulation, Computer Science, and psychology programs have actively collaborated...investigates the use of artificial intelligence and visual computing. Numerous fields across the human-computer interaction and gaming research areas...invested in digital gaming and simulation to cognitively stimulate humans by computers, forming a $10.5B industry [1]. On the other hand, cognitive
The emergence of cognitive hearing science.
Arlinger, Stig; Lunner, Thomas; Lyxell, Björn; Pichora-Fuller, M Kathleen
2009-10-01
Cognitive Hearing Science or Auditory Cognitive Science is an emerging field of interdisciplinary research concerning the interactions between hearing and cognition. It follows a trend over the last half century for interdisciplinary fields to develop, beginning with Neuroscience, then Cognitive Science, then Cognitive Neuroscience, and then Cognitive Vision Science. A common theme is that an interdisciplinary approach is necessary to understand complex human behaviors, to develop technologies incorporating knowledge of these behaviors, and to find solutions for individuals with impairments that undermine typical behaviors. Accordingly, researchers in traditional academic disciplines, such as Psychology, Physiology, Linguistics, Philosophy, Anthropology, and Sociology benefit from collaborations with each other, and with researchers in Computer Science and Engineering working on the design of technologies, and with health professionals working with individuals who have impairments. The factors that triggered the emergence of Cognitive Hearing Science include the maturation of the component disciplines of Hearing Science and Cognitive Science, new opportunities to use complex digital signal-processing to design technologies suited to performance in challenging everyday environments, and increasing social imperatives to help people whose communication problems span hearing and cognition. Cognitive Hearing Science is illustrated in research on three general topics: (1) language processing in challenging listening conditions; (2) use of auditory communication technologies or the visual modality to boost performance; (3) changes in performance with development, aging, and rehabilitative training. Future directions for modeling and the translation of research into practice are suggested.
NASA Astrophysics Data System (ADS)
Huppert, J.; Michal Lomask, S.; Lazarowitz, R.
2002-08-01
Computer-assisted learning, including simulated experiments, has great potential to address the problem solving process which is a complex activity. It requires a highly structured approach in order to understand the use of simulations as an instructional device. This study is based on a computer simulation program, 'The Growth Curve of Microorganisms', which required tenth grade biology students to use problem solving skills whilst simultaneously manipulating three independent variables in one simulated experiment. The aims were to investigate the computer simulation's impact on students' academic achievement and on their mastery of science process skills in relation to their cognitive stages. The results indicate that the concrete and transition operational students in the experimental group achieved significantly higher academic achievement than their counterparts in the control group. The higher the cognitive operational stage, the higher students' achievement was, except in the control group where students in the concrete and transition operational stages did not differ. Girls achieved equally with the boys in the experimental group. Students' academic achievement may indicate the potential impact a computer simulation program can have, enabling students with low reasoning abilities to cope successfully with learning concepts and principles in science which require high cognitive skills.
ERIC Educational Resources Information Center
Mayer, Richard E.
A review of the research on techniques for increasing the novice's understanding of computers and computer programming, this paper considers the potential usefulness of five tentative recommendations pertinent to the design of computer literacy curricula: (1) provide the learner with a concrete model of the computer; (2) encourage the learner to…
Toward a computational psycholinguistics of reference production.
van Deemter, Kees; Gatt, Albert; van Gompel, Roger P G; Krahmer, Emiel
2012-04-01
This article introduces the topic ''Production of Referring Expressions: Bridging the Gap between Computational and Empirical Approaches to Reference'' of the journal Topics in Cognitive Science. We argue that computational and psycholinguistic approaches to reference production can benefit from closer interaction, and that this is likely to result in the construction of algorithms that differ markedly from the ones currently known in the computational literature. We focus particularly on determinism, the feature of existing algorithms that is perhaps most clearly at odds with psycholinguistic results, discussing how future algorithms might include non-determinism, and how new psycholinguistic experiments could inform the development of such algorithms. Copyright © 2012 Cognitive Science Society, Inc.
Monaural Speech Segregation by Integrating Primitive and Schema-Based Analysis
2008-02-03
vol. 19, pp. 475-492. Wang D.L. and Chang P.S. (2008): An oscillatory correlation model of auditory streaming. Cognitive Neurodynamics , vol. 2, pp...Subcontracts DeLiang Wang (Principal Investigator) March 2008 Department of Computer Science & Engineering and Center for Cognitive Science The
Toward a Computational Model of Tutoring.
ERIC Educational Resources Information Center
Woolf, Beverly Park
1992-01-01
Discusses the integration of instructional science and computer science. Topics addressed include motivation for building knowledge-based systems; instructional design issues, including cognitive models, representing student intentions, and student models and error diagnosis; representing tutoring knowledge; building a tutoring system, including…
Understanding System of Systems Development Using an Agent-Based Wave Model
2012-01-01
Procedia Computer Science Procedia Computer Science 00 (2012) 000–000 www.elsevier.com/locate/ procedia Complex Adaptive Systems...integration of technical systems as well as cognitive and social processes, which alter system behavior [6]. As mentioned before * Corresponding...Prescribed by ANSI Std Z39-18 Acheson/ Procedia Computer Science 00 (2012) 000–000 most system architects assume that SoS participants exhibit
Computational methods to extract meaning from text and advance theories of human cognition.
McNamara, Danielle S
2011-01-01
Over the past two decades, researchers have made great advances in the area of computational methods for extracting meaning from text. This research has to a large extent been spurred by the development of latent semantic analysis (LSA), a method for extracting and representing the meaning of words using statistical computations applied to large corpora of text. Since the advent of LSA, researchers have developed and tested alternative statistical methods designed to detect and analyze meaning in text corpora. This research exemplifies how statistical models of semantics play an important role in our understanding of cognition and contribute to the field of cognitive science. Importantly, these models afford large-scale representations of human knowledge and allow researchers to explore various questions regarding knowledge, discourse processing, text comprehension, and language. This topic includes the latest progress by the leading researchers in the endeavor to go beyond LSA. Copyright © 2010 Cognitive Science Society, Inc.
Biomedical wellness challenges and opportunities
NASA Astrophysics Data System (ADS)
Tangney, John F.
2012-06-01
The mission of ONR's Human and Bioengineered Systems Division is to direct, plan, foster, and encourage Science and Technology in cognitive science, computational neuroscience, bioscience and bio-mimetic technology, social/organizational science, training, human factors, and decision making as related to future Naval needs. This paper highlights current programs that contribute to future biomedical wellness needs in context of humanitarian assistance and disaster relief. ONR supports fundamental research and related technology demonstrations in several related areas, including biometrics and human activity recognition; cognitive sciences; computational neurosciences and bio-robotics; human factors, organizational design and decision research; social, cultural and behavioral modeling; and training, education and human performance. In context of a possible future with automated casualty evacuation, elements of current science and technology programs are illustrated.
ERIC Educational Resources Information Center
Lamb, Richard L.; Firestone, Jonah B.
2017-01-01
Conflicting explanations and unrelated information in science classrooms increase cognitive load and decrease efficiency in learning. This reduced efficiency ultimately limits one's ability to solve reasoning problems in the science. In reasoning, it is the ability of students to sift through and identify critical pieces of information that is of…
Plus or Minus 30 Years in the Language Sciences
Newport, Elissa L.
2010-01-01
The language sciences – Linguistics, Psycholinguistics, and Computational Linguistics – have not been broadly represented at the Cognitive Science Society meetings of the past 30 years, but they are an important part of the heart of cognitive science. This article discusses several major themes that have dominated the controversies and consensus in the study of language and suggests the most pressing issues of the future. These themes include differences among the language science disciplines in their view of numbers and symbols and of modular and distributed cognition; and the need for an increasing prominence of questions concerning language and the brain. PMID:20730034
NASA Astrophysics Data System (ADS)
Perfors, Amy
2014-09-01
There is much to approve of in this provocative and interesting paper. I strongly agree in many parts, especially the point that dichotomies like nature/nurture are actively detrimental to the field. I also appreciate the idea that cognitive scientists should take the "biological wetware" of the cell (rather than the network) more seriously.
Computing and the social organization of academic work
NASA Astrophysics Data System (ADS)
Shields, Mark A.; Graves, William; Nyce, James M.
1992-12-01
This article discusses the academic computing movement during the 1980s. We focus on the Faculty Workstations Project at Brown University, where major computing initiatives were undertaken during the 1980s. Six departments are compared: chemistry, cognitive and linguistic sciences, geology, music, neural science, and sociology. We discuss the theoretical implications of our study for conceptualizing the relationship of computing to academic work.
A Fuzzy Evaluation Method for System of Systems Meta-architectures
2013-03-01
Procedia Computer Science Procedia Computer Science 00 (2013) 000–000 www.elsevier.com/locate/ procedia Conference on Systems Engineering...boundary includes integration of technical systems as well as cognitive and social processes, which alter system behavior [2]. Most system architects...unclassified c. THIS PAGE unclassified Standard Form 298 (Rev. 8-98) Prescribed by ANSI Std Z39-18 Pape/ Procedia Computer Science 00 (2013) 000
To naturalize or not to naturalize? An issue for cognitive science as well as anthropology.
Stenning, Keith
2012-07-01
Several of Beller, Bender, and Medin's (2012) issues are as relevant within cognitive science as between it and anthropology. Knowledge-rich human mental processes impose hermeneutic tasks, both on subjects and researchers. Psychology's current philosophy of science is ill suited to analyzing these: Its demand for ''stimulus control'' needs to give way to ''negotiation of mutual interpretation.'' Cognitive science has ways to address these issues, as does anthropology. An example from my own work is about how defeasible logics are mathematical models of some aspects of simple hermeneutic processes. They explain processing relative to databases of knowledge and belief-that is, content. A specific example is syllogistic reasoning, which raises issues of experimenters' interpretations of subjects' reasoning. Science, especially since the advent of understandings of computation, does not have to be reductive. How does this approach transfer onto anthropological topics? Recent cognitive science approaches to anthropological topics have taken a reductive stance in terms of modules. We end with some speculations about a different cognitive approach to, for example, religion. Copyright © 2012 Cognitive Science Society, Inc.
The neural and computational bases of semantic cognition.
Ralph, Matthew A Lambon; Jefferies, Elizabeth; Patterson, Karalyn; Rogers, Timothy T
2017-01-01
Semantic cognition refers to our ability to use, manipulate and generalize knowledge that is acquired over the lifespan to support innumerable verbal and non-verbal behaviours. This Review summarizes key findings and issues arising from a decade of research into the neurocognitive and neurocomputational underpinnings of this ability, leading to a new framework that we term controlled semantic cognition (CSC). CSC offers solutions to long-standing queries in philosophy and cognitive science, and yields a convergent framework for understanding the neural and computational bases of healthy semantic cognition and its dysfunction in brain disorders.
Situated Learning in Computer Science Education
ERIC Educational Resources Information Center
Ben-Ari, Mordechai
2004-01-01
Sociocultural theories of learning such as Wenger and Lave's situated learning have been suggested as alternatives to cognitive theories of learning like constructivism. This article examines situated learning within the context of computer science (CS) education. Situated learning accurately describes some CS communities like open-source software…
Palm, Günther
2016-01-01
Research in neural information processing has been successful in the past, providing useful approaches both to practical problems in computer science and to computational models in neuroscience. Recent developments in the area of cognitive neuroscience present new challenges for a computational or theoretical understanding asking for neural information processing models that fulfill criteria or constraints from cognitive psychology, neuroscience and computational efficiency. The most important of these criteria for the evaluation of present and future contributions to this new emerging field are listed at the end of this article. PMID:26858632
A Paradigm for the Next Millenium: Health Information Science.
ERIC Educational Resources Information Center
Sadler, Lewis
1991-01-01
Described is a curriculum for a new multidisciplinary science-Health Information Science-that incorporates aspects of computer science, cognitive psychology, bioengineering, biomedical visualization, medicine, dentistry, anthropology, mathematics, library science, and the visual arts. The situation of the medical illustration profession is…
Optimizing Cognitive Load for Learning from Computer-Based Science Simulations
ERIC Educational Resources Information Center
Lee, Hyunjeong; Plass, Jan L.; Homer, Bruce D.
2006-01-01
How can cognitive load in visual displays of computer simulations be optimized? Middle-school chemistry students (N = 257) learned with a simulation of the ideal gas law. Visual complexity was manipulated by separating the display of the simulations in two screens (low complexity) or presenting all information on one screen (high complexity). The…
ERIC Educational Resources Information Center
Orey, Michael A.; Nelson, Wayne A.
Arguing that the evolution of intelligent tutoring systems better reflects the recent theoretical developments of cognitive science than traditional computer-based instruction (CBI), this paper describes a general model for an intelligent tutoring system and suggests ways to improve CBI using design principles derived from research in cognitive…
Opportunities for Research on the Organizational Impact of School Computers. Technical-Report-No. 7.
ERIC Educational Resources Information Center
Newman, Denis
As computers are acquired in greater numbers in schools, their impact on the social organization of instruction increasingly becomes an issue for research. Developments in the cognitive science of instruction, drawing on sociohistorical theory, provide researchers with an appropriate theoretical approach to cultural tools and cognitive change,…
Embodiment and Human Development.
Marshall, Peter J
2016-12-01
We are recognizing increasingly that the study of cognitive, social, and emotional processes must account for their embodiment in living, acting beings. The related field of embodied cognition (EC) has coalesced around dissatisfaction with the lack of attention to the body in cognitive science. For developmental scientists, the emphasis in the literature on adult EC on the role of the body in cognition may not seem particularly novel, given that bodily action was central to Piaget's theory of cognitive development. However, as the influence of the Piagetian account waned, developmental notions of embodiment were shelved in favor of mechanical computational approaches. In this article, I argue that by reconsidering embodiment, we can address a key issue with computational accounts: how meaning is constructed by the developing person. I also suggest that the process-relational approach to developmental systems can provide a system of concepts for framing a fully embodied, integrative developmental science.
Embodiment and Human Development
Marshall, Peter J.
2016-01-01
We are recognizing increasingly that the study of cognitive, social, and emotional processes must account for their embodiment in living, acting beings. The related field of embodied cognition (EC) has coalesced around dissatisfaction with the lack of attention to the body in cognitive science. For developmental scientists, the emphasis in the literature on adult EC on the role of the body in cognition may not seem particularly novel, given that bodily action was central to Piaget’s theory of cognitive development. However, as the influence of the Piagetian account waned, developmental notions of embodiment were shelved in favor of mechanical computational approaches. In this article, I argue that by reconsidering embodiment, we can address a key issue with computational accounts: how meaning is constructed by the developing person. I also suggest that the process-relational approach to developmental systems can provide a system of concepts for framing a fully embodied, integrative developmental science. PMID:27833651
Federal Register 2010, 2011, 2012, 2013, 2014
2011-03-01
..., econometrics, cognitive psychology, and computer science as they pertain to the full range of Census Bureau... technical expertise from the following disciplines: demography, economics, geography, psychology, statistics..., psychology, statistics, survey methodology, social and behavioral sciences, Information Technology, computing...
Critical Thinking Traits of Top-Tier Experts and Implications for Computer Science Education
2007-08-01
field of cognitive theory ," [Papert 1999] used his work while developing the Logo programming language. 19 Although other researchers had developed ...of computer expert systems influenced the development of current theories dealing with cognitive abilities. One of the most important initiatives by...multitude of factors involved. He also builds on the cognitive development work of Piaget and is not ready to abandon the generalist approach. Instead, he
ERIC Educational Resources Information Center
Kausar, Tayyaba; Choudhry, Bushra Naoreen; Gujjar, Aijaz Ahmed
2008-01-01
This study was aimed to evaluate the effectiveness of CAI vs. classroom lecture for computer science at ICS level. The objectives were to compare the learning effects of two groups with class room lecture and computer assisted instruction studying the same curriculum and the effects of CAI and CRL in terms of cognitive development. Hypothesis of…
ERIC Educational Resources Information Center
Kausar, Tayyaba; Choudhry, Bushra Naoreen; Gujjar, Aijaz Ahmed
2008-01-01
This study was aimed to evaluate the effectiveness of CAI vs. classroom lecture for computer science at ICS level. The objectives were to compare the learning effects of two groups with class room lecture and computer assisted instruction studying the same curriculum and the effects of CAI and CRL in terms of cognitive development. Hypothesis of…
Mastering Cognitive Development Theory in Computer Science Education
ERIC Educational Resources Information Center
Gluga, Richard; Kay, Judy; Lister, Raymond; Kleitman, Simon; Kleitman, Sabina
2013-01-01
To design an effective computer science curriculum, educators require a systematic method of classifying the difficulty level of learning activities and assessment tasks. This is important for curriculum design and implementation and for communication between educators. Different educators must be able to use the method consistently, so that…
Exploring Human Cognition Using Large Image Databases.
Griffiths, Thomas L; Abbott, Joshua T; Hsu, Anne S
2016-07-01
Most cognitive psychology experiments evaluate models of human cognition using a relatively small, well-controlled set of stimuli. This approach stands in contrast to current work in neuroscience, perception, and computer vision, which have begun to focus on using large databases of natural images. We argue that natural images provide a powerful tool for characterizing the statistical environment in which people operate, for better evaluating psychological theories, and for bringing the insights of cognitive science closer to real applications. We discuss how some of the challenges of using natural images as stimuli in experiments can be addressed through increased sample sizes, using representations from computer vision, and developing new experimental methods. Finally, we illustrate these points by summarizing recent work using large image databases to explore questions about human cognition in four different domains: modeling subjective randomness, defining a quantitative measure of representativeness, identifying prior knowledge used in word learning, and determining the structure of natural categories. Copyright © 2016 Cognitive Science Society, Inc.
Neurale Netwerken en Radarsystemen (Neural Networks and Radar Systems)
1989-08-01
general issues in cognitive science", Parallel distributed processing, Vol 1: Foundations, Rumelhart et al. 1986 pp 110-146 THO rapport Pagina 151 36 D.E...34Neural networks (part 2)",Expert Focus, IEEE Expert, Spring 1988. 61 J.A. Anderson, " Cognitive and Psychological Computations with Neural Models", IEEE...Pagina 154 69 David H. Ackley, Geoffrey E. Hinton and Terrence J. Sejnowski, "A Learning Algorithm for Boltzmann machines", cognitive science 9, 147-169
Simulating Serious Games: A Discrete-Time Computational Model Based on Cognitive Flow Theory
ERIC Educational Resources Information Center
Westera, Wim
2018-01-01
This paper presents a computational model for simulating how people learn from serious games. While avoiding the combinatorial explosion of a games micro-states, the model offers a meso-level pathfinding approach, which is guided by cognitive flow theory and various concepts from learning sciences. It extends a basic, existing model by exposing…
ERIC Educational Resources Information Center
Cepni, Salih; Tas, Erol; Kose, Sacit
2006-01-01
The purpose of this study was to investigate the effects of a Computer-Assisted Instruction Material (CAIM) related to "photosynthesis" topic on student cognitive development, misconceptions and attitudes. The study conducted in 2002-2003 academic year and was carried out in two different classes taught by the same teacher, in which…
IBM Watson: How Cognitive Computing Can Be Applied to Big Data Challenges in Life Sciences Research.
Chen, Ying; Elenee Argentinis, J D; Weber, Griff
2016-04-01
Life sciences researchers are under pressure to innovate faster than ever. Big data offer the promise of unlocking novel insights and accelerating breakthroughs. Ironically, although more data are available than ever, only a fraction is being integrated, understood, and analyzed. The challenge lies in harnessing volumes of data, integrating the data from hundreds of sources, and understanding their various formats. New technologies such as cognitive computing offer promise for addressing this challenge because cognitive solutions are specifically designed to integrate and analyze big datasets. Cognitive solutions can understand different types of data such as lab values in a structured database or the text of a scientific publication. Cognitive solutions are trained to understand technical, industry-specific content and use advanced reasoning, predictive modeling, and machine learning techniques to advance research faster. Watson, a cognitive computing technology, has been configured to support life sciences research. This version of Watson includes medical literature, patents, genomics, and chemical and pharmacological data that researchers would typically use in their work. Watson has also been developed with specific comprehension of scientific terminology so it can make novel connections in millions of pages of text. Watson has been applied to a few pilot studies in the areas of drug target identification and drug repurposing. The pilot results suggest that Watson can accelerate identification of novel drug candidates and novel drug targets by harnessing the potential of big data. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
A conceptual and computational model of moral decision making in human and artificial agents.
Wallach, Wendell; Franklin, Stan; Allen, Colin
2010-07-01
Recently, there has been a resurgence of interest in general, comprehensive models of human cognition. Such models aim to explain higher-order cognitive faculties, such as deliberation and planning. Given a computational representation, the validity of these models can be tested in computer simulations such as software agents or embodied robots. The push to implement computational models of this kind has created the field of artificial general intelligence (AGI). Moral decision making is arguably one of the most challenging tasks for computational approaches to higher-order cognition. The need for increasingly autonomous artificial agents to factor moral considerations into their choices and actions has given rise to another new field of inquiry variously known as Machine Morality, Machine Ethics, Roboethics, or Friendly AI. In this study, we discuss how LIDA, an AGI model of human cognition, can be adapted to model both affective and rational features of moral decision making. Using the LIDA model, we will demonstrate how moral decisions can be made in many domains using the same mechanisms that enable general decision making. Comprehensive models of human cognition typically aim for compatibility with recent research in the cognitive and neural sciences. Global workspace theory, proposed by the neuropsychologist Bernard Baars (1988), is a highly regarded model of human cognition that is currently being computationally instantiated in several software implementations. LIDA (Franklin, Baars, Ramamurthy, & Ventura, 2005) is one such computational implementation. LIDA is both a set of computational tools and an underlying model of human cognition, which provides mechanisms that are capable of explaining how an agent's selection of its next action arises from bottom-up collection of sensory data and top-down processes for making sense of its current situation. We will describe how the LIDA model helps integrate emotions into the human decision-making process, and we will elucidate a process whereby an agent can work through an ethical problem to reach a solution that takes account of ethically relevant factors. Copyright © 2010 Cognitive Science Society, Inc.
Evolution, learning, and cognition
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lee, Y.C.
1988-01-01
The book comprises more than fifteen articles in the areas of neural networks and connectionist systems, classifier systems, adaptive network systems, genetic algorithm, cellular automata, artificial immune systems, evolutionary genetics, cognitive science, optical computing, combinatorial optimization, and cybernetics.
AFL-1: A programming Language for Massively Concurrent Computers.
1986-11-01
Bibliography Ackley, D.H., Hinton, G.E., Sejnowski, T.J., "A Learning Algorithm for boltzmann Machines", Cognitive Science, 1985, 9, 147-169. Agre...P.E., "Routines", Memo 828, MIT AI Laboratory, Many 1985. Ballard, D.H., Hayes, P.J., "Parallel Logical Inference", Conference of the Cognitive Science...34Experiments on Semantic Memory and Language Com- 125 prehension", in L.W. Greg (Ed.), Cognition in Learning and Memory, New York, Wiley, 1972._ Collins
Formal Operations and Learning Style Predict Success in Statistics and Computer Science Courses.
ERIC Educational Resources Information Center
Hudak, Mary A.; Anderson, David E.
1990-01-01
Studies 94 undergraduate students in introductory statistics and computer science courses. Applies Formal Operations Reasoning Test (FORT) and Kolb's Learning Style Inventory (LSI). Finds that substantial numbers of students have not achieved the formal operation level of cognitive maturity. Emphasizes need to examine students learning style and…
Strategic research in the social sciences
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bainbridge, W.S.
1995-12-31
The federal government has identified a number of multi-agency funding initiatives for science in strategic areas, such as the initiatives on global environmental change and high performance computing, that give some role to the social sciences. Seven strategic areas for social science research are given with potential for federal funding: (1) Democratization. (2) Human Capital. (3) Administrative Science. (4) Cognitive Science. (5) High Performance Computing and Digital Libraries. (6) Human Dimensions of Environmental Change. and (7) Human Genetic Diversity. The first two are addressed in detail and the remainder as a group. 10 refs.
NASA Astrophysics Data System (ADS)
Honing, Henkjan; Zuidema, Willem
2014-09-01
The future of cognitive science will be about bridging neuroscience and behavioral studies, with essential roles played by comparative biology, formal modeling, and the theory of computation. Nowhere will this integration be more strongly needed than in understanding the biological basis of language and music. We thus strongly sympathize with the general framework that Fitch [1] proposes, and welcome the remarkably broad and readable review he presents to support it.
Intelligent Computer-Assisted Language Learning.
ERIC Educational Resources Information Center
Harrington, Michael
1996-01-01
Introduces the field of intelligent computer assisted language learning (ICALL) and relates them to current practice in computer assisted language learning (CALL) and second language learning. Points out that ICALL applies expertise from artificial intelligence and the computer and cognitive sciences to the development of language learning…
Introduction: philosophy in and philosophy of cognitive science.
Brook, Andrew
2009-04-01
Despite being there from the beginning, philosophical approaches have never had a settled place in cognitive research and few cognitive researchers not trained in philosophy have a clear sense of what its role has been or should be. We distinguish philosophy in cognitive research and philosophy of cognitive research. Concerning philosophy in cognitive research, after exploring some standard reactions to this work by nonphilosophers, we will pay particular attention to the methods that philosophers use. Being neither experimental nor computational, they can leave others bewildered. Thought experiments are the most striking example but not the only one. Concerning philosophy of cognitive research, we will pay particular attention to its power to generate and test normative claims, claims about what should and should not be done. Copyright © 2009 Cognitive Science Society, Inc.
Computer Assisted Instructional Design for Computer-Based Instruction. Final Report. Working Papers.
ERIC Educational Resources Information Center
Russell, Daniel M.; Pirolli, Peter
Recent advances in artificial intelligence and the cognitive sciences have made it possible to develop successful intelligent computer-aided instructional systems for technical and scientific training. In addition, computer-aided design (CAD) environments that support the rapid development of such computer-based instruction have also been recently…
Six Suggestions for Research on Games in Cognitive Science.
Chabris, Christopher F
2017-04-01
Games are more varied and occupy more of daily life than ever before. At the same time, the tools available to study game play and players are more powerful than ever, especially massive data sets from online platforms and computational engines that can accurately evaluate human decisions. This essay offers six suggestions for future cognitive science research on games: (1) Don't forget about chess, (2) Look beyond action games and chess, (3) Use (near)-optimal play to understand human play and players, (4) Investigate social phenomena, (5) Raise the standards for studies of games as treatments, (6) Talk to real experts. Copyright © 2017 Cognitive Science Society, Inc.
ERIC Educational Resources Information Center
Giannakos, Michail N.
2014-01-01
Computer Science (CS) courses comprise both Programming and Information and Communication Technology (ICT) issues; however these two areas have substantial differences, inter alia the attitudes and beliefs of the students regarding the intended learning content. In this research, factors from the Social Cognitive Theory and Unified Theory of…
ERIC Educational Resources Information Center
Lamb, Richard L.
2016-01-01
Within the last 10 years, new tools for assisting in the teaching and learning of academic skills and content within the context of science have arisen. These new tools include multiple types of computer software and hardware to include (video) games. The purpose of this study was to examine and compare the effect of computer learning games in the…
Introduction to cognition in science and technology.
Gorman, Michael E
2009-10-01
Cognitive studies of science and technology have had a long history of largely independent research projects that have appeared in multiple outlets, but rarely together. The emergence of a new International Society for Psychology of Science and Technology suggests that this is a good time to put some of the latest work in this area into topiCS in a way that will both acquaint readers with the cutting edge in this domain and also give them a hint of its history. One core theme includes how scientists, inventors, and engineers represent and solve problems; another, related theme is the extent to which they distribute and share cognition. Methodologies include fine-grained studies of historical records, protocols of working scientists, observations and comparisons of engineering science laboratories, and computational simulations designed both to serve as research tools and also to improve scientific problem-solving. The series of articles will conclude with the Associate Editor's suggestions for future research. Copyright © 2009 Cognitive Science Society, Inc.
A Computational Model of Linguistic Humor in Puns.
Kao, Justine T; Levy, Roger; Goodman, Noah D
2016-07-01
Humor plays an essential role in human interactions. Precisely what makes something funny, however, remains elusive. While research on natural language understanding has made significant advancements in recent years, there has been little direct integration of humor research with computational models of language understanding. In this paper, we propose two information-theoretic measures-ambiguity and distinctiveness-derived from a simple model of sentence processing. We test these measures on a set of puns and regular sentences and show that they correlate significantly with human judgments of funniness. Moreover, within a set of puns, the distinctiveness measure distinguishes exceptionally funny puns from mediocre ones. Our work is the first, to our knowledge, to integrate a computational model of general language understanding and humor theory to quantitatively predict humor at a fine-grained level. We present it as an example of a framework for applying models of language processing to understand higher level linguistic and cognitive phenomena. © 2015 The Authors. Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.
ERIC Educational Resources Information Center
Yuen, Timothy; Liu, Min
2011-01-01
This paper presents a cognitive model of how interactive multimedia authoring (IMA) affect novices' cognition in object-oriented programming. This model was generated through an empirical study of first year computer science students at the university level being engaged in interactive multimedia authoring of a role-playing game. Clinical…
NASA Astrophysics Data System (ADS)
Purwins, Hendrik; Herrera, Perfecto; Grachten, Maarten; Hazan, Amaury; Marxer, Ricard; Serra, Xavier
2008-09-01
We present a review on perception and cognition models designed for or applicable to music. An emphasis is put on computational implementations. We include findings from different disciplines: neuroscience, psychology, cognitive science, artificial intelligence, and musicology. The article summarizes the methodology that these disciplines use to approach the phenomena of music understanding, the localization of musical processes in the brain, and the flow of cognitive operations involved in turning physical signals into musical symbols, going from the transducers to the memory systems of the brain. We discuss formal models developed to emulate, explain and predict phenomena involved in early auditory processing, pitch processing, grouping, source separation, and music structure computation. We cover generic computational architectures of attention, memory, and expectation that can be instantiated and tuned to deal with specific musical phenomena. Criteria for the evaluation of such models are presented and discussed. Thereby, we lay out the general framework that provides the basis for the discussion of domain-specific music models in Part II.
The educational effectiveness of computer-based instruction
NASA Astrophysics Data System (ADS)
Renshaw, Carl E.; Taylor, Holly A.
2000-07-01
Although numerous studies have shown that computer-based education is effective for enhancing rote memorization, the impact of these tools on higher-order cognitive skills, such as critical thinking, is less clear. Existing methods for evaluating educational effectiveness, such as surveys, quizzes and pre- or post-interviews, may not be effective for evaluating impact on critical thinking skills because students are not always aware of the effects the software has on their thought processes. We review an alternative evaluation strategy whereby the student's mastery of a specific cognitive skill is directly assessed both before and after participating in a computer-based exercise. Methodologies for assessing cognitive skill are based on recent advances in the fields of cognitive science. Results from two studies show that computer-based exercises can positively impact the higher-order cognitive skills of some students. However, a given exercise will not impact all students equally. This suggests that further work is needed to understand how and why CAI software is more or less effective within a given population.
Protocol for a randomized controlled trial of piano training on cognitive and psychosocial outcomes.
Bugos, Jennifer
2018-05-09
Age-related cognitive decline and cognitive impairment represent the fastest growing health epidemic worldwide among those over 60. There is a critical need to identify effective and novel complex cognitive interventions to promote successful aging. Since piano training engages cognitive and bimanual sensorimotor processing, we hypothesize that piano training may serve as an effective cognitive intervention, as it requires sustained attention and engages an executive network that supports generalized cognition and emotional control. Here, I describe the protocol of a randomized controlled trial (RCT) to evaluate the impact of piano training on cognitive performance in adulthood, a period associated with decreased neuroplasticity. In this cluster RCT, healthy older adults (age 60-80) were recruited and screened to control for confounding variables. Eligible participants completed an initial 3-h assessment of standardized cognitive and psychosocial measures. Participants were stratified by age, education, and estimate of intelligence and randomly assigned to one of three groups: piano training, computer brain training, or a no-treatment control group. Computer brain training consisted of progressively difficult auditory cognitive exercises (Brain HQ; Posit Science, 2010). Participants assigned to training groups completed a 16-week program that met twice a week for 90 minutes. Upon program completion and at a 3-month follow-up, training participants and no-treatment controls completed a posttest visit lasting 2.5 hours. © 2018 New York Academy of Sciences.
Cognitive biases, linguistic universals, and constraint-based grammar learning.
Culbertson, Jennifer; Smolensky, Paul; Wilson, Colin
2013-07-01
According to classical arguments, language learning is both facilitated and constrained by cognitive biases. These biases are reflected in linguistic typology-the distribution of linguistic patterns across the world's languages-and can be probed with artificial grammar experiments on child and adult learners. Beginning with a widely successful approach to typology (Optimality Theory), and adapting techniques from computational approaches to statistical learning, we develop a Bayesian model of cognitive biases and show that it accounts for the detailed pattern of results of artificial grammar experiments on noun-phrase word order (Culbertson, Smolensky, & Legendre, 2012). Our proposal has several novel properties that distinguish it from prior work in the domains of linguistic theory, computational cognitive science, and machine learning. This study illustrates how ideas from these domains can be synthesized into a model of language learning in which biases range in strength from hard (absolute) to soft (statistical), and in which language-specific and domain-general biases combine to account for data from the macro-level scale of typological distribution to the micro-level scale of learning by individuals. Copyright © 2013 Cognitive Science Society, Inc.
Conversational Agents in Virtual Worlds: Bridging Disciplines
ERIC Educational Resources Information Center
Veletsianos, George; Heller, Robert; Overmyer, Scott; Procter, Mike
2010-01-01
This paper examines the effective deployment of conversational agents in virtual worlds from the perspective of researchers/practitioners in cognitive psychology, computing science, learning technologies and engineering. From a cognitive perspective, the major challenge lies in the coordination and management of the various channels of information…
Theoretical computer science and the natural sciences
NASA Astrophysics Data System (ADS)
Marchal, Bruno
2005-12-01
I present some fundamental theorems in computer science and illustrate their relevance in Biology and Physics. I do not assume prerequisites in mathematics or computer science beyond the set N of natural numbers, functions from N to N, the use of some notational conveniences to describe functions, and at some point, a minimal amount of linear algebra and logic. I start with Cantor's transcendental proof by diagonalization of the non enumerability of the collection of functions from natural numbers to the natural numbers. I explain why this proof is not entirely convincing and show how, by restricting the notion of function in terms of discrete well defined processes, we are led to the non algorithmic enumerability of the computable functions, but also-through Church's thesis-to the algorithmic enumerability of partial computable functions. Such a notion of function constitutes, with respect to our purpose, a crucial generalization of that concept. This will make easy to justify deep and astonishing (counter-intuitive) incompleteness results about computers and similar machines. The modified Cantor diagonalization will provide a theory of concrete self-reference and I illustrate it by pointing toward an elementary theory of self-reproduction-in the Amoeba's way-and cellular self-regeneration-in the flatworm Planaria's way. To make it easier, I introduce a very simple and powerful formal system known as the Schoenfinkel-Curry combinators. I will use the combinators to illustrate in a more concrete way the notion introduced above. The combinators, thanks to their low-level fine grained design, will also make it possible to make a rough but hopefully illuminating description of the main lessons gained by the careful observation of nature, and to describe some new relations, which should exist between computer science, the science of life and the science of inert matter, once some philosophical, if not theological, hypotheses are made in the cognitive sciences. In the last section, I come back to self-reference and I give an exposition of its modal logics. This is used to show that theoretical computer science makes those “philosophical hypotheses” in theoretical cognitive science experimentally and mathematically testable.
Machine Understanding of Human Implicit Intention
2013-05-18
Cognitive Neurodynamics , Hokkaido, Japan, June 2011, Hokkaido, Japan (Plenary Talk) - Soo-Young Lee, Implicit Intention Recognition and Hierarchical...subject’s response with the accuracy of about 80% by SVM. 15. SUBJECT TERMS Brain Science and Engineering; Cognitive Neuroscience; Human-Computer...oscillations have been related to a variety of functions such as perception, cognition , sleep, etc. For a long time, researchers have found the sensory and
Understanding and Managing Causality of Change in Socio-Technical Systems II
2011-01-25
SUBJECT TERMS Cognition , Human Effectiveness, Information Science 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF ABSTRACT Same as Report (SAR) 18...at large taking into account the cognitive interaction between humans and technology. 8 Hussein Abbass Professor Abbass leads the...Network Centric Operations Future Air Traffic Management Systems Cognitive Engineering including Human-Computer Integration In all of the
Phillips, Lawrence; Pearl, Lisa
2015-11-01
The informativity of a computational model of language acquisition is directly related to how closely it approximates the actual acquisition task, sometimes referred to as the model's cognitive plausibility. We suggest that though every computational model necessarily idealizes the modeled task, an informative language acquisition model can aim to be cognitively plausible in multiple ways. We discuss these cognitive plausibility checkpoints generally and then apply them to a case study in word segmentation, investigating a promising Bayesian segmentation strategy. We incorporate cognitive plausibility by using an age-appropriate unit of perceptual representation, evaluating the model output in terms of its utility, and incorporating cognitive constraints into the inference process. Our more cognitively plausible model shows a beneficial effect of cognitive constraints on segmentation performance. One interpretation of this effect is as a synergy between the naive theories of language structure that infants may have and the cognitive constraints that limit the fidelity of their inference processes, where less accurate inference approximations are better when the underlying assumptions about how words are generated are less accurate. More generally, these results highlight the utility of incorporating cognitive plausibility more fully into computational models of language acquisition. Copyright © 2015 Cognitive Science Society, Inc.
A Pilot Meta-Analysis of Computer-Based Scaffolding in STEM Education
ERIC Educational Resources Information Center
Belland, Brian R.; Walker, Andrew E.; Olsen, Megan Whitney; Leary, Heather
2015-01-01
This paper employs meta-analysis to determine the influence of computer-based scaffolding characteristics and study and test score quality on cognitive outcomes in science, technology, engineering, and mathematics education at the secondary, college, graduate, and adult levels. Results indicate that (a) computer-based scaffolding positively…
Metocognitive Support Accelerates Computer Assisted Learning for Novice Programmers
ERIC Educational Resources Information Center
Rum, Siti Nurulain Mohd; Ismail, Maizatul Akmar
2017-01-01
Computer programming is a part of the curriculum in computer science education, and high drop rates for this subject are a universal problem. Development of metacognitive skills, including the conceptual framework provided by socio-cognitive theories that afford reflective thinking, such as actively monitoring, evaluating, and modifying one's…
Empathy in Future Teachers of the Pedagogical and Technological University of Colombia
ERIC Educational Resources Information Center
Herrera Torres, Lucía; Buitrago Bonilla, Rafael Enrique; Avila Moreno, Aida Karina
2016-01-01
This study analyzes cognitive and emotional empathy in students who started their training at the Education Science Faculty of the Pedagogical and Technological University of Colombia. The sample was formed by 317 students enrolled in the study programs of Preschool, Plastic Arts, Natural Sciences, Physical Education, Philosophy, Computer Science,…
The Spatial and the Visual in Mental Spatial Reasoning: An Ill-Posed Distinction
NASA Astrophysics Data System (ADS)
Schultheis, Holger; Bertel, Sven; Barkowsky, Thomas; Seifert, Inessa
It is an ongoing and controversial debate in cognitive science which aspects of knowledge humans process visually and which ones they process spatially. Similarly, artificial intelligence (AI) and cognitive science research, in building computational cognitive systems, tended to use strictly spatial or strictly visual representations. The resulting systems, however, were suboptimal both with respect to computational efficiency and cognitive plau sibility. In this paper, we propose that the problems in both research strands stem from a mis conception of the visual and the spatial in mental spatial knowl edge pro cessing. Instead of viewing the visual and the spatial as two clearly separable categories, they should be conceptualized as the extremes of a con tinuous dimension of representation. Regarding psychology, a continuous di mension avoids the need to exclusively assign processes and representations to either one of the cate gories and, thus, facilitates a more unambiguous rating of processes and rep resentations. Regarding AI and cognitive science, the con cept of a continuous spatial / visual dimension provides the possibility of rep re sentation structures which can vary continuously along the spatial / visual di mension. As a first step in exploiting these potential advantages of the pro posed conception we (a) introduce criteria allowing for a non-dichotomic judgment of processes and representations and (b) present an approach towards rep re sentation structures that can flexibly vary along the spatial / visual dimension.
Thill, Serge; Padó, Sebastian; Ziemke, Tom
2014-07-01
The recent trend in cognitive robotics experiments on language learning, symbol grounding, and related issues necessarily entails a reduction of sensorimotor aspects from those provided by a human body to those that can be realized in machines, limiting robotic models of symbol grounding in this respect. Here, we argue that there is a need for modeling work in this domain to explicitly take into account the richer human embodiment even for concrete concepts that prima facie relate merely to simple actions, and illustrate this using distributional methods from computational linguistics which allow us to investigate grounding of concepts based on their actual usage. We also argue that these techniques have applications in theories and models of grounding, particularly in machine implementations thereof. Similarly, considering the grounding of concepts in human terms may be of benefit to future work in computational linguistics, in particular in going beyond "grounding" concepts in the textual modality alone. Overall, we highlight the overall potential for a mutually beneficial relationship between the two fields. Copyright © 2014 Cognitive Science Society, Inc.
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Howard, Bruce C.; McGee, Steven; Shia, Regina; Hong, Namsoo Shin
This study sought to examine the effects of meta cognitive self-regulation on problem solving across three conditions: (1) an interactive, computer-based treatment condition; (2) a noninteractive computer-based alternative treatment condition; and (3) a control condition. Also investigated was which of five components of metacognitive…
Assessing Practical Skills in Physics Using Computer Simulations
ERIC Educational Resources Information Center
Walsh, Kevin
2018-01-01
Computer simulations have been used very effectively for many years in the teaching of science but the focus has been on cognitive development. This study, however, is an investigation into the possibility that a student's experimental skills in the real-world environment can be judged via the undertaking of a suitably chosen computer simulation…
McKay, E
2000-01-01
An innovative research program was devised to investigate the interactive effect of instructional strategies enhanced with text-plus-textual metaphors or text-plus-graphical metaphors, and cognitive style on the acquisition of programming concepts. The Cognitive Styles Analysis (CSA) program (Riding,1991) was used to establish the participants' cognitive style. The QUEST Interactive Test Analysis System (Adams and Khoo,1996) provided the cognitive performance measuring tool, which ensured an absence of error measurement in the programming knowledge testing instruments. Therefore, reliability of the instrumentation was assured through the calibration techniques utilized by the QUEST estimate; providing predictability of the research design. A means analysis of the QUEST data, using the Cohen (1977) approach to size effect and statistical power further quantified the significance of the findings. The experimental methodology adopted for this research links the disciplines of instructional science, cognitive psychology, and objective measurement to provide reliable mechanisms for beneficial use in the evaluation of cognitive performance by the education, training and development sectors. Furthermore, the research outcomes will be of interest to educators, cognitive psychologists, communications engineers, and computer scientists specializing in computer-human interactions.
ERIC Educational Resources Information Center
Willingham, Daniel T.
2013-01-01
Cognitive science is an interdisciplinary field of researchers from psychology, neuroscience, linguistics, philosophy, computer science, and anthropology who seek to understand the mind. This paper considers findings from this field that are strong and clear enough to merit classroom application. Although many teachers and parents worry that high…
Thirty Years After Marr's Vision: Levels of Analysis in Cognitive Science.
Peebles, David; Cooper, Richard P
2015-04-01
Thirty years after the publication of Marr's seminal book Vision (Marr, 1982) the papers in this topic consider the contemporary status of his influential conception of three distinct levels of analysis for information-processing systems, and in particular the role of the algorithmic and representational level with its cognitive-level concepts. This level has (either implicitly or explicitly) been downplayed or eliminated both by reductionist neuroscience approaches from below that seek to account for behavior from the implementation level and by Bayesian approaches from above that seek to account for behavior in purely computational-level terms. Copyright © 2015 Cognitive Science Society, Inc.
Shrager, Jeff; Billman, Dorrit; Convertino, Gregorio; Massar, J P; Pirolli, Peter
2010-01-01
Science is a form of distributed analysis involving both individual work that produces new knowledge and collaborative work to exchange information with the larger community. There are many particular ways in which individual and community can interact in science, and it is difficult to assess how efficient these are, and what the best way might be to support them. This paper reports on a series of experiments in this area and a prototype implementation using a research platform called CACHE. CACHE both supports experimentation with different structures of interaction between individual and community cognition and serves as a prototype for computational support for those structures. We particularly focus on CACHE-BC, the Bayes community version of CACHE, within which the community can break up analytical tasks into "mind-sized" units and use provenance tracking to keep track of the relationship between these units. Copyright © 2009 Cognitive Science Society, Inc.
Beyond functional architecture in cognitive neuropsychology: a reply to Coltheart (2010).
Plaut, David C; Patterson, Karalyn
2010-01-01
We (Patterson & Plaut, 2009) argued that cognitive neuropsychology has had a limited impact on cognitive science due to a nearly exclusive reliance on (a) single-case studies, (b) dissociations in cognitive performance, and (c) shallow, box-and-arrow theorizing, and we advocated adopting a case-series methodology, considering associations as well as dissociations, and employing explicit computational modeling in studying "how the brain does its cognitive business." In reply, Coltheart (2010) claims that our concern is misplaced because cognitive neuropsychology is concerned only with studying the mind, in terms of its "functional architecture," without regard to how this is implemented in the brain. In this response, we do not dispute his characterization of cognitive neuropsychology as it has typically been practiced over the last 40 years, but we suggest that our understanding of brain structure and function has advanced to the point where studying the mind without regard to the brain is unwise and perpetuates the field's isolation. Copyright © 2009 Cognitive Science Society, Inc.
Using Cognitive Control in Software Defined Networking for Port Scan Detection
2017-07-01
ARL-TR-8059 ● July 2017 US Army Research Laboratory Using Cognitive Control in Software-Defined Networking for Port Scan...Cognitive Control in Software-Defined Networking for Port Scan Detection by Vinod K Mishra Computational and Information Sciences Directorate, ARL...currently valid OMB control number. PLEASE DO NOT RETURN YOUR FORM TO THE ABOVE ADDRESS. 1. REPORT DATE (DD-MM-YYYY) July 2017 2. REPORT TYPE
Group Emotions: The Social and Cognitive Functions of Emotions in Argumentation
ERIC Educational Resources Information Center
Polo, Claire; Lund, Kristine; Plantin, Christian; Niccolai, Gerald P.
2016-01-01
The learning sciences of today recognize the tri-dimensional nature of learning as involving cognitive, social and emotional phenomena. However, many computer-supported argumentation systems still fail in addressing the socio-emotional aspects of group reasoning, perhaps due to a lack of an integrated theoretical vision of how these three…
Tracking Students' Cognitive Processes during Program Debugging--An Eye-Movement Approach
ERIC Educational Resources Information Center
Lin, Yu-Tzu; Wu, Cheng-Chih; Hou, Ting-Yun; Lin, Yu-Chih; Yang, Fang-Ying; Chang, Chia-Hu
2016-01-01
This study explores students' cognitive processes while debugging programs by using an eye tracker. Students' eye movements during debugging were recorded by an eye tracker to investigate whether and how high- and low-performance students act differently during debugging. Thirty-eight computer science undergraduates were asked to debug two C…
Language Learning in Mindbodyworld: A Sociocognitive Approach to Second Language Acquisition
ERIC Educational Resources Information Center
Atkinson, Dwight
2014-01-01
Based on recent research in cognitive science, interaction, and second language acquisition (SLA), I describe a sociocognitive approach to SLA. This approach adopts a "non-cognitivist" view of cognition: Instead of an isolated computational process in which input is extracted from the environment and used to build elaborate internal…
Capturing Problem-Solving Processes Using Critical Rationalism
ERIC Educational Resources Information Center
Chitpin, Stephanie; Simon, Marielle
2012-01-01
The examination of problem-solving processes continues to be a current research topic in education. Knowing how to solve problems is not only a key aspect of learning mathematics but is also at the heart of cognitive theories, linguistics, artificial intelligence, and computers sciences. Problem solving is a multistep, higher-order cognitive task…
Spatial Learning and Computer Simulations in Science
ERIC Educational Resources Information Center
Lindgren, Robb; Schwartz, Daniel L.
2009-01-01
Interactive simulations are entering mainstream science education. Their effects on cognition and learning are often framed by the legacy of information processing, which emphasized amodal problem solving and conceptual organization. In contrast, this paper reviews simulations from the vantage of research on perception and spatial learning,…
Pedagogical Approaches for Technology-Integrated Science Teaching
ERIC Educational Resources Information Center
Hennessy, Sara; Wishart, Jocelyn; Whitelock, Denise; Deaney, Rosemary; Brawn, Richard; la Velle, Linda; McFarlane, Angela; Ruthven, Kenneth; Winterbottom, Mark
2007-01-01
The two separate projects described have examined how teachers exploit computer-based technologies in supporting learning of science at secondary level. This paper examines how pedagogical approaches associated with these technological tools are adapted to both the cognitive and structuring resources available in the classroom setting. Four…
NASA Astrophysics Data System (ADS)
Akmam, A.; Anshari, R.; Amir, H.; Jalinus, N.; Amran, A.
2018-04-01
Misconception is one of the factors causing students are not suitable in to choose a method for problem solving. Computational Physics course is a major subject in the Department of Physics FMIPA UNP Padang. The problem in Computational Physics learning lately is that students have difficulties in constructing knowledge. The indication of this problem was the student learning outcomes do not achieve mastery learning. The root of the problem is the ability of students to think critically weak. Student critical thinking can be improved using cognitive by conflict learning strategies. The research aims to determine the effect of cognitive conflict learning strategy to student misconception on the subject of Computational Physics Course at the Department of Physics, Faculty of Mathematics and Science, Universitas Negeri Padang. The experimental research design conducted after-before design cycles with a sample of 60 students by cluster random sampling. Data were analyzed using repeated Anova measurements. The cognitive conflict learning strategy has a significant effect on student misconception in the subject of Computational Physics Course.
ERIC Educational Resources Information Center
Simon, Nicole A.
2013-01-01
Virtual laboratory experiments using interactive computer simulations are not being employed as viable alternatives to laboratory science curriculum at extensive enough rates within higher education. Rote traditional lab experiments are currently the norm and are not addressing inquiry, Critical Thinking, and cognition throughout the laboratory…
Have Technology and Multitasking Rewired How Students Learn?
ERIC Educational Resources Information Center
Willingham, Daniel T.
2010-01-01
Cognitive science is an interdisciplinary field of researchers from psychology, neuroscience, linguistics, philosophy, computer science, and anthropology who seek to understand the mind. In this article, the author considers findings from this field that are strong and clear enough to merit classroom application. He examines how technology has…
NASA Astrophysics Data System (ADS)
Gusev, A.; Trudkova, N.
2017-09-01
Center "GeoNa" will enable scientists and teachers of the Russian universities to join to advanced achievements of a science, information technologies; to establish scientific communications with foreign colleagues in sphere of the high technology, educational projects and Intellectual-Cognitive Tourism. The Project "Kazan - Moon - 2020+" is directed on the decision of fundamental problems of celestial mechanics, selenodesy and geophysics of the Moon(s) connected to carrying out of complex theoretical researches and computer modelling.
Allen Newell's Program of Research: The Video-Game Test.
Gobet, Fernand
2017-04-01
Newell (1973) argued that progress in psychology was slow because research focused on experiments trying to answer binary questions, such as serial versus parallel processing. In addition, not enough attention was paid to the strategies used by participants, and there was a lack of theories implemented as computer models offering sufficient precision for being tested rigorously. He proposed a three-headed research program: to develop computational models able to carry out the task they aimed to explain; to study one complex task in detail, such as chess; and to build computational models that can account for multiple tasks. This article assesses the extent to which the papers in this issue advance Newell's program. While half of the papers devote much attention to strategies, several papers still average across them, a capital sin according to Newell. The three courses of action he proposed were not popular in these papers: Only two papers used computational models, with no model being both able to carry out the task and to account for human data; there was no systematic analysis of a specific video game; and no paper proposed a computational model accounting for human data in several tasks. It is concluded that, while they use sophisticated methods of analysis and discuss interesting results, overall these papers contribute only little to Newell's program of research. In this respect, they reflect the current state of psychology and cognitive science. This is a shame, as Newell's ideas might help address the current crisis of lack of replication and fraud in psychology. Copyright © 2017 The Author. Topics in Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.
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Sins, Patrick H. M.; Savelsbergh, Elwin R.; van Joolingen, Wouter R.; van Hout-Wolters, Bernadette H. A. M.
2009-01-01
While many researchers in science education have argued that students' epistemological understanding of models and of modelling processes would influence their cognitive processing on a modelling task, there has been little direct evidence for such an effect. Therefore, this study aimed to investigate the relation between students' epistemological…
Computers and Cognitive Development at Work
ERIC Educational Resources Information Center
Roth, Wolff-Michael; Lee, Yew-Jin
2006-01-01
Data-logging exercises in science classrooms assume that with the proper scaffolding and provision of contexts by instructors, pupils are able to meaningfully comprehend the experimental variables under investigation. From a case study of knowing and learning in a fish hatchery using real-time computer statistical software, we show that…
ERIC Educational Resources Information Center
Dillenbourg, Pierre, Ed.
Intended to illustrate the benefits of collaboration between scientists from psychology and computer science, namely machine learning, this book contains the following chapters, most of which are co-authored by scholars from both sides: (1) "Introduction: What Do You Mean by 'Collaborative Learning'?" (Pierre Dillenbourg); (2)…
Flatbrain Spreadsheets: Mindtool outside the Box?
ERIC Educational Resources Information Center
Lamontagne, Claude; Desjardins, Francois; Benard, Michele
2007-01-01
Managing the pedagogical aspects of the "computational turn" that is occurring within the Humanities in general and the disciplines associated with cognitive science and neuroscience in particular, first implies facing the challenge of introducing students to computation. This paper presents what has proven to be an efficient approach to bringing…
Parallel Distributed Processing Theory in the Age of Deep Networks.
Bowers, Jeffrey S
2017-12-01
Parallel distributed processing (PDP) models in psychology are the precursors of deep networks used in computer science. However, only PDP models are associated with two core psychological claims, namely that all knowledge is coded in a distributed format and cognition is mediated by non-symbolic computations. These claims have long been debated in cognitive science, and recent work with deep networks speaks to this debate. Specifically, single-unit recordings show that deep networks learn units that respond selectively to meaningful categories, and researchers are finding that deep networks need to be supplemented with symbolic systems to perform some tasks. Given the close links between PDP and deep networks, it is surprising that research with deep networks is challenging PDP theory. Copyright © 2017. Published by Elsevier Ltd.
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Kaousar, Tayyeba; Choudhry, Bushra Naoreen; Gujjar, Aijaz Ahmed
2008-01-01
This study was aimed to evaluate the effectiveness of CAI vs. classroom lecture for computer science at ICS level. The objectives were to compare the learning effects of two groups with classroom lecture and computer-assisted instruction studying the same curriculum and the effects of CAI and CRL in terms of cognitive development. Hypotheses of…
Estimation of Time Requirements during Planning: Interactions between Motivation and Cognition.
1980-11-01
Haddad Program Manager Life Sciences Directorate AFOSR bollinq APB, DC 20332 44 Er. Party Rockway (AFHRL/IT) Lowry AFd Colorado 90230 45 3700 TCHTW/T!GH...10016 125 Dr. Robert Smith oepartment of Computer Science [utqers Uiversity New Brunswick. NJ 09903 126 Dr. Richard Snow School of Education Stanford
On quantum models of the human mind.
Wang, Hongbin; Sun, Yanlong
2014-01-01
Recent years have witnessed rapidly increasing interests in developing quantum theoretical models of human cognition. Quantum mechanisms have been taken seriously to describe how the mind reasons and decides. Papers in this special issue report the newest results in the field. Here we discuss why the two levels of commitment, treating the human brain as a quantum computer and merely adopting abstract quantum probability principles to model human cognition, should be integrated. We speculate that quantum cognition models gain greater modeling power due to a richer representation scheme. Copyright © 2013 Cognitive Science Society, Inc.
NASA Astrophysics Data System (ADS)
Smetana, Lara Kathleen; Bell, Randy L.
2012-06-01
Researchers have explored the effectiveness of computer simulations for supporting science teaching and learning during the past four decades. The purpose of this paper is to provide a comprehensive, critical review of the literature on the impact of computer simulations on science teaching and learning, with the goal of summarizing what is currently known and providing guidance for future research. We report on the outcomes of 61 empirical studies dealing with the efficacy of, and implications for, computer simulations in science instruction. The overall findings suggest that simulations can be as effective, and in many ways more effective, than traditional (i.e. lecture-based, textbook-based and/or physical hands-on) instructional practices in promoting science content knowledge, developing process skills, and facilitating conceptual change. As with any other educational tool, the effectiveness of computer simulations is dependent upon the ways in which they are used. Thus, we outline specific research-based guidelines for best practice. Computer simulations are most effective when they (a) are used as supplements; (b) incorporate high-quality support structures; (c) encourage student reflection; and (d) promote cognitive dissonance. Used appropriately, computer simulations involve students in inquiry-based, authentic science explorations. Additionally, as educational technologies continue to evolve, advantages such as flexibility, safety, and efficiency deserve attention.
ERIC Educational Resources Information Center
de Villiers, M. Ruth
2007-01-01
The teaching and learning of a complex section in "Theoretical Computer Science 1" in a distance-education context at the University of South Africa (UNISA) has been enhanced by a supplementary e-learning application called "Relations," which interactively teaches mathematical skills in a cognitive domain. It has tutorial and…
ERIC Educational Resources Information Center
Shih, M.; Feng, J.; Tsai, C. C.
2008-01-01
This paper provided a content analysis of studies in the field of cognition in e-learning that were published in five Social Sciences Citation Index (SSCI) journals (i.e. Computers and Education, British Journal of Educational Technology, Innovations in Education and Teaching International, Educational Technology Research & Development, and…
A Computational Model of Early Argument Structure Acquisition
ERIC Educational Resources Information Center
Alishahi, Afra; Stevenson, Suzanne
2008-01-01
How children go about learning the general regularities that govern language, as well as keeping track of the exceptions to them, remains one of the challenging open questions in the cognitive science of language. Computational modeling is an important methodology in research aimed at addressing this issue. We must determine appropriate learning…
2011-11-01
Presents Arthur C. Graesser as the 2011 winner of the American Psychological Association Award for Distinguished Contributions of Applications of Psychology to Education and Training. "As a multifaceted psychologist, cognitive engineer of useful education and training technologies, and mentor of new talent for the world of applied and translational cognitive science, Arthur C. Graesser is the perfect role model, showing how a strong scholar and intellect can shape both research and practice. His work is a mix of top-tier scholarship in psychology, education, intelligent systems, and computational linguistics. He combines cognitive science excellence with bold use of psychological knowledge and intelligent systems to design new generations of learning opportunities and to help lay the foundation for a translational science of learning." (PsycINFO Database Record (c) 2011 APA, all rights reserved). 2011 APA, all rights reserved
Applying Mathematical Optimization Methods to an ACT-R Instance-Based Learning Model.
Said, Nadia; Engelhart, Michael; Kirches, Christian; Körkel, Stefan; Holt, Daniel V
2016-01-01
Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.
NASA Astrophysics Data System (ADS)
Lamb, Richard L.
2016-02-01
Within the last 10 years, new tools for assisting in the teaching and learning of academic skills and content within the context of science have arisen. These new tools include multiple types of computer software and hardware to include (video) games. The purpose of this study was to examine and compare the effect of computer learning games in the form of three-dimensional serious educational games, two-dimensional online laboratories, and traditional lecture-based instruction in the context of student content learning in science. In particular, this study examines the impact of dimensionality, or the ability to move along the X-, Y-, and Z-axis in the games. Study subjects ( N = 551) were randomly selected using a stratified sampling technique. Independent strata subsamples were developed based upon the conditions of serious educational games, online laboratories, and lecture. The study also computationally models a potential mechanism of action and compares two- and three-dimensional learning environments. F test results suggest a significant difference for the main effect of condition across the factor of content gain score with large effect. Overall, comparisons using computational models suggest that three-dimensional serious educational games increase the level of success in learning as measured with content examinations through greater recruitment and attributional retraining of cognitive systems. The study supports assertions in the literature that the use of games in higher dimensions (i.e., three-dimensional versus two-dimensional) helps to increase student understanding of science concepts.
Evangelopoulos, Nicholas E
2013-11-01
This article reviews latent semantic analysis (LSA), a theory of meaning as well as a method for extracting that meaning from passages of text, based on statistical computations over a collection of documents. LSA as a theory of meaning defines a latent semantic space where documents and individual words are represented as vectors. LSA as a computational technique uses linear algebra to extract dimensions that represent that space. This representation enables the computation of similarity among terms and documents, categorization of terms and documents, and summarization of large collections of documents using automated procedures that mimic the way humans perform similar cognitive tasks. We present some technical details, various illustrative examples, and discuss a number of applications from linguistics, psychology, cognitive science, education, information science, and analysis of textual data in general. WIREs Cogn Sci 2013, 4:683-692. doi: 10.1002/wcs.1254 CONFLICT OF INTEREST: The author has declared no conflicts of interest for this article. For further resources related to this article, please visit the WIREs website. © 2013 John Wiley & Sons, Ltd.
Why formal learning theory matters for cognitive science.
Fulop, Sean; Chater, Nick
2013-01-01
This article reviews a number of different areas in the foundations of formal learning theory. After outlining the general framework for formal models of learning, the Bayesian approach to learning is summarized. This leads to a discussion of Solomonoff's Universal Prior Distribution for Bayesian learning. Gold's model of identification in the limit is also outlined. We next discuss a number of aspects of learning theory raised in contributed papers, related to both computational and representational complexity. The article concludes with a description of how semi-supervised learning can be applied to the study of cognitive learning models. Throughout this overview, the specific points raised by our contributing authors are connected to the models and methods under review. Copyright © 2013 Cognitive Science Society, Inc.
Structures, Not Strings: Linguistics as Part of the Cognitive Sciences.
Everaert, Martin B H; Huybregts, Marinus A C; Chomsky, Noam; Berwick, Robert C; Bolhuis, Johan J
2015-12-01
There are many questions one can ask about human language: its distinctive properties, neural representation, characteristic uses including use in communicative contexts, variation, growth in the individual, and origin. Every such inquiry is guided by some concept of what 'language' is. Sharpening the core question--what is language?--and paying close attention to the basic property of the language faculty and its biological foundations makes it clear how linguistics is firmly positioned within the cognitive sciences. Here we will show how recent developments in generative grammar, taking language as a computational cognitive mechanism seriously, allow us to address issues left unexplained in the increasingly popular surface-oriented approaches to language. Copyright © 2015 Elsevier Ltd. All rights reserved.
Leon Cooper, Cooper Pairs, and the BCS Theory
, psychology, mathematics, engineering, physics, linguistics and computer science. An Institute objective is to pave the way for the next generation of cognitive pharmaceuticals and intelligent systems for use in
Auditory expectation: the information dynamics of music perception and cognition.
Pearce, Marcus T; Wiggins, Geraint A
2012-10-01
Following in a psychological and musicological tradition beginning with Leonard Meyer, and continuing through David Huron, we present a functional, cognitive account of the phenomenon of expectation in music, grounded in computational, probabilistic modeling. We summarize a range of evidence for this approach, from psychology, neuroscience, musicology, linguistics, and creativity studies, and argue that simulating expectation is an important part of understanding a broad range of human faculties, in music and beyond. Copyright © 2012 Cognitive Science Society, Inc.
Probabilistic models of cognition: conceptual foundations.
Chater, Nick; Tenenbaum, Joshua B; Yuille, Alan
2006-07-01
Remarkable progress in the mathematics and computer science of probability has led to a revolution in the scope of probabilistic models. In particular, 'sophisticated' probabilistic methods apply to structured relational systems such as graphs and grammars, of immediate relevance to the cognitive sciences. This Special Issue outlines progress in this rapidly developing field, which provides a potentially unifying perspective across a wide range of domains and levels of explanation. Here, we introduce the historical and conceptual foundations of the approach, explore how the approach relates to studies of explicit probabilistic reasoning, and give a brief overview of the field as it stands today.
ERIC Educational Resources Information Center
Blikstein, Paulo; Wilensky, Uri
2009-01-01
This article reports on "MaterialSim", an undergraduate-level computational materials science set of constructionist activities which we have developed and tested in classrooms. We investigate: (a) the cognition of students engaging in scientific inquiry through interacting with simulations; (b) the effects of students programming simulations as…
ERIC Educational Resources Information Center
Hickey, Daniel T.; Kruger, Ann Cale; Fredrick, Laura D.; Schafer, Nancy Jo; Kindfield, Ann C. H.
This paper describes the GenScope Assessment Project, a project that is exploring ways of using multimedia computers to teach complex science content, refining sociocultural views of assessment and motivation, and considering different ways of reconciling the differences between these newer views and prior behavioral and cognitive views. The…
A cognitive computational model inspired by the immune system response.
Abdo Abd Al-Hady, Mohamed; Badr, Amr Ahmed; Mostafa, Mostafa Abd Al-Azim
2014-01-01
The immune system has a cognitive ability to differentiate between healthy and unhealthy cells. The immune system response (ISR) is stimulated by a disorder in the temporary fuzzy state that is oscillating between the healthy and unhealthy states. However, modeling the immune system is an enormous challenge; the paper introduces an extensive summary of how the immune system response functions, as an overview of a complex topic, to present the immune system as a cognitive intelligent agent. The homogeneity and perfection of the natural immune system have been always standing out as the sought-after model we attempted to imitate while building our proposed model of cognitive architecture. The paper divides the ISR into four logical phases: setting a computational architectural diagram for each phase, proceeding from functional perspectives (input, process, and output), and their consequences. The proposed architecture components are defined by matching biological operations with computational functions and hence with the framework of the paper. On the other hand, the architecture focuses on the interoperability of main theoretical immunological perspectives (classic, cognitive, and danger theory), as related to computer science terminologies. The paper presents a descriptive model of immune system, to figure out the nature of response, deemed to be intrinsic for building a hybrid computational model based on a cognitive intelligent agent perspective and inspired by the natural biology. To that end, this paper highlights the ISR phases as applied to a case study on hepatitis C virus, meanwhile illustrating our proposed architecture perspective.
A Cognitive Computational Model Inspired by the Immune System Response
Abdo Abd Al-Hady, Mohamed; Badr, Amr Ahmed; Mostafa, Mostafa Abd Al-Azim
2014-01-01
The immune system has a cognitive ability to differentiate between healthy and unhealthy cells. The immune system response (ISR) is stimulated by a disorder in the temporary fuzzy state that is oscillating between the healthy and unhealthy states. However, modeling the immune system is an enormous challenge; the paper introduces an extensive summary of how the immune system response functions, as an overview of a complex topic, to present the immune system as a cognitive intelligent agent. The homogeneity and perfection of the natural immune system have been always standing out as the sought-after model we attempted to imitate while building our proposed model of cognitive architecture. The paper divides the ISR into four logical phases: setting a computational architectural diagram for each phase, proceeding from functional perspectives (input, process, and output), and their consequences. The proposed architecture components are defined by matching biological operations with computational functions and hence with the framework of the paper. On the other hand, the architecture focuses on the interoperability of main theoretical immunological perspectives (classic, cognitive, and danger theory), as related to computer science terminologies. The paper presents a descriptive model of immune system, to figure out the nature of response, deemed to be intrinsic for building a hybrid computational model based on a cognitive intelligent agent perspective and inspired by the natural biology. To that end, this paper highlights the ISR phases as applied to a case study on hepatitis C virus, meanwhile illustrating our proposed architecture perspective. PMID:25003131
Logic as Marr's Computational Level: Four Case Studies.
Baggio, Giosuè; van Lambalgen, Michiel; Hagoort, Peter
2015-04-01
We sketch four applications of Marr's levels-of-analysis methodology to the relations between logic and experimental data in the cognitive neuroscience of language and reasoning. The first part of the paper illustrates the explanatory power of computational level theories based on logic. We show that a Bayesian treatment of the suppression task in reasoning with conditionals is ruled out by EEG data, supporting instead an analysis based on defeasible logic. Further, we describe how results from an EEG study on temporal prepositions can be reanalyzed using formal semantics, addressing a potential confound. The second part of the article demonstrates the predictive power of logical theories drawing on EEG data on processing progressive constructions and on behavioral data on conditional reasoning in people with autism. Logical theories can constrain processing hypotheses all the way down to neurophysiology, and conversely neuroscience data can guide the selection of alternative computational level models of cognition. Copyright © 2014 Cognitive Science Society, Inc.
The visual attention saliency map for movie retrospection
NASA Astrophysics Data System (ADS)
Rogalska, Anna; Napieralski, Piotr
2018-04-01
The visual saliency map is becoming important and challenging for many scientific disciplines (robotic systems, psychophysics, cognitive neuroscience and computer science). Map created by the model indicates possible salient regions by taking into consideration face presence and motion which is essential in motion pictures. By combining we can obtain credible saliency map with a low computational cost.
Counterfactuals and Causal Models: Introduction to the Special Issue
ERIC Educational Resources Information Center
Sloman, Steven A.
2013-01-01
Judea Pearl won the 2010 Rumelhart Prize in computational cognitive science due to his seminal contributions to the development of Bayes nets and causal Bayes nets, frameworks that are central to multiple domains of the computational study of mind. At the heart of the causal Bayes nets formalism is the notion of a counterfactual, a representation…
The simplicity principle in perception and cognition
Feldman, Jacob
2016-01-01
The simplicity principle, traditionally referred to as Occam’s razor, is the idea that simpler explanations of observations should be preferred to more complex ones. In recent decades the principle has been clarified via the incorporation of modern notions of computation and probability, allowing a more precise understanding of how exactly complexity minimization facilitates inference. The simplicity principle has found many applications in modern cognitive science, in contexts as diverse as perception, categorization, reasoning, and neuroscience. In all these areas, the common idea is that the mind seeks the simplest available interpretation of observations— or, more precisely, that it balances a bias towards simplicity with a somewhat opposed constraint to choose models consistent with perceptual or cognitive observations. This brief tutorial surveys some of the uses of the simplicity principle across cognitive science, emphasizing how complexity minimization in a number of forms has been incorporated into probabilistic models of inference. PMID:27470193
Internal Models, Vestibular Cognition, and Mental Imagery: Conceptual Considerations.
Mast, Fred W; Ellis, Andrew W
2015-01-01
Vestibular cognition has recently gained attention. Despite numerous experimental and clinical demonstrations, it is not yet clear what vestibular cognition really is. For future research in vestibular cognition, adopting a computational approach will make it easier to explore the underlying mechanisms. Indeed, most modeling approaches in vestibular science include a top-down or a priori component. We review recent Bayesian optimal observer models, and discuss in detail the conceptual value of prior assumptions, likelihood and posterior estimates for research in vestibular cognition. We then consider forward models in vestibular processing, which are required in order to distinguish between sensory input that is induced by active self-motion, and sensory input that is due to passive self-motion. We suggest that forward models are used not only in the service of estimating sensory states but they can also be drawn upon in an offline mode (e.g., spatial perspective transformations), in which interaction with sensory input is not desired. A computational approach to vestibular cognition will help to discover connections across studies, and it will provide a more coherent framework for investigating vestibular cognition.
Using Pedagogical Tools to Help Hispanics be Successful in Computer Science
NASA Astrophysics Data System (ADS)
Irish, Rodger
Irish, Rodger, Using Pedagogical Tools to Help Hispanics Be Successful in Computer Science. Master of Science (MS), July 2017, 68 pp., 4 tables, 2 figures, references 48 titles. Computer science (CS) jobs are a growing field and pay a living wage, but the Hispanics are underrepresented in this field. This project seeks to give an overview of several contributing factors to this problem. It will then explore some possible solutions to this problem and how a combination of some tools (teaching methods) can create the best possible outcome. It is my belief that this approach can produce successful Hispanics to fill the needed jobs in the CS field. Then the project will test its hypothesis. I will discuss the tools used to measure progress both in the affective and the cognitive domains. I will show how the decision to run a Computer Club was reached and the results of the research. The conclusion will summarize the results and tell of future research that still needs to be done.
Human-computer interaction: psychological aspects of the human use of computing.
Olson, Gary M; Olson, Judith S
2003-01-01
Human-computer interaction (HCI) is a multidisciplinary field in which psychology and other social sciences unite with computer science and related technical fields with the goal of making computing systems that are both useful and usable. It is a blend of applied and basic research, both drawing from psychological research and contributing new ideas to it. New technologies continuously challenge HCI researchers with new options, as do the demands of new audiences and uses. A variety of usability methods have been developed that draw upon psychological principles. HCI research has expanded beyond its roots in the cognitive processes of individual users to include social and organizational processes involved in computer usage in real environments as well as the use of computers in collaboration. HCI researchers need to be mindful of the longer-term changes brought about by the use of computing in a variety of venues.
What's New in Software? Computer Programs for Unobtrusive, Informal Evaluation.
ERIC Educational Resources Information Center
Hedley, Carolyn
1985-01-01
Teachers can use microcomputers in informal assessment of learning disabled students' academic achievement, math and science progress, reading comprehension, cognitive processes, motivation and social interaction. Selected software for unobtrusive, informal assessment is listed. (CL)
A Revision of Learning and Teaching = Revision del aprender y del ensenar.
ERIC Educational Resources Information Center
Reggini, Horace C.
1983-01-01
This review of the findings of recent cognitive science research pertaining to learning and teaching focuses on how science and mathematics are being taught, analyzes how the presence of the computer demonstrates a need for radical rethinking of both the theory and the practice of learning, and points out that if educators fail to consider the…
ERIC Educational Resources Information Center
Valanides, Nicos; Angeli, Charoula
2008-01-01
In this study, we discuss the scaffolded design of ODRES (Observe, Discuss, and Reason with Evidence in Science), a computer tool that was designed to be used with elementary school children in science, and report on the effects of learning with ODRES on students' conceptual understandings about light, color, and vision. Succinctly, dyads of…
Critical branching neural networks.
Kello, Christopher T
2013-01-01
It is now well-established that intrinsic variations in human neural and behavioral activity tend to exhibit scaling laws in their fluctuations and distributions. The meaning of these scaling laws is an ongoing matter of debate between isolable causes versus pervasive causes. A spiking neural network model is presented that self-tunes to critical branching and, in doing so, simulates observed scaling laws as pervasive to neural and behavioral activity. These scaling laws are related to neural and cognitive functions, in that critical branching is shown to yield spiking activity with maximal memory and encoding capacities when analyzed using reservoir computing techniques. The model is also shown to account for findings of pervasive 1/f scaling in speech and cued response behaviors that are difficult to explain by isolable causes. Issues and questions raised by the model and its results are discussed from the perspectives of physics, neuroscience, computer and information sciences, and psychological and cognitive sciences.
Toward using alpha and theta brain waves to quantify programmer expertise.
Crk, Igor; Kluthe, Timothy
2014-01-01
Empirical studies of programming language learnability and usability have thus far depended on indirect measures of human cognitive performance, attempting to capture what is at its essence a purely cognitive exercise through various indicators of comprehension, such as the correctness of coding tasks or the time spent working out the meaning of code and producing acceptable solutions. Understanding program comprehension is essential to understanding the inherent complexity of programming languages, and ultimately, having a measure of mental effort based on direct observation of the brain at work will illuminate the nature of the work of programming. We provide evidence of direct observation of the cognitive effort associated with programming tasks, through a carefully constructed empirical study using a cross-section of undergraduate computer science students and an inexpensive, off-the-shelf brain-computer interface device. This study presents a link between expertise and programming language comprehension, draws conclusions about the observed indicators of cognitive effort using recent cognitive theories, and proposes directions for future work that is now possible.
Veksler, Vladislav D; Buchler, Norbou; Hoffman, Blaine E; Cassenti, Daniel N; Sample, Char; Sugrim, Shridat
2018-01-01
Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision likelihood distributions, (b) human factors of cyber tools to address human system integration challenges, estimation of defender cognitive states, and opportunities for automation, (c) dynamic simulations involving attacker, defender, and user models to enhance studies of cyber epidemiology and cyber hygiene, and (d) training effectiveness research and training scenarios to address human cyber-security performance, maturation of cyber-security skill sets, and effective decision-making. Models may be initially constructed at the group-level based on mean tendencies of each subject's subgroup, based on known statistics such as specific skill proficiencies, demographic characteristics, and cultural factors. For more precise and accurate predictions, cognitive models may be fine-tuned to each individual attacker, defender, or user profile, and updated over time (based on recorded behavior) via techniques such as model tracing and dynamic parameter fitting.
Teachers' Organization of Participation Structures for Teaching Science with Computer Technology
NASA Astrophysics Data System (ADS)
Subramaniam, Karthigeyan
2016-08-01
This paper describes a qualitative study that investigated the nature of the participation structures and how the participation structures were organized by four science teachers when they constructed and communicated science content in their classrooms with computer technology. Participation structures focus on the activity structures and processes in social settings like classrooms thereby providing glimpses into the complex dynamics of teacher-students interactions, configurations, and conventions during collective meaning making and knowledge creation. Data included observations, interviews, and focus group interviews. Analysis revealed that the dominant participation structure evident within participants' instruction with computer technology was ( Teacher) initiation-( Student and Teacher) response sequences-( Teacher) evaluate participation structure. Three key events characterized the how participants organized this participation structure in their classrooms: setting the stage for interactive instruction, the joint activity, and maintaining accountability. Implications include the following: (1) teacher educators need to tap into the knowledge base that underscores science teachers' learning to teach philosophies when computer technology is used in instruction. (2) Teacher educators need to emphasize the essential idea that learning and cognition is not situated within the computer technology but within the pedagogical practices, specifically the participation structures. (3) The pedagogical practices developed with the integration or with the use of computer technology underscored by the teachers' own knowledge of classroom contexts and curriculum needs to be the focus for how students learn science content with computer technology instead of just focusing on how computer technology solely supports students learning of science content.
Towards Modeling False Memory With Computational Knowledge Bases.
Li, Justin; Kohanyi, Emma
2017-01-01
One challenge to creating realistic cognitive models of memory is the inability to account for the vast common-sense knowledge of human participants. Large computational knowledge bases such as WordNet and DBpedia may offer a solution to this problem but may pose other challenges. This paper explores some of these difficulties through a semantic network spreading activation model of the Deese-Roediger-McDermott false memory task. In three experiments, we show that these knowledge bases only capture a subset of human associations, while irrelevant information introduces noise and makes efficient modeling difficult. We conclude that the contents of these knowledge bases must be augmented and, more important, that the algorithms must be refined and optimized, before large knowledge bases can be widely used for cognitive modeling. Copyright © 2016 Cognitive Science Society, Inc.
Mild Cognitive Impairment: What Do We Do Now?
... in studies that focus on individual health, computer use and technology, family relationships and caregiving, community services, housing, and ... Reserve Officer Training Corps Navy Research Centers Science, Technology, and ... of Education School of Performing Arts College Office of the ...
Building Scalable Knowledge Graphs for Earth Science
NASA Astrophysics Data System (ADS)
Ramachandran, R.; Maskey, M.; Gatlin, P. N.; Zhang, J.; Duan, X.; Bugbee, K.; Christopher, S. A.; Miller, J. J.
2017-12-01
Estimates indicate that the world's information will grow by 800% in the next five years. In any given field, a single researcher or a team of researchers cannot keep up with this rate of knowledge expansion without the help of cognitive systems. Cognitive computing, defined as the use of information technology to augment human cognition, can help tackle large systemic problems. Knowledge graphs, one of the foundational components of cognitive systems, link key entities in a specific domain with other entities via relationships. Researchers could mine these graphs to make probabilistic recommendations and to infer new knowledge. At this point, however, there is a dearth of tools to generate scalable Knowledge graphs using existing corpus of scientific literature for Earth science research. Our project is currently developing an end-to-end automated methodology for incrementally constructing Knowledge graphs for Earth Science. Semantic Entity Recognition (SER) is one of the key steps in this methodology. SER for Earth Science uses external resources (including metadata catalogs and controlled vocabulary) as references to guide entity extraction and recognition (i.e., labeling) from unstructured text, in order to build a large training set to seed the subsequent auto-learning component in our algorithm. Results from several SER experiments will be presented as well as lessons learned.
Computational physics of the mind
NASA Astrophysics Data System (ADS)
Duch, Włodzisław
1996-08-01
In the XIX century and earlier physicists such as Newton, Mayer, Hooke, Helmholtz and Mach were actively engaged in the research on psychophysics, trying to relate psychological sensations to intensities of physical stimuli. Computational physics allows to simulate complex neural processes giving a chance to answer not only the original psychophysical questions but also to create models of the mind. In this paper several approaches relevant to modeling of the mind are outlined. Since direct modeling of the brain functions is rather limited due to the complexity of such models a number of approximations is introduced. The path from the brain, or computational neurosciences, to the mind, or cognitive sciences, is sketched, with emphasis on higher cognitive functions such as memory and consciousness. No fundamental problems in understanding of the mind seem to arise. From a computational point of view realistic models require massively parallel architectures.
Quantum walks in brain microtubules--a biomolecular basis for quantum cognition?
Hameroff, Stuart
2014-01-01
Cognitive decisions are best described by quantum mathematics. Do quantum information devices operate in the brain? What would they look like? Fuss and Navarro () describe quantum lattice registers in which quantum superpositioned pathways interact (compute/integrate) as 'quantum walks' akin to Feynman's path integral in a lattice (e.g. the 'Feynman quantum chessboard'). Simultaneous alternate pathways eventually reduce (collapse), selecting one particular pathway in a cognitive decision, or choice. This paper describes how quantum walks in a Feynman chessboard are conceptually identical to 'topological qubits' in brain neuronal microtubules, as described in the Penrose-Hameroff 'Orch OR' theory of consciousness. Copyright © 2013 Cognitive Science Society, Inc.
ERIC Educational Resources Information Center
Arnseth, Hans Christian; Krange, Ingeborg
2016-01-01
In this article we analyze how the joint cognitive system of teacher and student actions mediated by cultural tools develops sense making of science concepts, and the use of concepts as tools for explaining phenomena and processes related to energy and energy transformation. We take a sociocultural approach to the analysis of how material and…
NASA Astrophysics Data System (ADS)
Knappenberger, Naomi
This dissertation examines factors which may affect the educational effectiveness of science exhibits. Exhibit effectiveness is the result of a complex interaction among exhibit features, cognitive characteristics of the museum visitor, and educational outcomes. The purpose of this study was to determine the relative proportions of field-dependent and field-independent visitors in the museum audience, and to ascertain if the cognitive style of visitors interacted with instructional strategies to affect the educational outcomes for a computer-based science exhibit. Cognitive style refers to the self-consistent modes of selecting and processing information that an individual employs throughout his or her perceptual and intellectual activities. It has a broad influence on many aspects of personality and behavior, including perception, memory, problem solving, interest, and even social behaviors and self-concept. As such, it constitutes essential dimensions of individual differences among museum visitors and has important implications for instructional design in the museum. The study was conducted in the spring of 1998 at the Adler Planetarium and Astronomy Museum in Chicago. Two experimental treatments of a computer-based exhibit were tested in the study. The first experimental treatment utilized strategies designed for field-dependent visitors that limited the text and provided more structure and cueing than the baseline treatment of the computer program. The other experimental treatment utilized strategies designed for field-independent visitors that provided hypothesis-testing and more contextual information. Approximately two-thirds of the visitors were field-independent. The results of a multiple regression analysis indicated that there was a significant interaction between cognitive style and instructional strategy that affected visitors' posttest scores on a multiple-choice test of the content. Field-independent visitors out- performed the field-dependent visitors in the control, baseline, and both experimental treatments. Both field-dependent and field-independent visitor posttest scores increased in the field-dependent experimental treatment and in the field-independent treatment. The most effective treatment for all visitors was the field-independent treatment. Criteria for designing a computer-based exhibit to meet the needs of all visitors were recommended. These included organized, concise text; a structured, rather than exploratory design; and cueing in the form of questions, bold fonts, underlining of important words and concepts, and captioned images.
Educational Technology: Integration?
ERIC Educational Resources Information Center
Christensen, Dean L.; Tennyson, Robert D.
This paper presents a perspective of the current state of technology-assisted instruction integrating computer language, artificial intelligence (AI), and a review of cognitive science applied to instruction. The following topics are briefly discussed: (1) the language of instructional technology, i.e., programming languages, including authoring…
Federal Register 2010, 2011, 2012, 2013, 2014
2013-11-08
... analysis, survey methodology, geospatial analysis, econometrics, cognitive psychology, and computer science... following disciplines: demography, economics, geography, psychology, statistics, survey methodology, social... expertise in such areas as demography, economics, geography, psychology, statistics, survey methodology...
The Search for New Intellectual Technologies.
ERIC Educational Resources Information Center
Molnar, Andrew R.
1982-01-01
Among the topics discussed relating to demands on business/industry/education resulting from the "pull" of the information explosion are: frontiers of knowledge, research on educational television, computer-based learning, intelligent videodiscs, quality of learning, science education/cognitive research, misconceptions, motivation,…
Schrodt, Fabian; Kneissler, Jan; Ehrenfeld, Stephan; Butz, Martin V
2017-04-01
In line with Allen Newell's challenge to develop complete cognitive architectures, and motivated by a recent proposal for a unifying subsymbolic computational theory of cognition, we introduce the cognitive control architecture SEMLINCS. SEMLINCS models the development of an embodied cognitive agent that learns discrete production rule-like structures from its own, autonomously gathered, continuous sensorimotor experiences. Moreover, the agent uses the developing knowledge to plan and control environmental interactions in a versatile, goal-directed, and self-motivated manner. Thus, in contrast to several well-known symbolic cognitive architectures, SEMLINCS is not provided with production rules and the involved symbols, but it learns them. In this paper, the actual implementation of SEMLINCS causes learning and self-motivated, autonomous behavioral control of the game figure Mario in a clone of the computer game Super Mario Bros. Our evaluations highlight the successful development of behavioral versatility as well as the learning of suitable production rules and the involved symbols from sensorimotor experiences. Moreover, knowledge- and motivation-dependent individualizations of the agents' behavioral tendencies are shown. Finally, interaction sequences can be planned on the sensorimotor-grounded production rule level. Current limitations directly point toward the need for several further enhancements, which may be integrated into SEMLINCS in the near future. Overall, SEMLINCS may be viewed as an architecture that allows the functional and computational modeling of embodied cognitive development, whereby the current main focus lies on the development of production rules from sensorimotor experiences. Copyright © 2017 Cognitive Science Society, Inc.
Crupi, Vincenzo; Nelson, Jonathan D; Meder, Björn; Cevolani, Gustavo; Tentori, Katya
2018-06-17
Searching for information is critical in many situations. In medicine, for instance, careful choice of a diagnostic test can help narrow down the range of plausible diseases that the patient might have. In a probabilistic framework, test selection is often modeled by assuming that people's goal is to reduce uncertainty about possible states of the world. In cognitive science, psychology, and medical decision making, Shannon entropy is the most prominent and most widely used model to formalize probabilistic uncertainty and the reduction thereof. However, a variety of alternative entropy metrics (Hartley, Quadratic, Tsallis, Rényi, and more) are popular in the social and the natural sciences, computer science, and philosophy of science. Particular entropy measures have been predominant in particular research areas, and it is often an open issue whether these divergences emerge from different theoretical and practical goals or are merely due to historical accident. Cutting across disciplinary boundaries, we show that several entropy and entropy reduction measures arise as special cases in a unified formalism, the Sharma-Mittal framework. Using mathematical results, computer simulations, and analyses of published behavioral data, we discuss four key questions: How do various entropy models relate to each other? What insights can be obtained by considering diverse entropy models within a unified framework? What is the psychological plausibility of different entropy models? What new questions and insights for research on human information acquisition follow? Our work provides several new pathways for theoretical and empirical research, reconciling apparently conflicting approaches and empirical findings within a comprehensive and unified information-theoretic formalism. Copyright © 2018 Cognitive Science Society, Inc.
Neurobiomimetic constructs for intelligent unmanned systems and robotics
NASA Astrophysics Data System (ADS)
Braun, Jerome J.; Shah, Danelle C.; DeAngelus, Marianne A.
2014-06-01
This paper discusses a paradigm we refer to as neurobiomimetic, which involves emulations of brain neuroanatomy and neurobiology aspects and processes. Neurobiomimetic constructs include rudimentary and down-scaled computational representations of brain regions, sub-regions, and synaptic connectivity. Many different instances of neurobiomimetic constructs are possible, depending on various aspects such as the initial conditions of synaptic connectivity, number of neuron elements in regions, connectivity specifics, and more, and we refer to these instances as `animats'. While downscaled for computational feasibility, the animats are very large constructs; the animats implemented in this work contain over 47,000 neuron elements and over 720,000 synaptic connections. The paper outlines aspects of the animats implemented, spatial memory and learning cognitive task, the virtual-reality environment constructed to study the animat performing that task, and discussion of results. In a broad sense, we argue that the neurobiomimetic paradigm pursued in this work constitutes a particularly promising path to artificial cognition and intelligent unmanned systems. Biological brains readily cope with challenges of real-life tasks that consistently prove beyond even the most sophisticated algorithmic approaches known. At the cross-over point of neuroscience, cognitive science and computer science, paradigms such as the one pursued in this work aim to mimic the mechanisms of biological brains and as such, we argue, may lead to machines with abilities closer to those of biological species.
The body of knowledge: On the role of the living body in grounding embodied cognition.
Ziemke, Tom
2016-10-01
Embodied cognition is a hot topic in both cognitive science and AI, despite the fact that there still is relatively little consensus regarding what exactly constitutes 'embodiment'. While most embodied AI and cognitive robotics research views the body as the physical/sensorimotor interface that allows to ground computational cognitive processes in sensorimotor interactions with the environment, more biologically-based notions of embodied cognition emphasize the fundamental role that the living body - and more specifically its homeostatic/allostatic self-regulation - plays in grounding both sensorimotor interactions and embodied cognitive processes. Adopting the latter position - a multi-tiered affectively embodied view of cognition in living systems - it is further argued that modeling organisms as layered networks of bodily self-regulation mechanisms can make significant contributions to our scientific understanding of embodied cognition. Copyright © 2016 The Author. Published by Elsevier Ireland Ltd.. All rights reserved.
Philosophy for the rest of cognitive science.
Stepp, Nigel; Chemero, Anthony; Turvey, Michael T
2011-04-01
Cognitive science has always included multiple methodologies and theoretical commitments. The philosophy of cognitive science should embrace, or at least acknowledge, this diversity. Bechtel's (2009a) proposed philosophy of cognitive science, however, applies only to representationalist and mechanist cognitive science, ignoring the substantial minority of dynamically oriented cognitive scientists. As an example of nonrepresentational, dynamical cognitive science, we describe strong anticipation as a model for circadian systems (Stepp & Turvey, 2009). We then propose a philosophy of science appropriate to nonrepresentational, dynamical cognitive science. Copyright © 2011 Cognitive Science Society, Inc.
Exemplar Models as a Mechanism for Performing Bayesian Inference
2010-01-01
Feldman Department of Cognitive and Linguistic Sciences Brown University Adam N. Sanborn Gatsby Computational Neuroscience Unit University College London...problem. As noted above, particle filters are another instance of a rational process model, but the great diversity of efficient approximation algorithms
Computer-aided psychotherapy based on multimodal elicitation, estimation and regulation of emotion.
Cosić, Krešimir; Popović, Siniša; Horvat, Marko; Kukolja, Davor; Dropuljić, Branimir; Kovač, Bernard; Jakovljević, Miro
2013-09-01
Contemporary psychiatry is looking at affective sciences to understand human behavior, cognition and the mind in health and disease. Since it has been recognized that emotions have a pivotal role for the human mind, an ever increasing number of laboratories and research centers are interested in affective sciences, affective neuroscience, affective psychology and affective psychopathology. Therefore, this paper presents multidisciplinary research results of Laboratory for Interactive Simulation System at Faculty of Electrical Engineering and Computing, University of Zagreb in the stress resilience. Patient's distortion in emotional processing of multimodal input stimuli is predominantly consequence of his/her cognitive deficit which is result of their individual mental health disorders. These emotional distortions in patient's multimodal physiological, facial, acoustic, and linguistic features related to presented stimulation can be used as indicator of patient's mental illness. Real-time processing and analysis of patient's multimodal response related to annotated input stimuli is based on appropriate machine learning methods from computer science. Comprehensive longitudinal multimodal analysis of patient's emotion, mood, feelings, attention, motivation, decision-making, and working memory in synchronization with multimodal stimuli provides extremely valuable big database for data mining, machine learning and machine reasoning. Presented multimedia stimuli sequence includes personalized images, movies and sounds, as well as semantically congruent narratives. Simultaneously, with stimuli presentation patient provides subjective emotional ratings of presented stimuli in terms of subjective units of discomfort/distress, discrete emotions, or valence and arousal. These subjective emotional ratings of input stimuli and corresponding physiological, speech, and facial output features provides enough information for evaluation of patient's cognitive appraisal deficit. Aggregated real-time visualization of this information provides valuable assistance in patient mental state diagnostics enabling therapist deeper and broader insights into dynamics and progress of the psychotherapy.
Design of a Workstation by a Cognitive Approach
Jaspers, MWM; Steen, T.; Geelen, M.; van den Bos, C.
2001-01-01
To ensure ultimate acceptance of computer systems that are easy to use, provide the desired functionality and fits into users work practices requires the use of improved methods for system design and evaluation. Both designing and evaluating workstations that link up smoothly with daily routine of physicians' work requires a thorough understanding of their working practices. The application of methods from cognitive science may contribute to a thorough understanding of the activities involved in medical information processing. We used cognitive task analysis in designing a physicians' workstation, which seems a promising method to ensure that the system meets the user needs.
Veksler, Vladislav D.; Buchler, Norbou; Hoffman, Blaine E.; Cassenti, Daniel N.; Sample, Char; Sugrim, Shridat
2018-01-01
Computational models of cognitive processes may be employed in cyber-security tools, experiments, and simulations to address human agency and effective decision-making in keeping computational networks secure. Cognitive modeling can addresses multi-disciplinary cyber-security challenges requiring cross-cutting approaches over the human and computational sciences such as the following: (a) adversarial reasoning and behavioral game theory to predict attacker subjective utilities and decision likelihood distributions, (b) human factors of cyber tools to address human system integration challenges, estimation of defender cognitive states, and opportunities for automation, (c) dynamic simulations involving attacker, defender, and user models to enhance studies of cyber epidemiology and cyber hygiene, and (d) training effectiveness research and training scenarios to address human cyber-security performance, maturation of cyber-security skill sets, and effective decision-making. Models may be initially constructed at the group-level based on mean tendencies of each subject's subgroup, based on known statistics such as specific skill proficiencies, demographic characteristics, and cultural factors. For more precise and accurate predictions, cognitive models may be fine-tuned to each individual attacker, defender, or user profile, and updated over time (based on recorded behavior) via techniques such as model tracing and dynamic parameter fitting. PMID:29867661
NASA Astrophysics Data System (ADS)
Dennett, Daniel
2014-09-01
Fitch [5] has not only articulated a growing consensus, after decades of ideological quarreling, about how to put cognitive science together, but in the process has attempted to advance the unification process with some bold strokes of his own. His proposal [4] that we take seriously the perspective which replaces "spherical neurons" (McCulloch Pitts logical neurons and their close kin) with neurons that are micro-agents with agendas and computational talents of their own, has been taken up by a variety of theorists, including myself [2,3]. Now his dendrophilia hypothesis promises to distill the core truths energizing the heated debates about the innate equipment that distinguishes the cognitive competences of our species from all others. Whether this promise can be kept is a wide-open empirical question, but Fitch has given us enough specification to justify a serious investment in answering it.
Feature Statistics Modulate the Activation of Meaning During Spoken Word Processing.
Devereux, Barry J; Taylor, Kirsten I; Randall, Billi; Geertzen, Jeroen; Tyler, Lorraine K
2016-03-01
Understanding spoken words involves a rapid mapping from speech to conceptual representations. One distributed feature-based conceptual account assumes that the statistical characteristics of concepts' features--the number of concepts they occur in (distinctiveness/sharedness) and likelihood of co-occurrence (correlational strength)--determine conceptual activation. To test these claims, we investigated the role of distinctiveness/sharedness and correlational strength in speech-to-meaning mapping, using a lexical decision task and computational simulations. Responses were faster for concepts with higher sharedness, suggesting that shared features are facilitatory in tasks like lexical decision that require access to them. Correlational strength facilitated responses for slower participants, suggesting a time-sensitive co-occurrence-driven settling mechanism. The computational simulation showed similar effects, with early effects of shared features and later effects of correlational strength. These results support a general-to-specific account of conceptual processing, whereby early activation of shared features is followed by the gradual emergence of a specific target representation. Copyright © 2015 The Authors. Cognitive Science published by Cognitive Science Society, Inc.
3D Object Recognition: Symmetry and Virtual Views
1992-12-01
NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATIONI Artificial Intelligence Laboratory REPORT NUMBER 545 Technology Square AIM 1409 Cambridge... ARTIFICIAL INTELLIGENCE LABORATORY and CENTER FOR BIOLOGICAL AND COMPUTATIONAL LEARNING A.I. Memo No. 1409 December 1992 C.B.C.L. Paper No. 76 3D Object...research done within the Center for Biological and Computational Learning in the Department of Brain and Cognitive Sciences, and at the Artificial
NASA Technical Reports Server (NTRS)
Brooks, Rodney Allen; Stein, Lynn Andrea
1994-01-01
We describe a project to capitalize on newly available levels of computational resources in order to understand human cognition. We will build an integrated physical system including vision, sound input and output, and dextrous manipulation, all controlled by a continuously operating large scale parallel MIMD computer. The resulting system will learn to 'think' by building on its bodily experiences to accomplish progressively more abstract tasks. Past experience suggests that in attempting to build such an integrated system we will have to fundamentally change the way artificial intelligence, cognitive science, linguistics, and philosophy think about the organization of intelligence. We expect to be able to better reconcile the theories that will be developed with current work in neuroscience.
Exploring Music-Based Rehabilitation for Parkinsonism through Embodied Cognitive Science
Schiavio, Andrea; Altenmüller, Eckart
2015-01-01
Recent embodied approaches in cognitive sciences emphasize the constitutive roles of bodies and environment in driving cognitive processes. Cognition is thus seen as a distributed system based on the continuous interaction of bodies, brains, and environment. These categories, moreover, do not relate only causally, through a sequential input–output network of computations; rather, they are dynamically enfolded in each other, being mutually implemented by the concrete patterns of actions adopted by the cognitive system. However, while this claim has been widely discussed across various disciplines, its relevance and potential beneficial applications for music therapy remain largely unexplored. With this in mind, we provide here an overview of the embodied approaches to cognition, discussing their main tenets through the lenses of music therapy. In doing so, we question established methodological and theoretical paradigms and identify possible novel strategies for intervention. In particular, we refer to the music-based rehabilitative protocols adopted for Parkinson’s disease patients. Indeed, in this context, it has recently been observed that music therapy not only affects movement-related skills but that it also contributes to stabilizing physiological functions and improving socio-affective behaviors. We argue that these phenomena involve previously unconsidered aspects of cognition and (motor) behavior, which are rooted in the action-perception cycle characterizing the whole living system. PMID:26539155
Exploring Music-Based Rehabilitation for Parkinsonism through Embodied Cognitive Science.
Schiavio, Andrea; Altenmüller, Eckart
2015-01-01
Recent embodied approaches in cognitive sciences emphasize the constitutive roles of bodies and environment in driving cognitive processes. Cognition is thus seen as a distributed system based on the continuous interaction of bodies, brains, and environment. These categories, moreover, do not relate only causally, through a sequential input-output network of computations; rather, they are dynamically enfolded in each other, being mutually implemented by the concrete patterns of actions adopted by the cognitive system. However, while this claim has been widely discussed across various disciplines, its relevance and potential beneficial applications for music therapy remain largely unexplored. With this in mind, we provide here an overview of the embodied approaches to cognition, discussing their main tenets through the lenses of music therapy. In doing so, we question established methodological and theoretical paradigms and identify possible novel strategies for intervention. In particular, we refer to the music-based rehabilitative protocols adopted for Parkinson's disease patients. Indeed, in this context, it has recently been observed that music therapy not only affects movement-related skills but that it also contributes to stabilizing physiological functions and improving socio-affective behaviors. We argue that these phenomena involve previously unconsidered aspects of cognition and (motor) behavior, which are rooted in the action-perception cycle characterizing the whole living system.
Constructing a philosophy of science of cognitive science.
Bechtel, William
2009-07-01
Philosophy of science is positioned to make distinctive contributions to cognitive science by providing perspective on its conceptual foundations and by advancing normative recommendations. The philosophy of science I embrace is naturalistic in that it is grounded in the study of actual science. Focusing on explanation, I describe the recent development of a mechanistic philosophy of science from which I draw three normative consequences for cognitive science. First, insofar as cognitive mechanisms are information-processing mechanisms, cognitive science needs an account of how the representations invoked in cognitive mechanisms carry information about contents, and I suggest that control theory offers the needed perspective on the relation of representations to contents. Second, I argue that cognitive science requires, but is still in search of, a catalog of cognitive operations that researchers can draw upon in explaining cognitive mechanisms. Last, I provide a new perspective on the relation of cognitive science to brain sciences, one which embraces both reductive research on neural components that figure in cognitive mechanisms and a concern with recomposing higher-level mechanisms from their components and situating them in their environments. Copyright © 2009 Cognitive Science Society, Inc.
Cavagnaro, Daniel R; Myung, Jay I; Pitt, Mark A; Kujala, Janne V
2010-04-01
Discriminating among competing statistical models is a pressing issue for many experimentalists in the field of cognitive science. Resolving this issue begins with designing maximally informative experiments. To this end, the problem to be solved in adaptive design optimization is identifying experimental designs under which one can infer the underlying model in the fewest possible steps. When the models under consideration are nonlinear, as is often the case in cognitive science, this problem can be impossible to solve analytically without simplifying assumptions. However, as we show in this letter, a full solution can be found numerically with the help of a Bayesian computational trick derived from the statistics literature, which recasts the problem as a probability density simulation in which the optimal design is the mode of the density. We use a utility function based on mutual information and give three intuitive interpretations of the utility function in terms of Bayesian posterior estimates. As a proof of concept, we offer a simple example application to an experiment on memory retention.
A Model for Designing Library Instruction for Distance Learning
ERIC Educational Resources Information Center
Rand, Angela Doucet
2013-01-01
Providing library instruction in distance learning environments presents a unique set of challenges for instructional librarians. Innovations in computer-mediated communication and advances in cognitive science research provide the opportunity for designing library instruction that meets a variety of student information seeking needs. Using a…
Culture and Cognition in Information Technology Education
ERIC Educational Resources Information Center
Holvikivi, Jaana
2007-01-01
This paper aims at explaining the outcomes of information technology education for international students using anthropological theories of cultural schemas. Even though computer science and engineering are usually assumed to be culture-independent, the practice in classrooms seems to indicate that learning patterns depend on culture. The…
Scientists at Work. Final Report.
ERIC Educational Resources Information Center
Education Turnkey Systems, Inc., Falls Church, VA.
This report summarizes activities related to the development, field testing, evaluation, and marketing of the "Scientists at Work" program which combines computer assisted instruction with database tools to aid cognitively impaired middle and early high school children in learning and applying thinking skills to science. The brief report reviews…
Cognitive anthropology is a cognitive science.
Boster, James S
2012-07-01
Cognitive anthropology contributes to cognitive science as a complement to cognitive psychology. The chief threat to its survival has not been rejection by other cognitive scientists but by other cultural anthropologists. It will remain a part of cognitive science as long as cognitive anthropologists research, teach, and publish. Copyright © 2012 Cognitive Science Society, Inc.
NASA Astrophysics Data System (ADS)
Rothman, Alan H.
This study reports the results of research designed to examine the impact of computer-based science instruction on elementary school level students' science content achievement, their attitude about science learning, their level of critical thinking-inquiry skills, and their level of cognitive and English language development. The study compared these learning outcomes resulting from a computer-based approach compared to the learning outcomes from a traditional, textbook-based approach to science instruction. The computer-based approach was inherent in a curriculum titled The Voyage of the Mimi , published by The Bank Street College Project in Science and Mathematics (1984). The study sample included 209 fifth-grade students enrolled in three schools in a suburban school district. This sample was divided into three groups, each receiving one of the following instructional treatments: (a) Mixed-instruction primarily based on the use of a hardcopy textbook in conjunction with computer-based instructional materials as one component of the science course; (b) Non-Traditional, Technology-Based -instruction fully utilizing computer-based material; and (c) Traditional, Textbook-Based-instruction utilizing only the textbook as the basis for instruction. Pre-test, or pre-treatment, data related to each of the student learning outcomes was collected at the beginning of the school year and post-test data was collected at the end of the school year. Statistical analyses of pre-test data were used as a covariate to account for possible pre-existing differences with regard to the variables examined among the three student groups. This study concluded that non-traditional, computer-based instruction in science significantly improved students' attitudes toward science learning and their level of English language development. Non-significant, positive trends were found for the following student learning outcomes: overall science achievement and development of critical thinking-inquiry skills. These conclusions support the value of a non-traditional, computer-based approach to instruction, such as exemplified by The Voyage of the Mimi curriculum, and a recommendation for reform in science teaching that has recommended the use of computer technology to enhance learning outcomes from science instruction to assist in reversing the trend toward what has been perceived to be relatively poor science performance by American students, as documented by the 1996 Third International Mathematics and Science Study (TIMSS).
Herdağdelen, Amaç; Marelli, Marco
2017-05-01
Corpus-based word frequencies are one of the most important predictors in language processing tasks. Frequencies based on conversational corpora (such as movie subtitles) are shown to better capture the variance in lexical decision tasks compared to traditional corpora. In this study, we show that frequencies computed from social media are currently the best frequency-based estimators of lexical decision reaction times (up to 3.6% increase in explained variance). The results are robust (observed for Twitter- and Facebook-based frequencies on American English and British English datasets) and are still substantial when we control for corpus size. © 2016 The Authors. Cognitive Science published by Wiley Periodicals, Inc. on behalf of Cognitive Science Society.
Educational Assessment Using Intelligent Systems. Research Report. ETS RR-08-68
ERIC Educational Resources Information Center
Shute, Valerie J.; Zapata-Rivera, Diego
2008-01-01
Recent advances in educational assessment, cognitive science, and artificial intelligence have made it possible to integrate valid assessment and instruction in the form of modern computer-based intelligent systems. These intelligent systems leverage assessment information that is gathered from various sources (e.g., summative and formative). This…
The Role of Working Memory in Metaphor Production and Comprehension
ERIC Educational Resources Information Center
Chiappe, Dan L.; Chiappe, Penny
2007-01-01
The following tested Kintsch's [Kintsch, W. (2000). "Metaphor comprehension: a computational theory." "Psychonomic Bulletin & Review," 7, 257-266 and Kintsch, W. (2001). "Predication." "Cognitive Science," 25, 173-202] Predication Model, which predicts that working memory capacity is an important factor in metaphor processing. In support of his…
Schemas in Problem Solving: An Integrated Model of Learning, Memory, and Instruction
1992-01-01
article: "Hybrid Computation in Cognitive Science: Neural Networks and Symbols" (J. A. Anderson, 1990). And, Marvin Minsky echoes the sentiment in his...distributed processing: A handbook of models, programs, and exercises. Cambridge, MA: The MIT Press. Minsky , M. (1991). Logical versus analogical or symbolic
Concepts as Semantic Pointers: A Framework and Computational Model
ERIC Educational Resources Information Center
Blouw, Peter; Solodkin, Eugene; Thagard, Paul; Eliasmith, Chris
2016-01-01
The reconciliation of theories of concepts based on prototypes, exemplars, and theory-like structures is a longstanding problem in cognitive science. In response to this problem, researchers have recently tended to adopt either hybrid theories that combine various kinds of representational structure, or eliminative theories that replace concepts…
Conference on the Neurobiology of Learning and Memory (2nd).
1986-05-30
Illinois The Rockefeller University 603 E. Daniel 1230 York Ave. Champaign, IL 61820 New York, NY 10021 Mr. Steven M. Guich Dr. Franz Hock Social Sciences...Psychology Edmonton, Alberta T6H 2B9 John Hopkins University Canada Baltimore, MD 21218 Mr. Steven Hampson Ms. Carol A. Hunt Information and Computer...Irvine, CA 92717 University of California Irvine, CA 92717 Dr. David LaBerge Cognitive Sciences Mr. Richard S. Lewis University of California Department
The simplicity principle in perception and cognition.
Feldman, Jacob
2016-09-01
The simplicity principle, traditionally referred to as Occam's razor, is the idea that simpler explanations of observations should be preferred to more complex ones. In recent decades the principle has been clarified via the incorporation of modern notions of computation and probability, allowing a more precise understanding of how exactly complexity minimization facilitates inference. The simplicity principle has found many applications in modern cognitive science, in contexts as diverse as perception, categorization, reasoning, and neuroscience. In all these areas, the common idea is that the mind seeks the simplest available interpretation of observations- or, more precisely, that it balances a bias toward simplicity with a somewhat opposed constraint to choose models consistent with perceptual or cognitive observations. This brief tutorial surveys some of the uses of the simplicity principle across cognitive science, emphasizing how complexity minimization in a number of forms has been incorporated into probabilistic models of inference. WIREs Cogn Sci 2016, 7:330-340. doi: 10.1002/wcs.1406 For further resources related to this article, please visit the WIREs website. © 2016 Wiley Periodicals, Inc.
Collaborative Visualization Project: shared-technology learning environments for science learning
NASA Astrophysics Data System (ADS)
Pea, Roy D.; Gomez, Louis M.
1993-01-01
Project-enhanced science learning (PESL) provides students with opportunities for `cognitive apprenticeships' in authentic scientific inquiry using computers for data-collection and analysis. Student teams work on projects with teacher guidance to develop and apply their understanding of science concepts and skills. We are applying advanced computing and communications technologies to augment and transform PESL at-a-distance (beyond the boundaries of the individual school), which is limited today to asynchronous, text-only networking and unsuitable for collaborative science learning involving shared access to multimedia resources such as data, graphs, tables, pictures, and audio-video communication. Our work creates user technology (a Collaborative Science Workbench providing PESL design support and shared synchronous document views, program, and data access; a Science Learning Resource Directory for easy access to resources including two-way video links to collaborators, mentors, museum exhibits, media-rich resources such as scientific visualization graphics), and refine enabling technologies (audiovisual and shared-data telephony, networking) for this PESL niche. We characterize participation scenarios for using these resources and we discuss national networked access to science education expertise.
NASA Astrophysics Data System (ADS)
Wesley, Beth Eddinger; Krockover, Gerald H.; Devito, Alfred
The purpose of this study was to determine the effects of computer-assisted instruction (CAI) versus a text mode of programmed instruction (PI), and the cognitive style of locus of control, on preservice elementary teachers' achievement of the integrated science process skills. Eighty-one preservice elementary teachers in six sections of a science methods class were classified as internally or externally controlled. The sections were randomly assigned to receive instruction in the integrated science process skills via a microcomputer or printed text. The study used a pretest-posttest control group design. Before assessing main and interaction effects, analysis of covariance was used to adjust posttest scores using the pretest scores. Statistical analysis revealed that main effects were not significant. Additionally, no interaction effects between treatments and loci of control were demonstrated. The results suggest that printed PI and tutorial CAI are equally effective modes of instruction for teaching internally and externally oriented preservice elementary teachers the integrated science process skills.
How Albot0 finds its way home: a novel approach to cognitive mapping using robots.
Yeap, Wai K
2011-10-01
Much of what we know about cognitive mapping comes from observing how biological agents behave in their physical environments, and several of these ideas were implemented on robots, imitating such a process. In this paper a novel approach to cognitive mapping is presented whereby robots are treated as a species of their own and their cognitive mapping is being investigated. Such robots are referred to as Albots. The design of the first Albot, Albot0 , is presented. Albot0 computes an imprecise map and employs a novel method to find its way home. Both the map and the return-home algorithm exhibited characteristics commonly found in biological agents. What we have learned from Albot0 's cognitive mapping are discussed. One major lesson is that the spatiality in a cognitive map affords us rich and useful information and this argues against recent suggestions that the notion of a cognitive map is not a useful one. Copyright © 2011 Cognitive Science Society, Inc.
Student leadership in small group science inquiry
NASA Astrophysics Data System (ADS)
Oliveira, Alandeom W.; Boz, Umit; Broadwell, George A.; Sadler, Troy D.
2014-09-01
Background: Science educators have sought to structure collaborative inquiry learning through the assignment of static group roles. This structural approach to student grouping oversimplifies the complexities of peer collaboration and overlooks the highly dynamic nature of group activity. Purpose: This study addresses this issue of oversimplification of group dynamics by examining the social leadership structures that emerge in small student groups during science inquiry. Sample: Two small student groups investigating the burning of a candle under a jar participated in this study. Design and method: We used a mixed-method research approach that combined computational discourse analysis (computational quantification of social aspects of small group discussions) with microethnography (qualitative, in-depth examination of group discussions). Results: While in one group social leadership was decentralized (i.e., students shared control over topics and tasks), the second group was dominated by a male student (centralized social leadership). Further, decentralized social leadership was found to be paralleled by higher levels of student cognitive engagement. Conclusions: It is argued that computational discourse analysis can provide science educators with a powerful means of developing pedagogical models of collaborative science learning that take into account the emergent nature of group structures and highly fluid nature of student collaboration.
On the necessity of U-shaped learning.
Carlucci, Lorenzo; Case, John
2013-01-01
A U-shaped curve in a cognitive-developmental trajectory refers to a three-step process: good performance followed by bad performance followed by good performance once again. U-shaped curves have been observed in a wide variety of cognitive-developmental and learning contexts. U-shaped learning seems to contradict the idea that learning is a monotonic, cumulative process and thus constitutes a challenge for competing theories of cognitive development and learning. U-shaped behavior in language learning (in particular in learning English past tense) has become a central topic in the Cognitive Science debate about learning models. Antagonist models (e.g., connectionism versus nativism) are often judged on their ability of modeling or accounting for U-shaped behavior. The prior literature is mostly occupied with explaining how U-shaped behavior occurs. Instead, we are interested in the necessity of this kind of apparently inefficient strategy. We present and discuss a body of results in the abstract mathematical setting of (extensions of) Gold-style computational learning theory addressing a mathematically precise version of the following question: Are there learning tasks that require U-shaped behavior? All notions considered are learning in the limit from positive data. We present results about the necessity of U-shaped learning in classical models of learning as well as in models with bounds on the memory of the learner. The pattern emerges that, for parameterized, cognitively relevant learning criteria, beyond very few initial parameter values, U-shapes are necessary for full learning power! We discuss the possible relevance of the above results for the Cognitive Science debate about learning models as well as directions for future research. Copyright © 2013 Cognitive Science Society, Inc.
Using Predictability for Lexical Segmentation.
Çöltekin, Çağrı
2017-09-01
This study investigates a strategy based on predictability of consecutive sub-lexical units in learning to segment a continuous speech stream into lexical units using computational modeling and simulations. Lexical segmentation is one of the early challenges during language acquisition, and it has been studied extensively through psycholinguistic experiments as well as computational methods. However, despite strong empirical evidence, the explicit use of predictability of basic sub-lexical units in models of segmentation is underexplored. This paper presents an incremental computational model of lexical segmentation for exploring the usefulness of predictability for lexical segmentation. We show that the predictability cue is a strong cue for segmentation. Contrary to earlier reports in the literature, the strategy yields state-of-the-art segmentation performance with an incremental computational model that uses only this particular cue in a cognitively plausible setting. The paper also reports an in-depth analysis of the model, investigating the conditions affecting the usefulness of the strategy. Copyright © 2016 Cognitive Science Society, Inc.
Sculpting Computational-Level Models.
Blokpoel, Mark
2017-06-27
In this commentary, I advocate for strict relations between Marr's levels of analysis. Under a strict relationship, each level is exactly implemented by the subordinate level. This yields two benefits. First, it brings consistency for multilevel explanations. Second, similar to how a sculptor chisels away superfluous marble, a modeler can chisel a computational-level model by applying constraints. By sculpting the model, one restricts the (potentially infinitely large) set of possible algorithmic- and implementational-level theories. Copyright © 2017 Cognitive Science Society, Inc.
Application of Cognitive Science Principles: Instructional Heuristics and Mechanisms for Use.
ERIC Educational Resources Information Center
Montague, William E.
Cognitive science is briefly reviewed, and its implications for instructional design are discussed. The application of cognitive science to instruction requires knowledge of cognitive science, the subject content taught, and the system in which the instruction is imbedded. The central concept of cognitive science is mental representation--the…
Strategy generalization across orientation tasks: testing a computational cognitive model.
Gunzelmann, Glenn
2008-07-08
Humans use their spatial information processing abilities flexibly to facilitate problem solving and decision making in a variety of tasks. This article explores the question of whether a general strategy can be adapted for performing two different spatial orientation tasks by testing the predictions of a computational cognitive model. Human performance was measured on an orientation task requiring participants to identify the location of a target either on a map (find-on-map) or within an egocentric view of a space (find-in-scene). A general strategy instantiated in a computational cognitive model of the find-on-map task, based on the results from Gunzelmann and Anderson (2006), was adapted to perform both tasks and used to generate performance predictions for a new study. The qualitative fit of the model to the human data supports the view that participants were able to tailor a general strategy to the requirements of particular spatial tasks. The quantitative differences between the predictions of the model and the performance of human participants in the new experiment expose individual differences in sample populations. The model provides a means of accounting for those differences and a framework for understanding how human spatial abilities are applied to naturalistic spatial tasks that involve reasoning with maps. 2008 Cognitive Science Society, Inc.
Recursion and the Competence/Performance Distinction in AGL Tasks
ERIC Educational Resources Information Center
Lobina, David J.
2011-01-01
The term "recursion" is used in at least four distinct theoretical senses within cognitive science. Some of these senses in turn relate to the different levels of analysis described by David Marr some 20 years ago; namely, the underlying competence capacity (the "computational" level), the performance operations used in real-time processing (the…
Studying Students' Attitudes on Using Examples of Game Source Code for Learning Programming
ERIC Educational Resources Information Center
Theodoraki, Aristea; Xinogalos, Stelios
2014-01-01
Games for learning are currently used in several disciplines for motivating students and enhancing their learning experience. This new approach of technology-enhanced learning has attracted researchers' and instructors' attention in the area of programming that is one of the most cognitively demanding fields in Computer Science. Several…
ERIC Educational Resources Information Center
Beatty, Ian D.
There is a growing consensus among educational researchers that traditional problem-based assessments are not effective tools for diagnosing a student's knowledge state and for guiding pedagogical intervention, and that new tools grounded in the results of cognitive science research are needed. The ConMap ("Conceptual Mapping") project, described…
Programs as Causal Models: Speculations on Mental Programs and Mental Representation
ERIC Educational Resources Information Center
Chater, Nick; Oaksford, Mike
2013-01-01
Judea Pearl has argued that counterfactuals and causality are central to intelligence, whether natural or artificial, and has helped create a rich mathematical and computational framework for formally analyzing causality. Here, we draw out connections between these notions and various current issues in cognitive science, including the nature of…
Mathematical Problem Solving: A Review of the Literature.
ERIC Educational Resources Information Center
Funkhouser, Charles
The major perspectives on problem solving of the twentieth century are reviewed--associationism, Gestalt psychology, and cognitive science. The results of the review on teaching problem solving and the uses of computers to teach problem solving are included. Four major issues related to the teaching of problem solving are discussed: (1)…
ERIC Educational Resources Information Center
Lee, Mark J. W.; Pradhan, Sunam; Dalgarno, Barney
2008-01-01
Modern information technology and computer science curricula employ a variety of graphical tools and development environments to facilitate student learning of introductory programming concepts and techniques. While the provision of interactive features and the use of visualization can enhance students' understanding and assist them in grasping…
Problem Solving Skills of Hispanic College Students.
ERIC Educational Resources Information Center
Gerace, William J.; Mestre, Jose P.
Minorities have for some time been underrepresented in the technical fields, such as engineering and computer science. This development is known to be caused by a variety of factors, but the primary purpose of this report is to help identify those factors that adversely affect the cognitive development of the technical bilingual student in terms…
ERIC Educational Resources Information Center
Hoffman, Daniel L.
2013-01-01
The purpose of the study is to better understand the role of physicality, interactivity, and interface effects in learning with digital content. Drawing on work in cognitive science, human-computer interaction, and multimedia learning, the study argues that interfaces that promote physical interaction can provide "conceptual leverage"…
Why Today's Computers Don't Learn the Way People Do.
ERIC Educational Resources Information Center
Clancey, W. J.
A major error in cognitive science has been to suppose that the meaning of a representation in the mind is known prior to its production. Representations are inherently perceptual--constructed by a perceptual process and given meaning by subsequent perception of them. The person perceiving the representation determines what it means. This premise…
A Study on the Learning Efficiency of Multimedia-Presented, Computer-Based Science Information
ERIC Educational Resources Information Center
Guan, Ying-Hua
2009-01-01
This study investigated the effects of multimedia presentations on the efficiency of learning scientific information (i.e. information on basic anatomy of human brains and their functions, the definition of cognitive psychology, and the structure of human memory). Experiment 1 investigated whether the modality effect could be observed when the…
Strategy Shifts Without Impasses: A Computational Model of the Sum-to- Min Transition.
1991-09-01
the larger addend to the left hand. Rather, it starts and Gallistel (1978) who found that very young chil- with whichever addend is presented first... Gallistel , C. R. (1978). The child’s the discovery of problem solving strategies. Cognitive understanding of number. Cambridge, MA: Harvard Science
Getting ahead: forward models and their place in cognitive architecture.
Pickering, Martin J; Clark, Andy
2014-09-01
The use of forward models (mechanisms that predict the future state of a system) is well established in cognitive and computational neuroscience. We compare and contrast two recent, but interestingly divergent, accounts of the place of forward models in the human cognitive architecture. On the Auxiliary Forward Model (AFM) account, forward models are special-purpose prediction mechanisms implemented by additional circuitry distinct from core mechanisms of perception and action. On the Integral Forward Model (IFM) account, forward models lie at the heart of all forms of perception and action. We compare these neighbouring but importantly different visions and consider their implications for the cognitive sciences. We end by asking what kinds of empirical research might offer evidence favouring one or the other of these approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Fox, P. A.; Diviacco, P.; Busato, A.
2016-12-01
Geo-scientific research collaboration commonly faces of complex systems where multiple skills and competences are needed at the same time. Efficacy of such collaboration among researchers then becomes of paramount importance. Multidisciplinary studies draw from domains that are far from each other. Researchers also need to understand: how to extract what data they need and eventually produce something that can be used by others. The management of information and knowledge in this perspective is non-trivial. Interoperability is frequently sought in computer-to-computer environements, so-as to overcome mismatches in vocabulary, data formats, coordinate reference system and so on. Successful researcher collaboration also relies on interoperability of the people! Smaller, synchronous and face-to-face settings for researchers are knownn to enhance people interoperability. However changing settings; either geographically; temporally; or with increasing the team size, diversity, and expertise requires people-computer-people-computer (...) interoperability. To date, knowledge representation framework have been proposed but not proven as necessary and sufficient to achieve multi-way interoperability. In this contribution, we address epistemology and sociology of science advocating for a fluid perspective where science is mostly a social construct, conditioned by cognitive issues; especially cognitive bias. Bias cannot be obliterated. On the contrary it must be carefully taken into consideration. Information-centric interfaces built from different perspectives and ways of thinking by actors with different point of views, approaches and aims, are proposed as a means for enhancing people interoperability in computer-based settings. The contribution will provide details on the approach of augmenting and interfacing to knowledge representation frameworks to the cognitive-conceptual frameworks for people that are needed to meet and exceed collaborative research goals in the 21st century. A web based collaborative portal has been developed that integrates both approaches and will be presented. Reports will be given on initial tests that have encouraging results.
2017-01-01
Statistical learning has been studied in a variety of different tasks, including word segmentation, object identification, category learning, artificial grammar learning and serial reaction time tasks (e.g. Saffran et al. 1996 Science 274, 1926–1928; Orban et al. 2008 Proceedings of the National Academy of Sciences 105, 2745–2750; Thiessen & Yee 2010 Child Development 81, 1287–1303; Saffran 2002 Journal of Memory and Language 47, 172–196; Misyak & Christiansen 2012 Language Learning 62, 302–331). The difference among these tasks raises questions about whether they all depend on the same kinds of underlying processes and computations, or whether they are tapping into different underlying mechanisms. Prior theoretical approaches to statistical learning have often tried to explain or model learning in a single task. However, in many cases these approaches appear inadequate to explain performance in multiple tasks. For example, explaining word segmentation via the computation of sequential statistics (such as transitional probability) provides little insight into the nature of sensitivity to regularities among simultaneously presented features. In this article, we will present a formal computational approach that we believe is a good candidate to provide a unifying framework to explore and explain learning in a wide variety of statistical learning tasks. This framework suggests that statistical learning arises from a set of processes that are inherent in memory systems, including activation, interference, integration of information and forgetting (e.g. Perruchet & Vinter 1998 Journal of Memory and Language 39, 246–263; Thiessen et al. 2013 Psychological Bulletin 139, 792–814). From this perspective, statistical learning does not involve explicit computation of statistics, but rather the extraction of elements of the input into memory traces, and subsequent integration across those memory traces that emphasize consistent information (Thiessen and Pavlik 2013 Cognitive Science 37, 310–343). This article is part of the themed issue ‘New frontiers for statistical learning in the cognitive sciences'. PMID:27872374
Thiessen, Erik D
2017-01-05
Statistical learning has been studied in a variety of different tasks, including word segmentation, object identification, category learning, artificial grammar learning and serial reaction time tasks (e.g. Saffran et al. 1996 Science 274: , 1926-1928; Orban et al. 2008 Proceedings of the National Academy of Sciences 105: , 2745-2750; Thiessen & Yee 2010 Child Development 81: , 1287-1303; Saffran 2002 Journal of Memory and Language 47: , 172-196; Misyak & Christiansen 2012 Language Learning 62: , 302-331). The difference among these tasks raises questions about whether they all depend on the same kinds of underlying processes and computations, or whether they are tapping into different underlying mechanisms. Prior theoretical approaches to statistical learning have often tried to explain or model learning in a single task. However, in many cases these approaches appear inadequate to explain performance in multiple tasks. For example, explaining word segmentation via the computation of sequential statistics (such as transitional probability) provides little insight into the nature of sensitivity to regularities among simultaneously presented features. In this article, we will present a formal computational approach that we believe is a good candidate to provide a unifying framework to explore and explain learning in a wide variety of statistical learning tasks. This framework suggests that statistical learning arises from a set of processes that are inherent in memory systems, including activation, interference, integration of information and forgetting (e.g. Perruchet & Vinter 1998 Journal of Memory and Language 39: , 246-263; Thiessen et al. 2013 Psychological Bulletin 139: , 792-814). From this perspective, statistical learning does not involve explicit computation of statistics, but rather the extraction of elements of the input into memory traces, and subsequent integration across those memory traces that emphasize consistent information (Thiessen and Pavlik 2013 Cognitive Science 37: , 310-343).This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Author(s).
How can philosophy be a true cognitive science discipline?
Bechtel, William
2010-07-01
Although philosophy has been only a minor contributor to cognitive science to date, this paper describes two projects in naturalistic philosophy of mind and one in naturalistic philosophy of science that have been pursued during the past 30 years and that can make theoretical and methodological contributions to cognitive science. First, stances on the mind-body problem (identity theory, functionalism, and heuristic identity theory) are relevant to cognitive science as it negotiates its relation to neuroscience and cognitive neuroscience. Second, analyses of mental representations address both their vehicles and their contents; new approaches to characterizing how representations have content are particularly relevant to understanding the relation of cognitive agents to their environments. Third, the recently formulated accounts of mechanistic explanation in philosophy of science both provide perspective on the explanatory project of cognitive science and may offer normative guidance to cognitive science (e.g., by providing perspective on how multiple disciplinary perspectives can be integrated in understanding a given mechanism). Copyright © 2010 Cognitive Science Society, Inc.
[Activities of Research Institute for Advanced Computer Science
NASA Technical Reports Server (NTRS)
Gross, Anthony R. (Technical Monitor); Leiner, Barry M.
2001-01-01
The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administrations missions. RIACS is located at the NASA Ames Research Center, Moffett Field, California. RIACS research focuses on the three cornerstones of IT research necessary to meet the future challenges of NASA missions: 1. Automated Reasoning for Autonomous Systems Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. 2. Human-Centered Computing Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities. 3. High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to analysis of large scientific datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply IT research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, visiting scientist programs and student summer programs, designed to encourage and facilitate collaboration between the university and NASA IT research communities.
Dougherty, Stephen
2010-01-01
This essay examines the unconscious as modeled by cognitive science and compares it to the psychoanalytic unconscious. In making this comparison, the author underscores the important but usually overlooked fact that computational psychology and psychoanalytic theory are both varieties of posthumanism. He argues that if posthumanism is to advance a vision for our future that is no longer fixated on a normative image of the human, then its own normative claims about the primacy of Darwinian functioning must be disrupted and undermined through a renewed emphasis on its Freudian heritage.
Action and language integration: from humans to cognitive robots.
Borghi, Anna M; Cangelosi, Angelo
2014-07-01
The topic is characterized by a highly interdisciplinary approach to the issue of action and language integration. Such an approach, combining computational models and cognitive robotics experiments with neuroscience, psychology, philosophy, and linguistic approaches, can be a powerful means that can help researchers disentangle ambiguous issues, provide better and clearer definitions, and formulate clearer predictions on the links between action and language. In the introduction we briefly describe the papers and discuss the challenges they pose to future research. We identify four important phenomena the papers address and discuss in light of empirical and computational evidence: (a) the role played not only by sensorimotor and emotional information but also of natural language in conceptual representation; (b) the contextual dependency and high flexibility of the interaction between action, concepts, and language; (c) the involvement of the mirror neuron system in action and language processing; (d) the way in which the integration between action and language can be addressed by developmental robotics and Human-Robot Interaction. Copyright © 2014 Cognitive Science Society, Inc.
Psychology in cognitive science: 1978-2038.
Gentner, Dedre
2010-07-01
This paper considers the past and future of Psychology within Cognitive Science. In the history section, I focus on three questions: (a) how has the position of Psychology evolved within Cognitive Science, relative to the other disciplines that make up Cognitive Science; (b) how have particular Cognitive Science areas within Psychology waxed or waned; and (c) what have we gained and lost. After discussing what's happened since the late 1970s, when the Society and the journal began, I speculate about where the field is going. Copyright © 2010 Cognitive Science Society, Inc.
Security implications and governance of cognitive neuroscience.
Kosal, Margaret E; Huang, Jonathan Y
2015-01-01
In recent years, significant efforts have been made toward elucidating the potential of the human brain. Spanning fields as disparate as psychology, biomedicine, computer science, mathematics, electrical engineering, and chemistry, research venturing into the growing domains of cognitive neuroscience and brain research has become fundamentally interdisciplinary. Among the most interesting and consequential applications to international security are the military and defense community's interests in the potential of cognitive neuroscience findings and technologies. In the United States, multiple governmental agencies are actively pursuing such endeavors, including the Department of Defense, which has invested over $3 billion in the last decade to conduct research on defense-related innovations. This study explores governance and security issues surrounding cognitive neuroscience research with regard to potential security-related applications and reports scientists' views on the role of researchers in these areas through a survey of over 200 active cognitive neuroscientists.
Few believe the world is flat: How embodiment is changing the scientific understanding of cognition.
Glenberg, Arthur M
2015-06-01
Science has changed many of our dearly held and commonsensical (but incorrect) beliefs. For example, few still believe the world is flat, and few still believe the sun orbits the earth. Few still believe humans are unrelated to the rest of the animal kingdom, and soon few will believe human thinking is computer-like. Instead, as with all animals, our thoughts are based on bodily experiences, and our thoughts and behaviors are controlled by bodily and neural systems of perception, action, and emotion interacting with the physical and social environments. We are embodied; nothing more. Embodied cognition is about cognition formatted in sensorimotor experience, and sensorimotor systems make those thoughts dynamic. Even processes that seem abstract, such as language comprehension and goal understanding, are embodied. Thus, embodied cognition is not limited to 1 type of thought or another: It is cognition. (c) 2015 APA, all rights reserved.
Cognitive knowledge, attitude toward science, and skill development in virtual science laboratories
NASA Astrophysics Data System (ADS)
Babaie, Mahya
The purpose of this quantitative, descriptive, single group, pretest posttest design study was to explore the influence of a Virtual Science Laboratory (VSL) on middle school students' cognitive knowledge, skill development, and attitudes toward science. This study involved 2 eighth grade Physical Science classrooms at a large urban charter middle school located in Southern California. The Buoyancy and Density Test (BDT), a computer generated test, assessed students' scientific knowledge in areas of Buoyancy and Density. The Attitude Toward Science Inventory (ATSI), a multidimensional survey assessment, measured students' attitudes toward science in the areas of value of science in society, motivation in science, enjoyment of science, self-concept regarding science, and anxiety toward science. A Virtual Laboratory Packet (VLP), generated by the researcher, captured students' mathematical and scientific skills. Data collection was conducted over a period of five days. BDT and ATSI assessments were administered twice: once before the Buoyancy and Density VSL to serve as baseline data (pre) and also after the VSL (post). The findings of this study revealed that students' cognitive knowledge and attitudes toward science were positively changed as expected, however, the results from paired sample t-tests found no statistical significance. Analyses indicated that VSLs were effective in supporting students' scientific knowledge and attitude toward science. The attitudes most changed were value of science in society and enjoyment of science with mean differences of 1.71 and 0.88, respectively. Researchers and educational practitioners are urged to further examine VSLs, covering a variety of topics, with more middle school students to assess their learning outcomes. Additionally, it is recommended that publishers in charge of designing the VSLs communicate with science instructors and research practitioners to further improve the design and analytic components of these virtual learning environments. The results of this study contribute to the existing body of knowledge in an effort to raise awareness about the inclusion of VSLs in secondary science classrooms. With the advancement of technological tools in secondary science classrooms, instructional practices should consider including VSLs especially if providing real science laboratories is a challenge.
The Demise of the Synapse As the Locus of Memory: A Looming Paradigm Shift?
Trettenbrein, Patrick C
2016-01-01
Synaptic plasticity is widely considered to be the neurobiological basis of learning and memory by neuroscientists and researchers in adjacent fields, though diverging opinions are increasingly being recognized. From the perspective of what we might call "classical cognitive science" it has always been understood that the mind/brain is to be considered a computational-representational system. Proponents of the information-processing approach to cognitive science have long been critical of connectionist or network approaches to (neuro-)cognitive architecture, pointing to the shortcomings of the associative psychology that underlies Hebbian learning as well as to the fact that synapses are practically unfit to implement symbols. Recent work on memory has been adding fuel to the fire and current findings in neuroscience now provide first tentative neurobiological evidence for the cognitive scientists' doubts about the synapse as the (sole) locus of memory in the brain. This paper briefly considers the history and appeal of synaptic plasticity as a memory mechanism, followed by a summary of the cognitive scientists' objections regarding these assertions. Next, a variety of tentative neuroscientific evidence that appears to substantiate questioning the idea of the synapse as the locus of memory is presented. On this basis, a novel way of thinking about the role of synaptic plasticity in learning and memory is proposed.
Pearce, Marcus T
2018-05-11
Music perception depends on internal psychological models derived through exposure to a musical culture. It is hypothesized that this musical enculturation depends on two cognitive processes: (1) statistical learning, in which listeners acquire internal cognitive models of statistical regularities present in the music to which they are exposed; and (2) probabilistic prediction based on these learned models that enables listeners to organize and process their mental representations of music. To corroborate these hypotheses, I review research that uses a computational model of probabilistic prediction based on statistical learning (the information dynamics of music (IDyOM) model) to simulate data from empirical studies of human listeners. The results show that a broad range of psychological processes involved in music perception-expectation, emotion, memory, similarity, segmentation, and meter-can be understood in terms of a single, underlying process of probabilistic prediction using learned statistical models. Furthermore, IDyOM simulations of listeners from different musical cultures demonstrate that statistical learning can plausibly predict causal effects of differential cultural exposure to musical styles, providing a quantitative model of cultural distance. Understanding the neural basis of musical enculturation will benefit from close coordination between empirical neuroimaging and computational modeling of underlying mechanisms, as outlined here. © 2018 The Authors. Annals of the New York Academy of Sciences published by Wiley Periodicals, Inc. on behalf of New York Academy of Sciences.
Cognitive science contributions to decision science.
Busemeyer, Jerome R
2015-02-01
This article briefly reviews the history and interplay between decision theory, behavioral decision-making research, and cognitive psychology. The review reveals the increasingly important impact that psychology and cognitive science have on decision science. One of the main contributions of cognitive science to decision science is the development of dynamic models that describe the cognitive processes that underlay the evolution of preferences during deliberation phase of making a decision. Copyright © 2014 Elsevier B.V. All rights reserved.
Mastering cognitive development theory in computer science education
NASA Astrophysics Data System (ADS)
Gluga, Richard; Kay, Judy; Lister, Raymond; Simon; Kleitman, Sabina
2013-03-01
To design an effective computer science curriculum, educators require a systematic method of classifying the difficulty level of learning activities and assessment tasks. This is important for curriculum design and implementation and for communication between educators. Different educators must be able to use the method consistently, so that classified activities and assessments are comparable across the subjects of a degree, and, ideally, comparable across institutions. One widespread approach to supporting this is to write learning objects in terms of Bloom's Taxonomy. This, or other such classifications, is likely to be more effective if educators can use them consistently, in the way experts would use them. To this end, we present the design and evaluation of our online interactive web-based tutorial system, which can be configured and used to offer training in different classification schemes. We report on results from three evaluations. First, 17 computer science educators complete a tutorial on using Bloom's Taxonomy to classify programming examination questions. Second, 20 computer science educators complete a Neo-Piagetian tutorial. Third evaluation was a comparison of inter-rater reliability scores of computer science educators classifying programming questions using Bloom's Taxonomy, before and after taking our tutorial. Based on the results from these evaluations, we discuss the effectiveness of our tutorial system design for teaching computer science educators how to systematically and consistently classify programming examination questions. We also discuss the suitability of Bloom's Taxonomy and Neo-Piagetian theory for achieving this goal. The Bloom's and Neo-Piagetian tutorials are made available as a community resource. The contributions of this paper are the following: the tutorial system for learning classification schemes for the purpose of coding the difficulty of computing learning materials; its evaluation; new insights into the consistency that computing educators can achieve using Bloom; and first insights into the use of Neo-Piagetian theory by a group of classifiers.
Sánchez-Pérez, Noelia; Castillo, Alejandro; López-López, José A.; Pina, Violeta; Puga, Jorge L.; Campoy, Guillermo; González-Salinas, Carmen; Fuentes, Luis J.
2018-01-01
Student academic achievement has been positively related to further development outcomes, such as the attainment of higher educational, employment, and socioeconomic aspirations. Among all the academic competences, mathematics has been identified as an essential skill in the field of international leadership as well as for those seeking positions in disciplines related to science, technology, and engineering. Given its positive consequences, studies have designed trainings to enhance children's mathematical skills. Additionally, the ability to regulate and control actions and cognitions, i.e., executive functions (EF), has been associated with school success, which has resulted in a strong effort to develop EF training programs to improve students' EF and academic achievement. The present study examined the efficacy of a school computer-based training composed of two components, namely, working memory and mathematics tasks. Among the advantages of using a computer-based training program is the ease with which it can be implemented in school settings and the ease by which the difficulty of the tasks can be adapted to fit the child's ability level. To test the effects of the training, children's cognitive skills (EF and IQ) and their school achievement (math and language grades and abilities) were evaluated. The results revealed a significant improvement in cognitive skills, such as non-verbal IQ and inhibition, and better school performance in math and reading among the children who participated in the training compared to those children who did not. Most of the improvements were related to training on WM tasks. These findings confirmed the efficacy of a computer-based training that combined WM and mathematics activities as part of the school routines based on the training's impact on children's academic competences and cognitive skills. PMID:29375442
Sánchez-Pérez, Noelia; Castillo, Alejandro; López-López, José A; Pina, Violeta; Puga, Jorge L; Campoy, Guillermo; González-Salinas, Carmen; Fuentes, Luis J
2017-01-01
Student academic achievement has been positively related to further development outcomes, such as the attainment of higher educational, employment, and socioeconomic aspirations. Among all the academic competences, mathematics has been identified as an essential skill in the field of international leadership as well as for those seeking positions in disciplines related to science, technology, and engineering. Given its positive consequences, studies have designed trainings to enhance children's mathematical skills. Additionally, the ability to regulate and control actions and cognitions, i.e., executive functions (EF), has been associated with school success, which has resulted in a strong effort to develop EF training programs to improve students' EF and academic achievement. The present study examined the efficacy of a school computer-based training composed of two components, namely, working memory and mathematics tasks. Among the advantages of using a computer-based training program is the ease with which it can be implemented in school settings and the ease by which the difficulty of the tasks can be adapted to fit the child's ability level. To test the effects of the training, children's cognitive skills (EF and IQ) and their school achievement (math and language grades and abilities) were evaluated. The results revealed a significant improvement in cognitive skills, such as non-verbal IQ and inhibition, and better school performance in math and reading among the children who participated in the training compared to those children who did not. Most of the improvements were related to training on WM tasks. These findings confirmed the efficacy of a computer-based training that combined WM and mathematics activities as part of the school routines based on the training's impact on children's academic competences and cognitive skills.
ERIC Educational Resources Information Center
Kartiko, Iwan; Kavakli, Manolya; Cheng, Ken
2010-01-01
As the technology in computer graphics advances, Animated-Virtual Actors (AVAs) in Virtual Reality (VR) applications become increasingly rich and complex. Cognitive Theory of Multimedia Learning (CTML) suggests that complex visual materials could hinder novice learners from attending to the lesson properly. On the other hand, previous studies have…
Plateaus, Dips, and Leaps: Where to Look for Inventions and Discoveries during Skilled Performance
ERIC Educational Resources Information Center
Gray, Wayne D.; Lindstedt, John K.
2017-01-01
The framework of "plateaus, dips, and leaps" shines light on periods when individuals may be inventing new methods of skilled performance. We begin with a review of the role "performance plateaus" have played in (a) experimental psychology, (b) human-computer interaction, and (c) cognitive science. We then reanalyze two classic…
ERIC Educational Resources Information Center
Wefer, Stephen H.; Anderson, O. Roger
2008-01-01
Bioinformatics, merging biological data with computer science, is increasingly incorporated into school curricula at all levels. This case study of 10 secondary school students highlights student individual differences (especially the way they processed information and integrated procedural and analytical thought) and summarizes a variety of…
Should the study of Homo sapiens be part of cognitive science?
Clark Barrett, H; Stich, Stephen; Laurence, Stephen
2012-07-01
Beller, Bender, and Medin argue that a reconciliation between anthropology and cognitive science seems unlikely. We disagree. In our view, Beller et al.'s view of the scope of what anthropology can offer cognitive science is too narrow. In focusing on anthropology's role in elucidating cultural particulars, they downplay the fact that anthropology can reveal both variation and universals in human cognition, and is in a unique position to do so relative to the other subfields of cognitive science. Indeed, without cross-cultural research, the universality of any aspect of human cognition cannot truly be established. Therefore, if the goal of cognitive science is to understand the cognitive capacities of our species as a whole, then it cannot do without anthropology. We briefly review a growing body of anthropological work aimed at answering questions about human cognition and offer suggestions for future work. Copyright © 2012 Cognitive Science Society, Inc.
Phillips, Steven; Wilson, William H.
2012-01-01
Human cognitive capacity includes recursively definable concepts, which are prevalent in domains involving lists, numbers, and languages. Cognitive science currently lacks a satisfactory explanation for the systematic nature of such capacities (i.e., why the capacity for some recursive cognitive abilities–e.g., finding the smallest number in a list–implies the capacity for certain others–finding the largest number, given knowledge of number order). The category-theoretic constructs of initial F-algebra, catamorphism, and their duals, final coalgebra and anamorphism provide a formal, systematic treatment of recursion in computer science. Here, we use this formalism to explain the systematicity of recursive cognitive capacities without ad hoc assumptions (i.e., to the same explanatory standard used in our account of systematicity for non-recursive capacities). The presence of an initial algebra/final coalgebra explains systematicity because all recursive cognitive capacities, in the domain of interest, factor through (are composed of) the same component process. Moreover, this factorization is unique, hence no further (ad hoc) assumptions are required to establish the intrinsic connection between members of a group of systematically-related capacities. This formulation also provides a new perspective on the relationship between recursive cognitive capacities. In particular, the link between number and language does not depend on recursion, as such, but on the underlying functor on which the group of recursive capacities is based. Thus, many species (and infants) can employ recursive processes without having a full-blown capacity for number and language. PMID:22514704
Martínez-Pernía, David; González-Castán, Óscar; Huepe, David
2017-02-01
The development of rehabilitation has traditionally focused on measurements of motor disorders and measurements of the improvements produced during the therapeutic process; however, physical rehabilitation sciences have not focused on understanding the philosophical and scientific principles in clinical intervention and how they are interrelated. The main aim of this paper is to explain the foundation stones of the disciplines of physical therapy, occupational therapy, and speech/language therapy in recovery from motor disorder. To reach our goals, the mechanistic view and how it is integrated into physical rehabilitation will first be explained. Next, a classification into mechanistic therapy based on an old version (automaton model) and a technological version (cyborg model) will be shown. Then, it will be shown how physical rehabilitation sciences found a new perspective in motor recovery, which is based on functionalism, during the cognitive revolution in the 1960s. Through this cognitive theory, physical rehabilitation incorporated into motor recovery of those therapeutic strategies that solicit the activation of the brain and/or symbolic processing; aspects that were not taken into account in mechanistic therapy. In addition, a classification into functionalist rehabilitation based on a computational therapy and a brain therapy will be shown. At the end of the article, the methodological principles in physical rehabilitation sciences will be explained. It will allow us to go deeper into the differences and similarities between therapeutic mechanism and therapeutic functionalism.
Modelling human problem solving with data from an online game.
Rach, Tim; Kirsch, Alexandra
2016-11-01
Since the beginning of cognitive science, researchers have tried to understand human strategies in order to develop efficient and adequate computational methods. In the domain of problem solving, the travelling salesperson problem has been used for the investigation and modelling of human solutions. We propose to extend this effort with an online game, in which instances of the travelling salesperson problem have to be solved in the context of a game experience. We report on our effort to design and run such a game, present the data contained in the resulting openly available data set and provide an outlook on the use of games in general for cognitive science research. In addition, we present three geometrical models mapping the starting point preferences in the problems presented in the game as the result of an evaluation of the data set.
Editorial: Cognitive Architectures, Model Comparison and AGI
NASA Astrophysics Data System (ADS)
Lebiere, Christian; Gonzalez, Cleotilde; Warwick, Walter
2010-12-01
Cognitive Science and Artificial Intelligence share compatible goals of understanding and possibly generating broadly intelligent behavior. In order to determine if progress is made, it is essential to be able to evaluate the behavior of complex computational models, especially those built on general cognitive architectures, and compare it to benchmarks of intelligent behavior such as human performance. Significant methodological challenges arise, however, when trying to extend approaches used to compare model and human performance from tightly controlled laboratory tasks to complex tasks involving more open-ended behavior. This paper describes a model comparison challenge built around a dynamic control task, the Dynamic Stocks and Flows. We present and discuss distinct approaches to evaluating performance and comparing models. Lessons drawn from this challenge are discussed in light of the challenge of using cognitive architectures to achieve Artificial General Intelligence.
[Cognitive neuroscience of aging. Contributions and challenges].
Díaz, Fernando; Pereiro, Arturo X
The cognitive neuroscience of aging is a young discipline that has emerged as a result of the combination of: A) the theoretical and explanatory frameworks proposed by the cognitive psychology perspective throughout the second half of the twentieth century; B) the designs and methodological procedures arising from experimental psychology and the need to test the hypotheses proposed from the cognitive psychology perspective; C) the contributions of the computer sciences to the explanation of brain functions; and D) the development and use of neuroimaging techniques that have enabled the recording of brain activity in humans while tasks that test some cognitive process or function are performed. An analysis on the impact of research conducted from this perspective over the last 3decades has been carried out, including its shortcomings, as well as the potential directions and usefulness that will advantageously continue to drive this discipline in its description and explanation of the process es of cerebral and cognitive aging. Copyright © 2017 SEGG. Publicado por Elsevier España, S.L.U. All rights reserved.
Embodied cognition for autonomous interactive robots.
Hoffman, Guy
2012-10-01
In the past, notions of embodiment have been applied to robotics mainly in the realm of very simple robots, and supporting low-level mechanisms such as dynamics and navigation. In contrast, most human-like, interactive, and socially adept robotic systems turn away from embodiment and use amodal, symbolic, and modular approaches to cognition and interaction. At the same time, recent research in Embodied Cognition (EC) is spanning an increasing number of complex cognitive processes, including language, nonverbal communication, learning, and social behavior. This article suggests adopting a modern EC approach for autonomous robots interacting with humans. In particular, we present three core principles from EC that may be applicable to such robots: (a) modal perceptual representation, (b) action/perception and action/cognition integration, and (c) a simulation-based model of top-down perceptual biasing. We describe a computational framework based on these principles, and its implementation on two physical robots. This could provide a new paradigm for embodied human-robot interaction based on recent psychological and neurological findings. Copyright © 2012 Cognitive Science Society, Inc.
NASA Astrophysics Data System (ADS)
Neves, Rui Gomes; Teodoro, Vítor Duarte
2012-09-01
A teaching approach aiming at an epistemologically balanced integration of computational modelling in science and mathematics education is presented. The approach is based on interactive engagement learning activities built around computational modelling experiments that span the range of different kinds of modelling from explorative to expressive modelling. The activities are designed to make a progressive introduction to scientific computation without requiring prior development of a working knowledge of programming, generate and foster the resolution of cognitive conflicts in the understanding of scientific and mathematical concepts and promote performative competency in the manipulation of different and complementary representations of mathematical models. The activities are supported by interactive PDF documents which explain the fundamental concepts, methods and reasoning processes using text, images and embedded movies, and include free space for multimedia enriched student modelling reports and teacher feedback. To illustrate, an example from physics implemented in the Modellus environment and tested in undergraduate university general physics and biophysics courses is discussed.
A Connectionist Approach to Embodied Conceptual Metaphor
Flusberg, Stephen J.; Thibodeau, Paul H.; Sternberg, Daniel A.; Glick, Jeremy J.
2010-01-01
A growing body of data has been gathered in support of the view that the mind is embodied and that cognition is grounded in sensory-motor processes. Some researchers have gone so far as to claim that this paradigm poses a serious challenge to central tenets of cognitive science, including the widely held view that the mind can be analyzed in terms of abstract computational principles. On the other hand, computational approaches to the study of mind have led to the development of specific models that help researchers understand complex cognitive processes at a level of detail that theories of embodied cognition (EC) have sometimes lacked. Here we make the case that connectionist architectures in particular can illuminate many surprising results from the EC literature. These models can learn the statistical structure in their environments, providing an ideal framework for understanding how simple sensory-motor mechanisms could give rise to higher-level cognitive behavior over the course of learning. Crucially, they form overlapping, distributed representations, which have exactly the properties required by many embodied accounts of cognition. We illustrate this idea by extending an existing connectionist model of semantic cognition in order to simulate findings from the embodied conceptual metaphor literature. Specifically, we explore how the abstract domain of time may be structured by concrete experience with space (including experience with culturally specific spatial and linguistic cues). We suggest that both EC researchers and connectionist modelers can benefit from an integrated approach to understanding these models and the empirical findings they seek to explain. PMID:21833256
NASA Astrophysics Data System (ADS)
Lamb, Richard L.
Serious Educational Games (SEGs) have been a topic of increased popularity within the educational realm since the early millennia. SEGs are generalized form of Serious Games to mean games for purposes other than entertainment but, that also specifically include training, educational purpose and pedagogy within their design. This rise in popularity (for SEGs) has occurred at a time when school systems have increased the type, number, and presentations of student achievement tests for decision-making purposes. These tests often task the form of end of course (year) tests and periodic benchmark testing. As the use of these tests, has increased policymakers have suggested their use as a measure for teacher accountability. The change in testing resulted from a push by school districts and policy makers at various component levels for a data-driven decision-making (D3M) approach. With the data-driven decision making approaches by school districts, there has been an increased focus on the measurement and assessment of student content knowledge with little focus on the contributing factors and cognitive attributes within learning that cross multiple-content areas. One-way to increase the focus on these aspects of learning (factors and attributes) that are additional to content learning is through assessments based in cognitive diagnostics. Cognitive diagnostics are a family of methodological approaches in which tasks tie to specific cognitive attributes for analytical purposes. This study explores data derived from computer data logging (n=158,000) in an observational design, using traditional statistical techniques such as clustering (exploratory and confirmatory), item response theory and through data mining techniques such as artificial neural network analysis. From these analyses, a model of student learning emerges illustrating student thinking and learning while engaged in SEG Design. This study seeks to use cognitive diagnostic type approaches to measure student learning while designing science task based SEGs. In addition, the study suggests that it may be possible to use SEGs to provide a means to administer cognitive diagnostic based assessments in real time. Results of this study suggest the confirmation of four families (factors) of traits illustrating a simple factor loading structure. Item response theory (IRT) results illustrate a 2-parameter logistic model (2PLM) fit allowing for parameterization using the IRT-True Score Method (chi2=1.70, df=1, p=0.19). Finally, fit statistics for the artificial neural network suggest the developed model adequately fits the current data set and provides a means to explore cognitive attributes and their effect on task outcomes. This study has developed a justification for combining and developing two distinct areas of research related to student learning. The first is the use of cognitive diagnostic approaches to assess student learning as it relates to the cognitive attributes used during science processing. The second area is an examination and modeling of the relationship between attributes as propagated in an artificial neural network. Results of the study provide for an ANN model of student cognition while designing science based SEGs (r 2=0.73, RMSE= 0.21) at a convergence of 1000 training iterations. The literature presented in this dissertation work integrates work from multiple field areas. Fields represented in this work range from science education, educational psychology, measurement, and computational psychology.
Grounded understanding of abstract concepts: The case of STEM learning.
Hayes, Justin C; Kraemer, David J M
2017-01-01
Characterizing the neural implementation of abstract conceptual representations has long been a contentious topic in cognitive science. At the heart of the debate is whether the "sensorimotor" machinery of the brain plays a central role in representing concepts, or whether the involvement of these perceptual and motor regions is merely peripheral or epiphenomenal. The domain of science, technology, engineering, and mathematics (STEM) learning provides an important proving ground for sensorimotor (or grounded) theories of cognition, as concepts in science and engineering courses are often taught through laboratory-based and other hands-on methodologies. In this review of the literature, we examine evidence suggesting that sensorimotor processes strengthen learning associated with the abstract concepts central to STEM pedagogy. After considering how contemporary theories have defined abstraction in the context of semantic knowledge, we propose our own explanation for how body-centered information, as computed in sensorimotor brain regions and visuomotor association cortex, can form a useful foundation upon which to build an understanding of abstract scientific concepts, such as mechanical force. Drawing from theories in cognitive neuroscience, we then explore models elucidating the neural mechanisms involved in grounding intangible concepts, including Hebbian learning, predictive coding, and neuronal recycling. Empirical data on STEM learning through hands-on instruction are considered in light of these neural models. We conclude the review by proposing three distinct ways in which the field of cognitive neuroscience can contribute to STEM learning by bolstering our understanding of how the brain instantiates abstract concepts in an embodied fashion.
Cognitive neuroscience: the troubled marriage of cognitive science and neuroscience.
Cooper, Richard P; Shallice, Tim
2010-07-01
We discuss the development of cognitive neuroscience in terms of the tension between the greater sophistication in cognitive concepts and methods of the cognitive sciences and the increasing power of more standard biological approaches to understanding brain structure and function. There have been major technological developments in brain imaging and advances in simulation, but there have also been shifts in emphasis, with topics such as thinking, consciousness, and social cognition becoming fashionable within the brain sciences. The discipline has great promise in terms of applications to mental health and education, provided it does not abandon the cognitive perspective and succumb to reductionism. Copyright © 2010 Cognitive Science Society, Inc.
Dupoux, Emmanuel
2018-04-01
Spectacular progress in the information processing sciences (machine learning, wearable sensors) promises to revolutionize the study of cognitive development. Here, we analyse the conditions under which 'reverse engineering' language development, i.e., building an effective system that mimics infant's achievements, can contribute to our scientific understanding of early language development. We argue that, on the computational side, it is important to move from toy problems to the full complexity of the learning situation, and take as input as faithful reconstructions of the sensory signals available to infants as possible. On the data side, accessible but privacy-preserving repositories of home data have to be setup. On the psycholinguistic side, specific tests have to be constructed to benchmark humans and machines at different linguistic levels. We discuss the feasibility of this approach and present an overview of current results. Copyright © 2017 Elsevier B.V. All rights reserved.
Homo heuristicus: why biased minds make better inferences.
Gigerenzer, Gerd; Brighton, Henry
2009-01-01
Heuristics are efficient cognitive processes that ignore information. In contrast to the widely held view that less processing reduces accuracy, the study of heuristics shows that less information, computation, and time can in fact improve accuracy. We review the major progress made so far: (a) the discovery of less-is-more effects; (b) the study of the ecological rationality of heuristics, which examines in which environments a given strategy succeeds or fails, and why; (c) an advancement from vague labels to computational models of heuristics; (d) the development of a systematic theory of heuristics that identifies their building blocks and the evolved capacities they exploit, and views the cognitive system as relying on an "adaptive toolbox;" and (e) the development of an empirical methodology that accounts for individual differences, conducts competitive tests, and has provided evidence for people's adaptive use of heuristics. Homo heuristicus has a biased mind and ignores part of the available information, yet a biased mind can handle uncertainty more efficiently and robustly than an unbiased mind relying on more resource-intensive and general-purpose processing strategies. Copyright © 2009 Cognitive Science Society, Inc.
Case Series in Cognitive Neuropsychology: Promise, Perils and Proper Perspective
Rapp, Brenda
2012-01-01
Schwartz & Dell (2010) advocated for a major role for case series investigations in cognitive neuropsychology. They defined the key features of this approach and presented a number of arguments and examples illustrating the benefits of case series studies and their contribution to computational cognitive neuropsychology. In the Special Issue on “Case Series in Cognitive Neuropsychology” there are six commentaries on Schwartz and Dell (2010) as well as a response to the six commentaries by Dell and Schwartz. In this paper, I provide a brief summary of the key points made in Schwartz and Dell (2010) and I review the promise and perils of case series design as revealed by the six commentaries. I conclude by placing the set of papers within a broader perspective, providing some clarification of the historical record on case series and single case approaches, raising some cautionary notes for case series studies and situating both case series and single case approaches within the larger context of theory development in the cognitive sciences. PMID:22746685
Moberget, Torgeir; Ivry, Richard B
2016-04-01
The past 25 years have seen the functional domain of the cerebellum extend beyond the realm of motor control, with considerable discussion of how this subcortical structure contributes to cognitive domains including attention, memory, and language. Drawing on evidence from neuroanatomy, physiology, neuropsychology, and computational work, sophisticated models have been developed to describe cerebellar function in sensorimotor control and learning. In contrast, mechanistic accounts of how the cerebellum contributes to cognition have remained elusive. Inspired by the homogeneous cerebellar microanatomy and a desire for parsimony, many researchers have sought to extend mechanistic ideas from motor control to cognition. One influential hypothesis centers on the idea that the cerebellum implements internal models, representations of the context-specific dynamics of an agent's interactions with the environment, enabling predictive control. We briefly review cerebellar anatomy and physiology, to review the internal model hypothesis as applied in the motor domain, before turning to extensions of these ideas in the linguistic domain, focusing on speech perception and semantic processing. While recent findings are consistent with this computational generalization, they also raise challenging questions regarding the nature of cerebellar learning, and may thus inspire revisions of our views on the role of the cerebellum in sensorimotor control. © 2016 New York Academy of Sciences.
2013-01-01
Objective. This study compared the relationship between computer experience and performance on computerized cognitive tests and a traditional paper-and-pencil cognitive test in a sample of older adults (N = 634). Method. Participants completed computer experience and computer attitudes questionnaires, three computerized cognitive tests (Useful Field of View (UFOV) Test, Road Sign Test, and Stroop task) and a paper-and-pencil cognitive measure (Trail Making Test). Multivariate analysis of covariance was used to examine differences in cognitive performance across the four measures between those with and without computer experience after adjusting for confounding variables. Results. Although computer experience had a significant main effect across all cognitive measures, the effect sizes were similar. After controlling for computer attitudes, the relationship between computer experience and UFOV was fully attenuated. Discussion. Findings suggest that computer experience is not uniquely related to performance on computerized cognitive measures compared with paper-and-pencil measures. Because the relationship between computer experience and UFOV was fully attenuated by computer attitudes, this may imply that motivational factors are more influential to UFOV performance than computer experience. Our findings support the hypothesis that computer use is related to cognitive performance, and this relationship is not stronger for computerized cognitive measures. Implications and directions for future research are provided. PMID:22929395
NASA Technical Reports Server (NTRS)
Shafto, Michael G.; Remington, Roger W.; Trimble, Jay W.
1994-01-01
A case study is presented to illustrate some of the problems of applying cognitive science to complex human-machine systems. Disregard for facts about human cognition often undermines the safety, reliability, and cost-effectiveness of complex systems. Yet single-point methods (for example, better user-interface design), whether rooted in computer science or in experimental psychology, fall far short of addressing systems-level problems in a timely way using realistic resources. A model-based methodology is proposed for organizing and prioritizing the cognitive engineering effort, focusing appropriate expertise on major problems first, then moving to more sophisticated refinements if time and resources permit. This case study is based on a collaborative effort between the Human Factors Division at NASA-Ames and the Spaceborne Imaging Radar SIR-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) Project at the Jet Propulsion Laboratory (JPL), California institute of Technology. The first SIR-C/X-SAR Shuttle mission flew successfully in April, 1994. A series of such missions is planned to provide radar data to study Earth's ecosystems, climatic and geological processes, hydrologic cycle, and ocean circulation. In addition to JPL and NASA personnel, the SIR-C/X-SAR operations team included Scientists and engineers from the German and Italian space agencies.
Twelve Issues for Cognitive Science.
ERIC Educational Resources Information Center
Norman, Donald A.
Cognitive science is a science of intelligence, of knowledge and its uses. Research is psychological theory follows four major themes: Perception, Attention, Memory, and Performance. Only when the range of cognitive mechanisms and functions is known, can possible theoretical approaches characterizing human thought and cognition be distinguished.…
Kelty-Stephen, Damian; Dixon, James A
2012-01-01
The neurobiological sciences have struggled to resolve the physical foundations for biological and cognitive phenomena with a suspicion that biological and cognitive systems, capable of exhibiting and contributing to structure within themselves and through their contexts, are fundamentally distinct or autonomous from purely physical systems. Complexity science offers new physics-based approaches to explaining biological and cognitive phenomena. In response to controversy over whether complexity science might seek to "explain away" biology and cognition as "just physics," we propose that complexity science serves as an application of recent advances in physics to phenomena in biology and cognition without reducing or undermining the integrity of the phenomena to be explained. We highlight that physics is, like the neurobiological sciences, an evolving field and that the threat of reduction is overstated. We propose that distinctions between biological and cognitive systems from physical systems are pretheoretical and thus optional. We review our own work applying insights from post-classical physics regarding turbulence and fractal fluctuations to the problems of developing cognitive structure. Far from hoping to reduce biology and cognition to "nothing but" physics, we present our view that complexity science offers new explanatory frameworks for considering physical foundations of biological and cognitive phenomena.
Behavioral and computational aspects of language and its acquisition
NASA Astrophysics Data System (ADS)
Edelman, Shimon; Waterfall, Heidi
2007-12-01
One of the greatest challenges facing the cognitive sciences is to explain what it means to know a language, and how the knowledge of language is acquired. The dominant approach to this challenge within linguistics has been to seek an efficient characterization of the wealth of documented structural properties of language in terms of a compact generative grammar-ideally, the minimal necessary set of innate, universal, exception-less, highly abstract rules that jointly generate all and only the observed phenomena and are common to all human languages. We review developmental, behavioral, and computational evidence that seems to favor an alternative view of language, according to which linguistic structures are generated by a large, open set of constructions of varying degrees of abstraction and complexity, which embody both form and meaning and are acquired through socially situated experience in a given language community, by probabilistic learning algorithms that resemble those at work in other cognitive modalities.
Social Cognition Unbound: Insights Into Anthropomorphism and Dehumanization.
Waytz, Adam; Epley, Nicholas; Cacioppo, John T
2010-02-01
People conceive of wrathful gods, fickle computers, and selfish genes, attributing human characteristics to a variety of supernatural, technological, and biological agents. This tendency to anthropomorphize nonhuman agents figures prominently in domains ranging from religion to marketing to computer science. Perceiving an agent to be humanlike has important implications for whether the agent is capable of social influence, accountable for its actions, and worthy of moral care and consideration. Three primary factors-elicited agent knowledge, sociality motivation, and effectance motivation-appear to account for a significant amount of variability in anthropomorphism. Identifying these factors that lead people to see nonhuman agents as humanlike also sheds light on the inverse process of dehumanization, whereby people treat human agents as animals or objects. Understanding anthropomorphism can contribute to a more expansive view of social cognition that applies social psychological theory to a wide variety of both human and nonhuman agents.
Social Cognition Unbound: Insights Into Anthropomorphism and Dehumanization
Waytz, Adam; Epley, Nicholas; Cacioppo, John T.
2014-01-01
People conceive of wrathful gods, fickle computers, and selfish genes, attributing human characteristics to a variety of supernatural, technological, and biological agents. This tendency to anthropomorphize nonhuman agents figures prominently in domains ranging from religion to marketing to computer science. Perceiving an agent to be humanlike has important implications for whether the agent is capable of social influence, accountable for its actions, and worthy of moral care and consideration. Three primary factors—elicited agent knowledge, sociality motivation, and effectance motivation—appear to account for a significant amount of variability in anthropomorphism. Identifying these factors that lead people to see nonhuman agents as humanlike also sheds light on the inverse process of dehumanization, whereby people treat human agents as animals or objects. Understanding anthropomorphism can contribute to a more expansive view of social cognition that applies social psychological theory to a wide variety of both human and nonhuman agents. PMID:24839358
Editor's Introduction and Review: Coordination and Context in Cognitive Science.
Kello, Christopher T
2018-01-01
The role of coordination in cognitive science has been on the rise in recent years, in terms of coordination among neurons, coordination among sensory and motor systems, and coordination among individuals. Research has shown that coordination patterns corresponding to cognitive activities depend on the various contexts in which the underlying interactions are situated. The present issue of Topics in Cognitive Science centers on studies of coordination that address the role of context in shaping or interpreting dynamical patterns of human behavior. This introductory article reviews some of the prior literature leading up to current and future research on coordination and context in cognitive science. Copyright © 2017 Cognitive Science Society, Inc.
Natural language processing and the Now-or-Never bottleneck.
Gómez-Rodríguez, Carlos
2016-01-01
Researchers, motivated by the need to improve the efficiency of natural language processing tools to handle web-scale data, have recently arrived at models that remarkably match the expected features of human language processing under the Now-or-Never bottleneck framework. This provides additional support for said framework and highlights the research potential in the interaction between applied computational linguistics and cognitive science.
ERIC Educational Resources Information Center
Luse, Andy; Rursch, Julie A.; Jacobson, Doug
2014-01-01
In the United States, the number of students entering into and completing degrees in science, technology, engineering, and mathematics (STEM) areas has declined significantly over the past decade. Although modest increases have been shown in enrollments in computer-related majors in the past 4 years, the prediction is that even in 3 to 4 years…
NASA Technical Reports Server (NTRS)
1997-01-01
Session MP4 includes short reports on: (1) Face Recognition in Microgravity: Is Gravity Direction Involved in the Inversion Effect?; (2) Motor Timing under Microgravity; (3) Perceived Self-Motion Assessed by Computer-Generated Animations: Complexity and Reliability; (4) Prolonged Weightlessness Reference Frames and Visual Symmetry Detection; (5) Mental Representation of Gravity During a Locomotor Task; and (6) Haptic Perception in Weightlessness: A Sense of Force or a Sense of Effort?
Active Learning with Statistical Models.
1995-01-01
Active Learning with Statistical Models ASC-9217041, NSF CDA-9309300 6. AUTHOR(S) David A. Cohn, Zoubin Ghahramani, and Michael I. Jordan 7. PERFORMING...TERMS 15. NUMBER OF PAGES Al, MIT, Artificial Intelligence, active learning , queries, locally weighted 6 regression, LOESS, mixtures of gaussians...COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES A.I. Memo No. 1522 January 9. 1995 C.B.C.L. Paper No. 110 Active Learning with
Cognitive Support During High-Consequence Episodes of Care in Cardiovascular Surgery.
Conboy, Heather M; Avrunin, George S; Clarke, Lori A; Osterweil, Leon J; Christov, Stefan C; Goldman, Julian M; Yule, Steven J; Zenati, Marco A
2017-03-01
Despite significant efforts to reduce preventable adverse events in medical processes, such events continue to occur at unacceptable rates. This paper describes a computer science approach that uses formal process modeling to provide situationally aware monitoring and management support to medical professionals performing complex processes. These process models represent both normative and non-normative situations, and are validated by rigorous automated techniques such as model checking and fault tree analysis, in addition to careful review by experts. Context-aware Smart Checklists are then generated from the models, providing cognitive support during high-consequence surgical episodes. The approach is illustrated with a case study in cardiovascular surgery.
Morimoto, Jun; Kawato, Mitsuo
2015-03-06
In the past two decades, brain science and robotics have made gigantic advances in their own fields, and their interactions have generated several interdisciplinary research fields. First, in the 'understanding the brain by creating the brain' approach, computational neuroscience models have been applied to many robotics problems. Second, such brain-motivated fields as cognitive robotics and developmental robotics have emerged as interdisciplinary areas among robotics, neuroscience and cognitive science with special emphasis on humanoid robots. Third, in brain-machine interface research, a brain and a robot are mutually connected within a closed loop. In this paper, we review the theoretical backgrounds of these three interdisciplinary fields and their recent progress. Then, we introduce recent efforts to reintegrate these research fields into a coherent perspective and propose a new direction that integrates brain science and robotics where the decoding of information from the brain, robot control based on the decoded information and multimodal feedback to the brain from the robot are carried out in real time and in a closed loop. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Creating the brain and interacting with the brain: an integrated approach to understanding the brain
Morimoto, Jun; Kawato, Mitsuo
2015-01-01
In the past two decades, brain science and robotics have made gigantic advances in their own fields, and their interactions have generated several interdisciplinary research fields. First, in the ‘understanding the brain by creating the brain’ approach, computational neuroscience models have been applied to many robotics problems. Second, such brain-motivated fields as cognitive robotics and developmental robotics have emerged as interdisciplinary areas among robotics, neuroscience and cognitive science with special emphasis on humanoid robots. Third, in brain–machine interface research, a brain and a robot are mutually connected within a closed loop. In this paper, we review the theoretical backgrounds of these three interdisciplinary fields and their recent progress. Then, we introduce recent efforts to reintegrate these research fields into a coherent perspective and propose a new direction that integrates brain science and robotics where the decoding of information from the brain, robot control based on the decoded information and multimodal feedback to the brain from the robot are carried out in real time and in a closed loop. PMID:25589568
Conditions for quantum interference in cognitive sciences.
Yukalov, Vyacheslav I; Sornette, Didier
2014-01-01
We present a general classification of the conditions under which cognitive science, concerned, e.g. with decision making, requires the use of quantum theoretical notions. The analysis is done in the frame of the mathematical approach based on the theory of quantum measurements. We stress that quantum effects in cognition can arise only when decisions are made under uncertainty. Conditions for the appearance of quantum interference in cognitive sciences and the conditions when interference cannot arise are formulated. Copyright © 2013 Cognitive Science Society, Inc.
AI and cognitive science: the past and next 30 years.
Forbus, Kenneth D
2010-07-01
Artificial Intelligence (AI) is a core area of Cognitive Science, yet today few AI researchers attend the Cognitive Science Society meetings. This essay examines why, how AI has changed over the last 30 years, and some emerging areas of potential interest where AI and the Society can go together in the next 30 years, if they choose. Copyright © 2010 Cognitive Science Society, Inc.
Learning the Hidden Structure of Speech.
1987-02-01
STRUCTURE OF SPEECH J. L. Elman and D. Zipser February 1987 ICS Report 8701 COGNITIVE SCIENCE ,a - ~QIt b’eez INSTITUTE FOR COGNITIVE SCIENCE...Zipser February 1987 ICS Report 8701 *0:-.:-! ,%. ., Jeffrey L. Elman David Zipser Department of Linguistics Institute for Cognitive Science...any purpose of the United States Government. Requests for reprints should be sent to the Institute for Cognitive Science, C-015; University of
Networks in cognitive science.
Baronchelli, Andrea; Ferrer-i-Cancho, Ramon; Pastor-Satorras, Romualdo; Chater, Nick; Christiansen, Morten H
2013-07-01
Networks of interconnected nodes have long played a key role in Cognitive Science, from artificial neural networks to spreading activation models of semantic memory. Recently, however, a new Network Science has been developed, providing insights into the emergence of global, system-scale properties in contexts as diverse as the Internet, metabolic reactions, and collaborations among scientists. Today, the inclusion of network theory into Cognitive Sciences, and the expansion of complex-systems science, promises to significantly change the way in which the organization and dynamics of cognitive and behavioral processes are understood. In this paper, we review recent contributions of network theory at different levels and domains within the Cognitive Sciences. Copyright © 2013 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Chung, Duk Ho; Park, Kyeong-Jin; Cho, Kyu Seong
2016-04-01
We investigated the cognitive frame of high school students and inservice high school science teachers about effective teaching method, and we also explored how they understood about the teaching methods suggested by the 2009 revised Science Curriculum. Data were collected from 275 high school science teachers and 275 high school students. We analyzed data in terms of the words and the cognitive frame using the Semantic Network Analysis. The results were as follows. First, the teachers perceived that an activity oriented class was the effective science class that helped improve students'' problem-solving abilities and their inquiry skills. The students had the cognitive frame that their teacher had to present relevant and enough teaching materials to students, and that they should also receive assistance from teachers in science class to better prepare for college entrance exam. Second, both students and teachers retained the cognitive frame about the efficient science class that was not reflected 2009 revised Science Curriculum exactly. Especially, neither groups connected the elements of ''convergence'' as well as ''integration'' embedded across science subject areas to their cognitive frame nor cognized the fact that many science learning contents were closed related to one another. Therefore, various professional development opportunities should be offered so that teachers succinctly comprehend the essential features and the intents of the 2009 revised Science Curriculum and thereby implement it in their science lessons effectively. Keywords : semantic network analysis, cognitive frame, teaching method, science lesson
Stieglitz, T
2007-01-01
Today applications of neural prostheses that successfully help patients to increase their activities of daily living and participate in social life again are quite simple implants that yield definite tissue response and are well recognized as foreign body. Latest developments in genetic engineering, nanotechnologies and materials sciences have paved the way to new scenarios towards highly complex systems to interface the human nervous system. Combinations of neural cells with microimplants promise stable biohybrid interfaces. Nanotechnology opens the door to macromolecular landscapes on implants that mimic the biologic topology and surface interaction of biologic cells. Computer sciences dream of technical cognitive systems that act and react due to knowledge-based conclusion mechanisms to a changing or adaptive environment. Different sciences start to interact and discuss the synergies when methods and paradigms from biology, computer sciences and engineering, neurosciences, psychology will be combined. They envision the era of "converging technologies" to completely change the understanding of science and postulate a new vision of humans. In this chapter, these research lines will be discussed on some examples as well as the societal implications and ethical questions that arise from these new opportunities.
Explaining how the mind works: on the relation between cognitive science and philosophy.
Trigg, Jonathan; Kalish, Michael
2011-04-01
In this paper, we argue that under certain prevalent interpretations of the nature and aims of cognitive science, theories of cognition generate a forced choice between a conception of cognition which depends on the possibility of a private language, and a conception of cognition which depends on mereological confusions. We argue, further, that this should not pose a fundamental problem for cognitive scientists since a plausible interpretation of the nature and aims of cognitive science is available that does not generate this forced choice. The crucial difference between these interpretations is that on the one hand the aim of theories of cognition is to tell us what thinking (etc.) is, and on the other it is to tell us what is causally necessary if an intelligent creature is to be able to think. Our argument draws heavily on a Wittgensteinian conception of philosophy in which no philosophical theory can explain what thinking, perceiving, remembering, etc. are, either. The positive, strictly therapeutic, purpose of a philosophy of cognitive science should be to show that, since the traditional problems which constitute the philosophy of mind are chimerical, there is nothing for philosophical theorizing in cognitive science to achieve. Copyright © 2011 Cognitive Science Society, Inc.
Evolving Non-Dominated Parameter Sets for Computational Models from Multiple Experiments
NASA Astrophysics Data System (ADS)
Lane, Peter C. R.; Gobet, Fernand
2013-03-01
Creating robust, reproducible and optimal computational models is a key challenge for theorists in many sciences. Psychology and cognitive science face particular challenges as large amounts of data are collected and many models are not amenable to analytical techniques for calculating parameter sets. Particular problems are to locate the full range of acceptable model parameters for a given dataset, and to confirm the consistency of model parameters across different datasets. Resolving these problems will provide a better understanding of the behaviour of computational models, and so support the development of general and robust models. In this article, we address these problems using evolutionary algorithms to develop parameters for computational models against multiple sets of experimental data; in particular, we propose the `speciated non-dominated sorting genetic algorithm' for evolving models in several theories. We discuss the problem of developing a model of categorisation using twenty-nine sets of data and models drawn from four different theories. We find that the evolutionary algorithms generate high quality models, adapted to provide a good fit to all available data.
Exploring Cognition Using Software Defined Radios for NASA Missions
NASA Technical Reports Server (NTRS)
Mortensen, Dale J.; Reinhart, Richard C.
2016-01-01
NASA missions typically operate using a communication infrastructure that requires significant schedule planning with limited flexibility when the needs of the mission change. Parameters such as modulation, coding scheme, frequency, and data rate are fixed for the life of the mission. This is due to antiquated hardware and software for both the space and ground assets and a very complex set of mission profiles. Automated techniques in place by commercial telecommunication companies are being explored by NASA to determine their usability by NASA to reduce cost and increase science return. Adding cognition the ability to learn from past decisions and adjust behavior is also being investigated. Software Defined Radios are an ideal way to implement cognitive concepts. Cognition can be considered in many different aspects of the communication system. Radio functions, such as frequency, modulation, data rate, coding and filters can be adjusted based on measurements of signal degradation. Data delivery mechanisms and route changes based on past successes and failures can be made to more efficiently deliver the data to the end user. Automated antenna pointing can be added to improve gain, coverage, or adjust the target. Scheduling improvements and automation to reduce the dependence on humans provide more flexible capabilities. The Cognitive Communications project, funded by the Space Communication and Navigation Program, is exploring these concepts and using the SCaN Testbed on board the International Space Station to implement them as they evolve. The SCaN Testbed contains three Software Defined Radios and a flight computer. These four computing platforms, along with a tracking antenna system and the supporting ground infrastructure, will be used to implement various concepts in a system similar to those used by missions. Multiple universities and SBIR companies are supporting this investigation. This paper will describe the cognitive system ideas under consideration and the plan for implementing them on platforms, including the SCaN Testbed. Discussions in the paper will include how these concepts might be used to reduce cost and improve the science return for NASA missions.
Cellular intelligence: Microphenomenology and the realities of being.
Ford, Brian J
2017-12-01
Traditions of Eastern thought conceptualised life in a holistic sense, emphasising the processes of maintaining health and conquering sickness as manifestations of an essentially spiritual principle that was of overriding importance in the conduct of living. Western science, which drove the overriding and partial eclipse of Eastern traditions, became founded on a reductionist quest for ultimate realities which, in the modern scientific world, has embraced the notion that every living process can be successfully modelled by a digital computer system. It is argued here that the essential processes of cognition, response and decision-making inherent in living cells transcend conventional modelling, and microscopic studies of organisms like the shell-building amoebae and the rhodophyte alga Antithamnion reveal a level of cellular intelligence that is unrecognized by science and is not amenable to computer analysis. Copyright © 2017. Published by Elsevier Ltd.
On agent-based modeling and computational social science.
Conte, Rosaria; Paolucci, Mario
2014-01-01
In the first part of the paper, the field of agent-based modeling (ABM) is discussed focusing on the role of generative theories, aiming at explaining phenomena by growing them. After a brief analysis of the major strengths of the field some crucial weaknesses are analyzed. In particular, the generative power of ABM is found to have been underexploited, as the pressure for simple recipes has prevailed and shadowed the application of rich cognitive models. In the second part of the paper, the renewal of interest for Computational Social Science (CSS) is focused upon, and several of its variants, such as deductive, generative, and complex CSS, are identified and described. In the concluding remarks, an interdisciplinary variant, which takes after ABM, reconciling it with the quantitative one, is proposed as a fundamental requirement for a new program of the CSS.
On agent-based modeling and computational social science
Conte, Rosaria; Paolucci, Mario
2014-01-01
In the first part of the paper, the field of agent-based modeling (ABM) is discussed focusing on the role of generative theories, aiming at explaining phenomena by growing them. After a brief analysis of the major strengths of the field some crucial weaknesses are analyzed. In particular, the generative power of ABM is found to have been underexploited, as the pressure for simple recipes has prevailed and shadowed the application of rich cognitive models. In the second part of the paper, the renewal of interest for Computational Social Science (CSS) is focused upon, and several of its variants, such as deductive, generative, and complex CSS, are identified and described. In the concluding remarks, an interdisciplinary variant, which takes after ABM, reconciling it with the quantitative one, is proposed as a fundamental requirement for a new program of the CSS. PMID:25071642
Processing Conversational Implicatures: Alternatives and Counterfactual Reasoning.
van Tiel, Bob; Schaeken, Walter
2017-05-01
In a series of experiments, Bott and Noveck (2004) found that the computation of scalar inferences, a variety of conversational implicature, caused a delay in response times. In order to determine what aspect of the inferential process that underlies scalar inferences caused this delay, we extended their paradigm to three other kinds of inferences: free choice inferences, conditional perfection, and exhaustivity in "it"-clefts. In contrast to scalar inferences, the computation of these three kinds of inferences facilitated response times. Following a suggestion made by Chemla and Bott (2014), we propose that the time it takes to compute a conversational implicature depends on the structural characteristics of the required alternatives. Copyright © 2016 Cognitive Science Society, Inc.
Gerjets, Peter; Walter, Carina; Rosenstiel, Wolfgang; Bogdan, Martin; Zander, Thorsten O.
2014-01-01
According to Cognitive Load Theory (CLT), one of the crucial factors for successful learning is the type and amount of working-memory load (WML) learners experience while studying instructional materials. Optimal learning conditions are characterized by providing challenges for learners without inducing cognitive over- or underload. Thus, presenting instruction in a way that WML is constantly held within an optimal range with regard to learners' working-memory capacity might be a good method to provide these optimal conditions. The current paper elaborates how digital learning environments, which achieve this goal can be developed by combining approaches from Cognitive Psychology, Neuroscience, and Computer Science. One of the biggest obstacles that needs to be overcome is the lack of an unobtrusive method of continuously assessing learners' WML in real-time. We propose to solve this problem by applying passive Brain-Computer Interface (BCI) approaches to realistic learning scenarios in digital environments. In this paper we discuss the methodological and theoretical prospects and pitfalls of this approach based on results from the literature and from our own research. We present a strategy on how several inherent challenges of applying BCIs to WML and learning can be met by refining the psychological constructs behind WML, by exploring their neural signatures, by using these insights for sophisticated task designs, and by optimizing algorithms for analyzing electroencephalography (EEG) data. Based on this strategy we applied machine-learning algorithms for cross-task classifications of different levels of WML to tasks that involve studying realistic instructional materials. We obtained very promising results that yield several recommendations for future work. PMID:25538544
Cognitive and Neural Sciences Division 1991 Programs
1991-08-01
FUNDING NUMBERS Cognitive and Neural Sciences Division 1991 Programs PE 61153N 6. AUTHOR(S) Edited by Willard S. Vaughan 7. PERFORMING ORGANIZATION...NAME(S) AND ADDRESS(ES) 8. PERFORMING ORGANIZATION REPORT NUMBER Office of Naval Research 0CNR !1491-19 Cognitive and Neural Sciences Division Code 1142...NOTES iN This is a compilation of abstracts representing R&D sponsored by the ONR Cognitive and Neural Sciences Division. 12a. DISTRIBUTION
A Future Accelerated Cognitive Distributed Hybrid Testbed for Big Data Science Analytics
NASA Astrophysics Data System (ADS)
Halem, M.; Prathapan, S.; Golpayegani, N.; Huang, Y.; Blattner, T.; Dorband, J. E.
2016-12-01
As increased sensor spectral data volumes from current and future Earth Observing satellites are assimilated into high-resolution climate models, intensive cognitive machine learning technologies are needed to data mine, extract and intercompare model outputs. It is clear today that the next generation of computers and storage, beyond petascale cluster architectures, will be data centric. They will manage data movement and process data in place. Future cluster nodes have been announced that integrate multiple CPUs with high-speed links to GPUs and MICS on their backplanes with massive non-volatile RAM and access to active flash RAM disk storage. Active Ethernet connected key value store disk storage drives with 10Ge or higher are now available through the Kinetic Open Storage Alliance. At the UMBC Center for Hybrid Multicore Productivity Research, a future state-of-the-art Accelerated Cognitive Computer System (ACCS) for Big Data science is being integrated into the current IBM iDataplex computational system `bluewave'. Based on the next gen IBM 200 PF Sierra processor, an interim two node IBM Power S822 testbed is being integrated with dual Power 8 processors with 10 cores, 1TB Ram, a PCIe to a K80 GPU and an FPGA Coherent Accelerated Processor Interface card to 20TB Flash Ram. This system is to be updated to the Power 8+, an NVlink 1.0 with the Pascal GPU late in 2016. Moreover, the Seagate 96TB Kinetic Disk system with 24 Ethernet connected active disks is integrated into the ACCS storage system. A Lightweight Virtual File System developed at the NASA GSFC is installed on bluewave. Since remote access to publicly available quantum annealing computers is available at several govt labs, the ACCS will offer an in-line Restricted Boltzmann Machine optimization capability to the D-Wave 2X quantum annealing processor over the campus high speed 100 Gb network to Internet 2 for large files. As an evaluation test of the cognitive functionality of the architecture, the following studies utilizing all the system components will be presented; (i) a near real time climate change study generating CO2 fluxes and (ii) a deep dive capability into an 8000 x8000 pixel image pyramid display and (iii) Large dense and sparse eigenvalue decomposition.
The computationalist reformulation of the mind-body problem.
Marchal, Bruno
2013-09-01
Computationalism, or digital mechanism, or simply mechanism, is a hypothesis in the cognitive science according to which we can be emulated by a computer without changing our private subjective feeling. We provide a weaker form of that hypothesis, weaker than the one commonly referred to in the (vast) literature and show how to recast the mind-body problem in that setting. We show that such a mechanist hypothesis does not solve the mind-body problem per se, but does help to reduce partially the mind-body problem into another problem which admits a formulation in pure arithmetic. We will explain that once we adopt the computationalist hypothesis, which is a form of mechanist assumption, we have to derive from it how our belief in the physical laws can emerge from *only* arithmetic and classical computer science. In that sense we reduce the mind-body problem to a body problem appearance in computer science, or in arithmetic. The general shape of the possible solution of that subproblem, if it exists, is shown to be closer to "Platonist or neoplatonist theology" than to the "Aristotelian theology". In Plato's theology, the physical or observable reality is only the shadow of a vaster hidden nonphysical and nonobservable, perhaps mathematical, reality. The main point is that the derivation is constructive, and it provides the technical means to derive physics from arithmetic, and this will make the computationalist hypothesis empirically testable, and thus scientific in the Popperian analysis of science. In case computationalism is wrong, the derivation leads to a procedure for measuring "our local degree of noncomputationalism". Copyright © 2013 Elsevier Ltd. All rights reserved.
From computers to cultivation: reconceptualizing evolutionary psychology.
Barrett, Louise; Pollet, Thomas V; Stulp, Gert
2014-01-01
Does evolutionary theorizing have a role in psychology? This is a more contentious issue than one might imagine, given that, as evolved creatures, the answer must surely be yes. The contested nature of evolutionary psychology lies not in our status as evolved beings, but in the extent to which evolutionary ideas add value to studies of human behavior, and the rigor with which these ideas are tested. This, in turn, is linked to the framework in which particular evolutionary ideas are situated. While the framing of the current research topic places the brain-as-computer metaphor in opposition to evolutionary psychology, the most prominent school of thought in this field (born out of cognitive psychology, and often known as the Santa Barbara school) is entirely wedded to the computational theory of mind as an explanatory framework. Its unique aspect is to argue that the mind consists of a large number of functionally specialized (i.e., domain-specific) computational mechanisms, or modules (the massive modularity hypothesis). Far from offering an alternative to, or an improvement on, the current perspective, we argue that evolutionary psychology is a mainstream computational theory, and that its arguments for domain-specificity often rest on shaky premises. We then go on to suggest that the various forms of e-cognition (i.e., embodied, embedded, enactive) represent a true alternative to standard computational approaches, with an emphasis on "cognitive integration" or the "extended mind hypothesis" in particular. We feel this offers the most promise for human psychology because it incorporates the social and historical processes that are crucial to human "mind-making" within an evolutionarily informed framework. In addition to linking to other research areas in psychology, this approach is more likely to form productive links to other disciplines within the social sciences, not least by encouraging a healthy pluralism in approach.
Big Computing in Astronomy: Perspectives and Challenges
NASA Astrophysics Data System (ADS)
Pankratius, Victor
2014-06-01
Hardware progress in recent years has led to astronomical instruments gathering large volumes of data. In radio astronomy for instance, the current generation of antenna arrays produces data at Tbits per second, and forthcoming instruments will expand these rates much further. As instruments are increasingly becoming software-based, astronomers will get more exposed to computer science. This talk therefore outlines key challenges that arise at the intersection of computer science and astronomy and presents perspectives on how both communities can collaborate to overcome these challenges.Major problems are emerging due to increases in data rates that are much larger than in storage and transmission capacity, as well as humans being cognitively overwhelmed when attempting to opportunistically scan through Big Data. As a consequence, the generation of scientific insight will become more dependent on automation and algorithmic instrument control. Intelligent data reduction will have to be considered across the entire acquisition pipeline. In this context, the presentation will outline the enabling role of machine learning and parallel computing.BioVictor Pankratius is a computer scientist who joined MIT Haystack Observatory following his passion for astronomy. He is currently leading efforts to advance astronomy through cutting-edge computer science and parallel computing. Victor is also involved in projects such as ALMA Phasing to enhance the ALMA Observatory with Very-Long Baseline Interferometry capabilities, the Event Horizon Telescope, as well as in the Radio Array of Portable Interferometric Detectors (RAPID) to create an analysis environment using parallel computing in the cloud. He has an extensive track record of research in parallel multicore systems and software engineering, with contributions to auto-tuning, debugging, and empirical experiments studying programmers. Victor has worked with major industry partners such as Intel, Sun Labs, and Oracle. He holds a distinguished doctorate and a Habilitation degree in Computer Science from the University of Karlsruhe. Contact him at pankrat@mit.edu, victorpankratius.com, or Twitter @vpankratius.
ERIC Educational Resources Information Center
Novak, John Anthony
This study investigated the relationship among personality types, cognitive preference orientation, science achievement, intelligence, attitudes toward science and scientists, sex, and geographic area of eighth-grade science students using the following four instruments: (1) Myers-Briggs Type Indication (MBTI); (2) Cognitive Preference Examination…
Emotion-affected decision making in human simulation.
Zhao, Y; Kang, J; Wright, D K
2006-01-01
Human modelling is an interdisciplinary research field. The topic, emotion-affected decision making, was originally a cognitive psychology issue, but is now recognized as an important research direction for both computer science and biomedical modelling. The main aim of this paper is to attempt to bridge the gap between psychology and bioengineering in emotion-affected decision making. The work is based on Ortony's theory of emotions and bounded rationality theory, and attempts to connect the emotion process with decision making. A computational emotion model is proposed, and the initial framework of this model in virtual human simulation within the platform of Virtools is presented.
Campbell, Sarah
2015-01-01
Mark Sagar is changing the way we look at computers by giving them faces?disconcertingly realistic human faces. Sagar first gained widespread recognition for his pioneering work in rendering faces for Hollywood movies, including Avatar and King Kong. With a Ph.D. degree in bioengineering and two Academy Awards under his belt, Sagar now directs a research lab at the University of Auckland, New Zealand, a combinatorial hub where artificial intelligence (AI), neuroscience, computer science, philosophy, and cognitive psychology intersect in creating interactive, intelligent technologies.
Intention, emotion, and action: a neural theory based on semantic pointers.
Schröder, Tobias; Stewart, Terrence C; Thagard, Paul
2014-06-01
We propose a unified theory of intentions as neural processes that integrate representations of states of affairs, actions, and emotional evaluation. We show how this theory provides answers to philosophical questions about the concept of intention, psychological questions about human behavior, computational questions about the relations between belief and action, and neuroscientific questions about how the brain produces actions. Our theory of intention ties together biologically plausible mechanisms for belief, planning, and motor control. The computational feasibility of these mechanisms is shown by a model that simulates psychologically important cases of intention. © 2013 Cognitive Science Society, Inc.
ERIC Educational Resources Information Center
Pinnick, Cassandra L.
2008-01-01
This paper examines the relation between situated cognition theory in science education, and feminist standpoint theory in philosophy of science. It shows that situated cognition is an idea borrowed from a long since discredited philosophy of science. It argues that feminist standpoint theory ought not be indulged as it is a failed challenge to…
Autonomous Driver Based on an Intelligent System of Decision-Making.
Czubenko, Michał; Kowalczuk, Zdzisław; Ordys, Andrew
The paper presents and discusses a system ( xDriver ) which uses an Intelligent System of Decision-making (ISD) for the task of car driving. The principal subject is the implementation, simulation and testing of the ISD system described earlier in our publications (Kowalczuk and Czubenko in artificial intelligence and soft computing lecture notes in computer science, lecture notes in artificial intelligence, Springer, Berlin, 2010, 2010, In Int J Appl Math Comput Sci 21(4):621-635, 2011, In Pomiary Autom Robot 2(17):60-5, 2013) for the task of autonomous driving. The design of the whole ISD system is a result of a thorough modelling of human psychology based on an extensive literature study. Concepts somehow similar to the ISD system can be found in the literature (Muhlestein in Cognit Comput 5(1):99-105, 2012; Wiggins in Cognit Comput 4(3):306-319, 2012), but there are no reports of a system which would model the human psychology for the purpose of autonomously driving a car. The paper describes assumptions for simulation, the set of needs and reactions (characterizing the ISD system), the road model and the vehicle model, as well as presents some results of simulation. It proves that the xDriver system may behave on the road as a very inexperienced driver.
Science knowledge and cognitive strategy use among culturally and linguistically diverse students
NASA Astrophysics Data System (ADS)
Lee, Okhee; Fradd, Sandra H.; Sutman, Frank X.
Science performance is determined, to a large extent, by what students already know about science (i.e., science knowledge) and what techniques or methods students use in performing science tasks (i.e., cognitive strategies). This study describes and compares science knowledge, science vocabulary, and cognitive strategy use among four diverse groups of elementary students: (a) monolingual English Caucasian, (b) African-American, (c) bilingual Spanish, and (d) bilingual Haitian Creole. To facilitate science performance in culturally and linguistically congruent settings, the study included student dyads and teachers of the same language, culture, and gender. Science performance was observed using three science tasks: weather phenomena, simple machines, and buoyancy. Data analysis involved a range of qualitative methods focusing on major themes and patterns, and quantitative methods using coding systems to summarize frequencies and total scores. The findings reveal distinct patterns of science knowledge, science vocabulary, and cognitive strategy use among the four language and culture groups. The findings also indicate relationships among science knowledge, science vocabulary, and cognitive strategy use. These findings raise important issues about science instruction for culturally and linguistically diverse groups of students.Received: 3 January 1995;
Computational rationality: linking mechanism and behavior through bounded utility maximization.
Lewis, Richard L; Howes, Andrew; Singh, Satinder
2014-04-01
We propose a framework for including information-processing bounds in rational analyses. It is an application of bounded optimality (Russell & Subramanian, 1995) to the challenges of developing theories of mechanism and behavior. The framework is based on the idea that behaviors are generated by cognitive mechanisms that are adapted to the structure of not only the environment but also the mind and brain itself. We call the framework computational rationality to emphasize the incorporation of computational mechanism into the definition of rational action. Theories are specified as optimal program problems, defined by an adaptation environment, a bounded machine, and a utility function. Such theories yield different classes of explanation, depending on the extent to which they emphasize adaptation to bounds, and adaptation to some ecology that differs from the immediate local environment. We illustrate this variation with examples from three domains: visual attention in a linguistic task, manual response ordering, and reasoning. We explore the relation of this framework to existing "levels" approaches to explanation, and to other optimality-based modeling approaches. Copyright © 2014 Cognitive Science Society, Inc.
Cognitive training in Parkinson disease: cognition-specific vs nonspecific computer training.
Zimmermann, Ronan; Gschwandtner, Ute; Benz, Nina; Hatz, Florian; Schindler, Christian; Taub, Ethan; Fuhr, Peter
2014-04-08
In this study, we compared a cognition-specific computer-based cognitive training program with a motion-controlled computer sports game that is not cognition-specific for their ability to enhance cognitive performance in various cognitive domains in patients with Parkinson disease (PD). Patients with PD were trained with either a computer program designed to enhance cognition (CogniPlus, 19 patients) or a computer sports game with motion-capturing controllers (Nintendo Wii, 20 patients). The effect of training in 5 cognitive domains was measured by neuropsychological testing at baseline and after training. Group differences over all variables were assessed with multivariate analysis of variance, and group differences in single variables were assessed with 95% confidence intervals of mean difference. The groups were similar regarding age, sex, and educational level. Patients with PD who were trained with Wii for 4 weeks performed better in attention (95% confidence interval: -1.49 to -0.11) than patients trained with CogniPlus. In our study, patients with PD derived at least the same degree of cognitive benefit from non-cognition-specific training involving movement as from cognition-specific computerized training. For patients with PD, game consoles may be a less expensive and more entertaining alternative to computer programs specifically designed for cognitive training. This study provides Class III evidence that, in patients with PD, cognition-specific computer-based training is not superior to a motion-controlled computer game in improving cognitive performance.
Georgetown Institute for Cognitive and Computational Sciences
2000-03-01
in neuronal apoptosis. Cerebellar granules cells (CGCs) were co-transfected with a green fluorescent protein reporter and one of several hammerhead ... ribozymes constructed to cleave caspase-3 RNA. Use of such ribozymes is highly selective. In separate experiments we co-transfected with a gene that...expressing a ribozyme against rat caspase-3. Apoptosis was assessed after 24, 36, or 48 h of serum/K+ deprivation. In negative control cells expressing ß
1988-03-01
29 Statistical Machine Learning for the Cognitive Selection of Nonlinear Programming Algorithms in Engineering Design Optimization Toward...interpolation and Interpolation by Box Spline Surfaces Charles K. Chui, Harvey Diamond, Louise A. Raphael. 301 Knot Selection for Least Squares...West Virginia University, Morgantown, West Virginia; and Louise Raphael, National Science Foundation, Washington, DC Knot Selection for Least
Conceptualization and application of an approach for designing healthcare software interfaces.
Kumar, Ajit; Maskara, Reena; Maskara, Sanjeev; Chiang, I-Jen
2014-06-01
The aim of this study is to conceptualize a novel approach, which facilitates us to design prototype interfaces for healthcare software. Concepts and techniques from various disciplines were used to conceptualize an interface design approach named MORTARS (Map Original Rhetorical To Adapted Rhetorical Situation). The concepts and techniques included in this approach are (1) rhetorical situation - a concept of philosophy provided by Bitzer (1968); (2) move analysis - an applied linguistic technique provided by Swales (1990) and Bhatia (1993); (3) interface design guidelines - a cognitive and computer science concept provided by Johnson (2010); (4) usability evaluation instrument - an interface evaluation questionnaire provided by Lund (2001); (5) user modeling via stereotyping - a cognitive and computer science concept provided by Rich (1979). A prototype interface for outpatient clinic software was designed to introduce the underlying concepts of MORTARS. The prototype interface was evaluated by thirty-two medical informaticians. The medical informaticians found the designed prototype interface to be useful (73.3%), easy to use (71.9%), easy to learn (93.1%), and satisfactory (53.2%). MORTARS approach was found to be effective in designing the prototype user interface for the outpatient clinic software. This approach might be further used to design interfaces for various software pertaining to healthcare and other domains. Copyright © 2014 Elsevier Inc. All rights reserved.
2010-07-01
To be successful, the research needs to integrate kinesiological , neurophysiological, psychological, and cognitive science, and sociocultural... kinesiological neurophysiological, psychological, and cognitive science and sociocultural anthropology and information science components. Research and...successful, the research needs to integrate kinesiological , neurophysiological, psychological, and cognitive science, and sociocultural
Audience-contingent variation in action demonstrations for humans and computers.
Herberg, Jonathan S; Saylor, Megan M; Ratanaswasd, Palis; Levin, Daniel T; Wilkes, D Mitchell
2008-09-01
People may exhibit two kinds of modifications when demonstrating action for others: modifications to facilitate bottom-up, or sensory-based processing; and modifications to facilitate top-down, or knowledge-based processing. The current study examined actors' production of such modifications in action demonstrations for audiences that differed in their capacity for intentional reasoning. Actors' demonstrations of complex actions for a non-anthropomorphic computer system and for people (adult and toddler) were compared. Evidence was found for greater highlighting of top-down modifications in the demonstrations for the human audiences versus the computer audience. Conversely, participants highlighted simple perceptual modifications for the computer audience, producing more punctuated and wider ranging motions. This study suggests that people consider differences in their audiences when demonstrating action. 2008 Cognitive Science Society, Inc.
Reading Emotion From Mouse Cursor Motions: Affective Computing Approach.
Yamauchi, Takashi; Xiao, Kunchen
2018-04-01
Affective computing research has advanced emotion recognition systems using facial expressions, voices, gaits, and physiological signals, yet these methods are often impractical. This study integrates mouse cursor motion analysis into affective computing and investigates the idea that movements of the computer cursor can provide information about emotion of the computer user. We extracted 16-26 trajectory features during a choice-reaching task and examined the link between emotion and cursor motions. Participants were induced for positive or negative emotions by music, film clips, or emotional pictures, and they indicated their emotions with questionnaires. Our 10-fold cross-validation analysis shows that statistical models formed from "known" participants (training data) could predict nearly 10%-20% of the variance of positive affect and attentiveness ratings of "unknown" participants, suggesting that cursor movement patterns such as the area under curve and direction change help infer emotions of computer users. Copyright © 2017 Cognitive Science Society, Inc.
Cognitive science in popular film: the Cognitive Science Movie Index.
Motz, Benjamin
2013-10-01
HAL 9000. Morpheus. Skynet. These household names demonstrate the strong cultural impact of films depicting themes in cognitive science and the potential power of popular cinema for outreach and education. Considering their wide influence, there is value to aggregating these movies and reflecting on their renderings of our field. The Cognitive Science Movie Index (CSMI) serves these purposes, leveraging popular film for the advancement of the discipline. Copyright © 2013 Elsevier Ltd. All rights reserved.
On Learning the Past Tenses of English Verbs.
1985-10-01
RD-AI164 233 ON LEARING THE PAST TENSES OF ENGLISH YERBS(U) vi1 r CALIFORNIA UNIV SAN DIEGO LA JOLLA INST FOR COGNITIVE SCIENCE D E RUMELNART ET AL... COGNITIVE SCIENCE O I$FE13Me~ 0C*" INSTITUTE FOR COGNITIVE SCIENCE UNIVERSITY OF CALIFORNIA, SAN DIEGO LA JOLLA, CALIFORNIA 92093 - *~-’~7...8507 . *** David E. Rurneihart James L. McClelland Institute for Cognitive Science Department of Psychology University of Calif ornia. San Diego
Dormitory of Physical and Engineering Sciences: Sleeping Beauties May Be Sleeping Innovations.
van Raan, Anthony F J
2015-01-01
A 'Sleeping Beauty in Science' is a publication that goes unnoticed ('sleeps') for a long time and then, almost suddenly, attracts a lot of attention ('is awakened by a prince'). The aim of this paper is to present a general methodology to investigate (1) important properties of Sleeping Beauties such as the time-dependent distribution, author characteristics, journals and fields, and (2) the cognitive environment of Sleeping Beauties. We are particularly interested to find out to what extent Sleeping Beauties are application-oriented and thus are potential Sleeping Innovations. In this study we focus primarily on physics (including materials science and astrophysics) and present first results for chemistry and for engineering & computer science. We find that more than half of the SBs are application-oriented. To study the cognitive environments of Sleeping Beauties we develop a new approach in which the cognitive environment of the SBs is analyzed, based on the mapping of Sleeping Beauties using their citation links and conceptual relations, particularly co-citation mapping. In this way we investigate the research themes in which the SBs are 'used' and possible causes of why the premature work in the SBs becomes topical, i.e., the trigger of the awakening of the SBs. This approach is tested with a blue skies SB and an application-oriented SB. We think that the mapping procedures discussed in this paper are not only important for bibliometric analyses. They also provide researchers with useful, interactive tools to discover both relevant older work as well as new developments, for instance in themes related to Sleeping Beauties that are also Sleeping Innovations.
Music cognition and the cognitive sciences.
Pearce, Marcus; Rohrmeier, Martin
2012-10-01
Why should music be of interest to cognitive scientists, and what role does it play in human cognition? We review three factors that make music an important topic for cognitive scientific research. First, music is a universal human trait fulfilling crucial roles in everyday life. Second, music has an important part to play in ontogenetic development and human evolution. Third, appreciating and producing music simultaneously engage many complex perceptual, cognitive, and emotional processes, rendering music an ideal object for studying the mind. We propose an integrated status for music cognition in the Cognitive Sciences and conclude by reviewing challenges and big questions in the field and the way in which these reflect recent developments. Copyright © 2012 Cognitive Science Society, Inc.
Embedded assessment algorithms within home-based cognitive computer game exercises for elders.
Jimison, Holly; Pavel, Misha
2006-01-01
With the recent consumer interest in computer-based activities designed to improve cognitive performance, there is a growing need for scientific assessment algorithms to validate the potential contributions of cognitive exercises. In this paper, we present a novel methodology for incorporating dynamic cognitive assessment algorithms within computer games designed to enhance cognitive performance. We describe how this approach works for variety of computer applications and describe cognitive monitoring results for one of the computer game exercises. The real-time cognitive assessments also provide a control signal for adapting the difficulty of the game exercises and providing tailored help for elders of varying abilities.
M69. Changes in Neural Measures of Emotion Processes Following Targeted Social Cognition Training
Saxena, Abhishek; Guty, Erin; Dodell-Feder, David; Yin, Hong; Haut, Kristen; Nahum, Mor; Hooker, Christine
2017-01-01
Abstract Background: Research has shown that people who develop a psychotic disorder display observable decreases in cognitive abilities even before they begin to display overt symptoms of psychosis. Thus research has shown an increased interest in targeted cognitive training (TCT) as possible technique to deter or even stop cognitive deterioration in psychiatric disorders, such as schizophrenia. Although TCT has shown promising improvements in certain cognitive deficits, TCT research has largely ignored social cognition training. The current study investigates whether targeted social cognition training may be a viable method of improving social cognition in patient populations. Methods: To this end, 56 healthy adults from the community completed MRI scans before and after a 2-week period, where participants were randomized to complete either up to 10 hours of SocialVille, a computerized social cognition training program from PositScience Corporation, or up to 10 hours of common computer games. SocialVille consists of a variety of social cognition exercises, such as face emotion recognition, gaze tracking, and recognizing social incongruences. During the MRI scans, participants completed an emotion identification task (EmotID), consisting of object discrimination and emotion discrimination blocks. During the object discrimination blocks, participants where shown pictures of 2 cars and were asked to indicate whether the cars were the same or different, while in the emotion discrimination blocks, participants were shown 2 faces and were asked whether the faces displayed the same emotion. Results: Behavioral data indicated that controlling for initial performance, sex, age, and estimated IQ, being in the TCT group only predicted better performance during the emotion discrimination blocks after treatment compared to those who completed placebo computer games. Additionally, fMRI analyses indicate that brain regions central to the emotion processes (ie, amygdala) and the social processes (ie, MPFC), saw significant increases in connectivity to other regions of the brain associated with emotion processes during the emotion discrimination blocks after training among the participants randomized to the TCT group compared to those assigned to complete placebo computer games, and in comparison to connectivity between these regions prior to training and during the object discrimination blocks. Conclusion: These findings indicate that social cognition can be improved in healthy adults with varying ability at baseline. Furthermore, these results indicate that it is possible to target specific neural systems associated with emotion and social cognition and show a learning-induced neuroplastic response. Thus, programs, like SocialVille, may be useful tools for targeted treatment in psychiatric populations where social cognition deficits are prominent, specifically schizophrenia.
Walsh, Matthew M; Gluck, Kevin A; Gunzelmann, Glenn; Jastrzembski, Tiffany; Krusmark, Michael
2018-06-01
The spacing effect is among the most widely replicated empirical phenomena in the learning sciences, and its relevance to education and training is readily apparent. Yet successful applications of spacing effect research to education and training is rare. Computational modeling can provide the crucial link between a century of accumulated experimental data on the spacing effect and the emerging interest in using that research to enable adaptive instruction. In this paper, we review relevant literature and identify 10 criteria for rigorously evaluating computational models of the spacing effect. Five relate to evaluating the theoretic adequacy of a model, and five relate to evaluating its application potential. We use these criteria to evaluate a novel computational model of the spacing effect called the Predictive Performance Equation (PPE). Predictive Performance Equation combines elements of earlier models of learning and memory including the General Performance Equation, Adaptive Control of Thought-Rational, and the New Theory of Disuse, giving rise to a novel computational account of the spacing effect that performs favorably across the complete sets of theoretic and applied criteria. We implemented two other previously published computational models of the spacing effect and compare them to PPE using the theoretic and applied criteria as guides. Copyright © 2018 Cognitive Science Society, Inc.
The part of cognitive science that is philosophy.
Dennett, Daniel C
2009-04-01
There is much good work for philosophers to do in cognitive science if they adopt the constructive attitude that prevails in science, work toward testable hypotheses, and take on the task of clarifying the relationship between the scientific concepts and the everyday concepts with which we conduct our moral lives. Copyright © 2009 Cognitive Science Society, Inc.
Morris, Alan H
2018-02-01
Our education system seems to fail to enable clinicians to broadly understand core physiological principles. The emphasis on reductionist science, including "omics" branches of research, has likely contributed to this decrease in understanding. Consequently, clinicians cannot be expected to consistently make clinical decisions linked to best physiological evidence. This is a large-scale problem with multiple determinants, within an even larger clinical decision problem: the failure of clinicians to consistently link their decisions to best evidence. Clinicians, like all human decision-makers, suffer from significant cognitive limitations. Detailed context-sensitive computer protocols can generate personalized medicine instructions that are well matched to individual patient needs over time and can partially resolve this problem.
ERIC Educational Resources Information Center
National Science Foundation, Washington, DC.
Cognitive science, the study of both biological and artificial intelligent systems, is an inherently interdisciplinary activity that embraces aspects of psychology, linguistics, artificial intelligence, neuroscience, engineering, and other behavioral and social sciences. This document reports the results of a workshop designed to provide advice to…
Is cognitive science usefully cast as complexity science?
Van Orden, Guy; Stephen, Damian G
2012-01-01
Readers of TopiCS are invited to join a debate about the utility of ideas and methods of complexity science. The topics of debate include empirical instances of qualitative change in cognitive activity and whether this empirical work demonstrates sufficiently the empirical flags of complexity. In addition, new phenomena discovered by complexity scientists, and motivated by complexity theory, call into question some basic assumptions of conventional cognitive science such as stable equilibria and homogeneous variance. The articles and commentaries that appear in this issue also illustrate a new debate style format for topiCS. Copyright © 2011 Cognitive Science Society, Inc.
Stip, Emmanuel; Rialle, Vincent
2005-04-01
In light of the advent of new technologies, we proposed to reexamine certain challenges posed by cognitive remediation and social reintegration (that is, deinstitutionalization) of patients with severe and persistent mental disorders. We reviewed literature on cognition, remediation, smart homes, as well as on objects and utilities, using medical and computer science electronic library and Internet searches. These technologies provide solutions for disabled persons with respect to care delivery, workload reduction, and socialization. Examples include home support, video conferencing, remote monitoring of medical parameters through sensors, teledetection of critical situations (for example, a fall or malaise), measures of daily living activities, and help with tasks of daily living. One of the key concepts unifying all these technologies is the health-smart home. We present the notion of the health-smart home in general and then examine it more specifically in relation to schizophrenia. Management of people with schizophrenia with cognitive deficits who are being rehabilitated in the community can be improved with the use of technology; however, such technology has ethical ramifications.
Human-system interfaces for space cognitive awareness
NASA Astrophysics Data System (ADS)
Ianni, J.
Space situational awareness is a human activity. We have advanced sensors and automation capabilities but these continue to be tools for humans to use. The reality is, however, that humans cannot take full advantage of the power of these tools due to time constraints, cognitive limitations, poor tool integration, poor human-system interfaces, and other reasons. Some excellent tools may never be used in operations and, even if they were, they may not be well suited to provide a cohesive and comprehensive picture. Recognizing this, the Air Force Research Laboratory (AFRL) is applying cognitive science principles to increase the knowledge derived from existing tools and creating new capabilities to help space analysts and decision makers. At the center of this research is Sensemaking Support Environment technology. The concept is to create cognitive-friendly computer environments that connect critical and creative thinking for holistic decision making. AFRL is also investigating new visualization technologies for multi-sensor exploitation and space weather, human-to-human collaboration technologies, and other technology that will be discussed in this paper.
Functional relations and cognitive psychology: Lessons from human performance and animal research.
Proctor, Robert W; Urcuioli, Peter J
2016-02-01
We consider requirements for effective interdisciplinary communication and explore alternative interpretations of "building bridges between functional and cognitive psychology." If the bridges are intended to connect radical behaviourism and cognitive psychology, or functional contextualism and cognitive psychology, the efforts are unlikely to be successful. But if the bridges are intended to connect functional relationships and cognitive theory, no construction is needed because the bridges already exist within cognitive psychology. We use human performance and animal research to illustrate the latter point and to counter the claim that the functional approach is unique in offering a close relationship between science and practice. Effective communication will be enhanced and, indeed, may only occur if the goal of functional contextualism extends beyond just "the advancement of functional contextual cognitive and behavioral science and practice" to "the advancement of cognitive and behavioral science and practice" without restriction. © 2015 International Union of Psychological Science.
Extended cognition in science communication.
Ludwig, David
2014-11-01
The aim of this article is to propose a methodological externalism that takes knowledge about science to be partly constituted by the environment. My starting point is the debate about extended cognition in contemporary philosophy and cognitive science. Externalists claim that human cognition extends beyond the brain and can be partly constituted by external devices. First, I show that most studies of public knowledge about science are based on an internalist framework that excludes the environment we usually utilize to make sense of science and does not allow the possibility of extended knowledge. In a second step, I argue that science communication studies should adopt a methodological externalism and accept that knowledge about science can be partly realized by external information resources such as Wikipedia. © The Author(s) 2013.
Anthropology in cognitive science.
Bender, Andrea; Hutchins, Edwin; Medin, Douglas
2010-07-01
This paper reviews the uneven history of the relationship between Anthropology and Cognitive Science over the past 30 years, from its promising beginnings, followed by a period of disaffection, on up to the current context, which may lay the groundwork for reconsidering what Anthropology and (the rest of) Cognitive Science have to offer each other. We think that this history has important lessons to teach and has implications for contemporary efforts to restore Anthropology to its proper place within Cognitive Science. The recent upsurge of interest in the ways that thought may shape and be shaped by action, gesture, cultural experience, and language sets the stage for, but so far has not fully accomplished, the inclusion of Anthropology as an equal partner. Copyright © 2010 Cognitive Science Society, Inc.
Combined neurostimulation and neuroimaging in cognitive neuroscience: past, present, and future.
Bestmann, Sven; Feredoes, Eva
2013-08-01
Modern neurostimulation approaches in humans provide controlled inputs into the operations of cortical regions, with highly specific behavioral consequences. This enables causal structure-function inferences, and in combination with neuroimaging, has provided novel insights into the basic mechanisms of action of neurostimulation on distributed networks. For example, more recent work has established the capacity of transcranial magnetic stimulation (TMS) to probe causal interregional influences, and their interaction with cognitive state changes. Combinations of neurostimulation and neuroimaging now face the challenge of integrating the known physiological effects of neurostimulation with theoretical and biological models of cognition, for example, when theoretical stalemates between opposing cognitive theories need to be resolved. This will be driven by novel developments, including biologically informed computational network analyses for predicting the impact of neurostimulation on brain networks, as well as novel neuroimaging and neurostimulation techniques. Such future developments may offer an expanded set of tools with which to investigate structure-function relationships, and to formulate and reconceptualize testable hypotheses about complex neural network interactions and their causal roles in cognition. © 2013 New York Academy of Sciences.
NASA Technical Reports Server (NTRS)
Memarsadeghi, Nargess
2015-01-01
Scientists and engineers constantly face new challenges, despite myriad advances in computing. More sets of data are collected today from earth and sky than there is time or resources available to carefully analyze them. Some problems either don't have fast algorithms to solve them or have solutions that must be found among millions of options, a situation akin to finding a needle in a haystack. But all hope is not lost: advances in technology and the Internet have empowered the general public to participate in the scientific process via individual computational resources and brain cognition, which isn't matched by any machine. Citizen scientists are volunteers who perform scientific work by making observations, collecting and disseminating data, making measurements, and analyzing or interpreting data without necessarily having any scientific training. In so doing, individuals from all over the world can contribute to science in ways that wouldn't have been otherwise possible.
Science Teachers' Epistemic Cognition in Instructional Decision Making
ERIC Educational Resources Information Center
Ponnock, Annette R.
2017-01-01
One understudied barrier to science education reform concerns teachers' cognitive processes and how they relate to instructional decision-making. Epistemic cognition--teachers' beliefs about knowledge and knowledge acquisition and goals for their students' knowledge acquisition--could provide important insights into the choices science teachers…
Useful theories make predictions.
Howes, Andrew
2012-01-01
Stephen and Van Orden (this issue) propose that there is a complex system approach to cognitive science, and collectively the authors of the papers presented in this issue believe that this approach provides the means to drive a revolution in the science of the mind. Unfortunately, however illuminating, this explanation is absent and hyperbole is all too extensive. In contrast, I argue (1) that dynamic systems theory is not new to cognitive science and does not provide a basis for a revolution, (2) it is not necessary to reject cognitive science in order to explain the constraints imposed by the body and the environment, (3) it is not necessary, as Silberstein and Chemero (this issue) appear to do, to reject cognitive science in order to explain consciousness, and (4) our understanding of pragmatics is not advanced by Gibbs and Van Orden's (this issue) "self-organized criticality".? Any debate about the future of cognitive science could usefully focus on predictive adequacy. Unfortunately, this is not the approach taken by the authors of this issue. Copyright © 2012 Cognitive Science Society, Inc.
Cognitive Neuroimaging: Cognitive Science out of the Armchair
ERIC Educational Resources Information Center
de Zubicaray, Greig I.
2006-01-01
Cognitive scientists were not quick to embrace the functional neuroimaging technologies that emerged during the late 20th century. In this new century, cognitive scientists continue to question, not unreasonably, the relevance of functional neuroimaging investigations that fail to address questions of interest to cognitive science. However, some…
The Impact of Cognitive and Non-Cognitive Personality Traits on Computer Literacy Level
ERIC Educational Resources Information Center
Saparniene, Diana; Merkys, Gediminas; Saparnis, Gintaras
2006-01-01
Purpose: The paper deals with the study of students' computer literacy one of the purposes being demonstration the impact of the cognitive and non-cognitive personality traits (attention, verbal and non-verbal intelligence, emotional-motivational relationship with computer, learning strategies, etc.) on the quality of computer literacy.…
The emergence of mind and brain: an evolutionary, computational, and philosophical approach.
Mainzer, Klaus
2008-01-01
Modern philosophy of mind cannot be understood without recent developments in computer science, artificial intelligence (AI), robotics, neuroscience, biology, linguistics, and psychology. Classical philosophy of formal languages as well as symbolic AI assume that all kinds of knowledge must explicitly be represented by formal or programming languages. This assumption is limited by recent insights into the biology of evolution and developmental psychology of the human organism. Most of our knowledge is implicit and unconscious. It is not formally represented, but embodied knowledge, which is learnt by doing and understood by bodily interacting with changing environments. That is true not only for low-level skills, but even for high-level domains of categorization, language, and abstract thinking. The embodied mind is considered an emergent capacity of the brain as a self-organizing complex system. Actually, self-organization has been a successful strategy of evolution to handle the increasing complexity of the world. Genetic programs are not sufficient and cannot prepare the organism for all kinds of complex situations in the future. Self-organization and emergence are fundamental concepts in the theory of complex dynamical systems. They are also applied in organic computing as a recent research field of computer science. Therefore, cognitive science, AI, and robotics try to model the embodied mind in an artificial evolution. The paper analyzes these approaches in the interdisciplinary framework of complex dynamical systems and discusses their philosophical impact.
Dufau, Stephane; Duñabeitia, Jon Andoni; Moret-Tatay, Carmen; McGonigal, Aileen; Peeters, David; Alario, F-Xavier; Balota, David A; Brysbaert, Marc; Carreiras, Manuel; Ferrand, Ludovic; Ktori, Maria; Perea, Manuel; Rastle, Kathy; Sasburg, Olivier; Yap, Melvin J; Ziegler, Johannes C; Grainger, Jonathan
2011-01-01
Investigating human cognitive faculties such as language, attention, and memory most often relies on testing small and homogeneous groups of volunteers coming to research facilities where they are asked to participate in behavioral experiments. We show that this limitation and sampling bias can be overcome by using smartphone technology to collect data in cognitive science experiments from thousands of subjects from all over the world. This mass coordinated use of smartphones creates a novel and powerful scientific "instrument" that yields the data necessary to test universal theories of cognition. This increase in power represents a potential revolution in cognitive science.
Georgetown Institute for Cognitive and Computational Sciences
2004-04-01
lumbar DRG after formalin injection into the hindpaw. Dilute formalin (1.8%) was injected into the rat hindpaw and DRG were harvested 30 minutes later...staining (Figure 140, arrows) on the ipsilateral side to nerve crush. In the lumbar spinal cord, the site of sciatic innervation, there was a dramatic...Proteases in traumatic brain injury. Proieases in Biology and Disease, Volume 3.: Proteases in the Brain, Edited by Nigel Hooper and Uwe Lendeckel, in
Designing an Advanced Instructional Design Advisor: Principles of Instructional Design. Volume 2
1991-05-01
ones contained in this paper would comprise a substantial part of the knowledge base for the AIDA . 14. SUBJECT TERMS IS.NUMBER OF PAGES ucigoirlive...the classroom (e.g., computer simulations models can be used to enhance CBI). The Advanced Instructional Design Advisor is a project aimed at providing... model shares with its variations. Tennyson then identifies research- based prescriptions from the cognitive sciences which should become part of ISD in
ERIC Educational Resources Information Center
Simonson, Michael R., Ed.; Frey, Diane, Ed.
1989-01-01
The 46 papers is this volume represent some of the most current thinking in educational communications and technology. Individual papers address the following topics: gender differences in the selection of elective computer science courses and in the selection of non-traditional careers; instruction for individuals with different cognitive styles;…
Negotiating the Traffic: Can Cognitive Science Help Make Autonomous Vehicles a Reality?
Chater, Nick; Misyak, Jennifer; Watson, Derrick; Griffiths, Nathan; Mouzakitis, Alex
2018-02-01
To drive safely among human drivers, cyclists and pedestrians, autonomous vehicles will need to mimic, or ideally improve upon, humanlike driving. Yet, driving presents us with difficult problems of joint action: 'negotiating' with other users over shared road space. We argue that autonomous driving provides a test case for computational theories of social interaction, with fundamental implications for the development of autonomous vehicles. Copyright © 2017 Elsevier Ltd. All rights reserved.
Greater Philadelphia Bioinformatics Alliance (GPBA) 3rd Annual Retreat 2005
2005-11-01
Using Probabilistic Network Reliability. Genome Res. 14:1170-1175 [27] Batagelj , V. and Mrvar , A. (1998). Pajek: Program for large network analysis...and Neural Computation, Division of Informatics, Centre for Cognitive Science, University of Edinburgh, Scotland, April 1996 . www.anc.ed.ac.uk/-mjo...research center in the College of Engineering, and one of the foremost academic research centers in its field. From 1996 to 1998 he was the Founding
Pezzulo, Giovanni; Barsalou, Lawrence W.; Cangelosi, Angelo; Fischer, Martin H.; McRae, Ken; Spivey, Michael J.
2013-01-01
Grounded theories assume that there is no central module for cognition. According to this view, all cognitive phenomena, including those considered the province of amodal cognition such as reasoning, numeric, and language processing, are ultimately grounded in (and emerge from) a variety of bodily, affective, perceptual, and motor processes. The development and expression of cognition is constrained by the embodiment of cognitive agents and various contextual factors (physical and social) in which they are immersed. The grounded framework has received numerous empirical confirmations. Still, there are very few explicit computational models that implement grounding in sensory, motor and affective processes as intrinsic to cognition, and demonstrate that grounded theories can mechanistically implement higher cognitive abilities. We propose a new alliance between grounded cognition and computational modeling toward a novel multidisciplinary enterprise: Computational Grounded Cognition. We clarify the defining features of this novel approach and emphasize the importance of using the methodology of Cognitive Robotics, which permits simultaneous consideration of multiple aspects of grounding, embodiment, and situatedness, showing how they constrain the development and expression of cognition. PMID:23346065
The structure of the cognitive revolution: An examination from the philosophy of science
O'Donohue, William; Ferguson, Kyle E.; Naugle, Amy E.
2003-01-01
The received view is that psychology has undergone several scientific revolutions similar to those that occurred in the physical sciences. Of these, this paper will consider the cognitive revolution. Because the arguments in favor of the existence of a cognitive revolution are cast using the concepts and terms of revolutionary science, we will examine the cognitive revolution using accounts of revolutionary science advanced by five influential philosophers of science. Specifically, we will draw from the philosophical positions of Popper, Kuhn, Lakatos, Laudan, and Gross for the purpose of discussion. We conclude that no substantive revolution took place according to these accounts. This conclusion is based on data gathered from some of the major participants in the “cognitive revolution” and on a general scholarly survey of the literature. We argue that the so-called cognitive revolution is best characterized as a socio-rhetorical phenomenon. PMID:22478396
The Association Between Computer Use and Cognition Across Adulthood: Use it so You Won't Lose it?
Tun, Patricia A.; Lachman, Margie E.
2012-01-01
Understanding the association between computer use and adult cognition has been limited until now by self-selected samples with restricted ranges of age and education. Here we studied effects of computer use in a large national sample (N=2671) of adults aged 32 to 84, assessing cognition with the Brief Test of Adult Cognition by Telephone (Tun & Lachman, 2005), and executive function with the Stop and Go Switch Task (Tun & Lachman, 2008). Frequency of computer activity was associated with cognitive performance after controlling for age, sex, education, and health status: that is, individuals who used the computer frequently scored significantly higher than those who seldom used the computer. Greater computer use was also associated with better executive function on a task-switching test, even after controlling for basic cognitive ability as well as demographic variables. These findings suggest that frequent computer activity is associated with good cognitive function, particularly executive control, across adulthood into old age, especially for those with lower intellectual ability. PMID:20677884
Cognitive and Neural Sciences Division 1990 Programs.
ERIC Educational Resources Information Center
Vaughan, Willard S., Jr., Ed.
Research and development efforts carried out under sponsorship of the Cognitive and Neural Sciences Division of the Office of Naval Research during fiscal year 1990 are described in this compilation of project description summaries. The Division's research is organized in three types of programs: (1) Cognitive Science (the human learner--cognitive…
New Frontiers in Language Evolution and Development.
Oller, D Kimbrough; Dale, Rick; Griebel, Ulrike
2016-04-01
This article introduces the Special Issue and its focus on research in language evolution with emphasis on theory as well as computational and robotic modeling. A key theme is based on the growth of evolutionary developmental biology or evo-devo. The Special Issue consists of 13 articles organized in two sections: A) Theoretical foundations and B) Modeling and simulation studies. All the papers are interdisciplinary in nature, encompassing work in biological and linguistic foundations for the study of language evolution as well as a variety of computational and robotic modeling efforts shedding light on how language may be developed and may have evolved. Copyright © 2016 Cognitive Science Society, Inc.
Simulation of an array-based neural net model
NASA Technical Reports Server (NTRS)
Barnden, John A.
1987-01-01
Research in cognitive science suggests that much of cognition involves the rapid manipulation of complex data structures. However, it is very unclear how this could be realized in neural networks or connectionist systems. A core question is: how could the interconnectivity of items in an abstract-level data structure be neurally encoded? The answer appeals mainly to positional relationships between activity patterns within neural arrays, rather than directly to neural connections in the traditional way. The new method was initially devised to account for abstract symbolic data structures, but it also supports cognitively useful spatial analogue, image-like representations. As the neural model is based on massive, uniform, parallel computations over 2D arrays, the massively parallel processor is a convenient tool for simulation work, although there are complications in using the machine to the fullest advantage. An MPP Pascal simulation program for a small pilot version of the model is running.
Modeling Co-evolution of Speech and Biology.
de Boer, Bart
2016-04-01
Two computer simulations are investigated that model interaction of cultural evolution of language and biological evolution of adaptations to language. Both are agent-based models in which a population of agents imitates each other using realistic vowels. The agents evolve under selective pressure for good imitation. In one model, the evolution of the vocal tract is modeled; in the other, a cognitive mechanism for perceiving speech accurately is modeled. In both cases, biological adaptations to using and learning speech evolve, even though the system of speech sounds itself changes at a more rapid time scale than biological evolution. However, the fact that the available acoustic space is used maximally (a self-organized result of cultural evolution) is constant, and therefore biological evolution does have a stable target. This work shows that when cultural and biological traits are continuous, their co-evolution may lead to cognitive adaptations that are strong enough to detect empirically. Copyright © 2016 Cognitive Science Society, Inc.
Seeking Synthesis: The Integrative Problem in Understanding Language and Its Evolution.
Dale, Rick; Kello, Christopher T; Schoenemann, P Thomas
2016-04-01
We discuss two problems for a general scientific understanding of language, sequences and synergies: how language is an intricately sequenced behavior and how language is manifested as a multidimensionally structured behavior. Though both are central in our understanding, we observe that the former tends to be studied more than the latter. We consider very general conditions that hold in human brain evolution and its computational implications, and identify multimodal and multiscale organization as two key characteristics of emerging cognitive function in our species. This suggests that human brains, and cognitive function specifically, became more adept at integrating diverse information sources and operating at multiple levels for linguistic performance. We argue that framing language evolution, learning, and use in terms of synergies suggests new research questions, and it may be a fruitful direction for new developments in theory and modeling of language as an integrated system. Copyright © 2016 Cognitive Science Society, Inc.
Grammatical Constructions as Relational Categories.
Goldwater, Micah B
2017-07-01
This paper argues that grammatical constructions, specifically argument structure constructions that determine the "who did what to whom" part of sentence meaning and how this meaning is expressed syntactically, can be considered a kind of relational category. That is, grammatical constructions are represented as the abstraction of the syntactic and semantic relations of the exemplar utterances that are expressed in that construction, and it enables the generation of novel exemplars. To support this argument, I review evidence that there are parallel behavioral patterns between how children learn relational categories generally and how they learn grammatical constructions specifically. Then, I discuss computational simulations of how grammatical constructions are abstracted from exemplar sentences using a domain-general relational cognitive architecture. Last, I review evidence from adult language processing that shows parallel behavioral patterns with expert behavior from other cognitive domains. After reviewing the evidence, I consider how to integrate this account with other theories of language development. Copyright © 2017 Cognitive Science Society, Inc.
ERIC Educational Resources Information Center
Hong, Jon-Chao; Hwang, Ming-Yueh; Tai, Kai-Hsin; Tsai, Chi-Ruei
2017-01-01
Based on the cognitive-affective theory, the present study designed a science inquiry learning model, "predict-observe-explain" (POE), and implemented it in an app called "WhyWhy" to examine the effectiveness of students' science inquiry learning practice. To understand how POE can affect the cognitive-affective learning…
Translation Meets Cognitive Science: The Imprint of Translation on Cognitive Processing
ERIC Educational Resources Information Center
Rojo, Ana
2015-01-01
Translation has long played a role in linguistic and literary studies research. More recently, the theoretical and methodological concerns of process research have given translation an additional role in cognitive science. The interest in the cognitive aspects of translation has led scholars to turn to disciplines such as cognitive linguistics,…
A new perspective on the perceptual selectivity of attention under load.
Giesbrecht, Barry; Sy, Jocelyn; Bundesen, Claus; Kyllingsbaek, Søren
2014-05-01
The human attention system helps us cope with a complex environment by supporting the selective processing of information relevant to our current goals. Understanding the perceptual, cognitive, and neural mechanisms that mediate selective attention is a core issue in cognitive neuroscience. One prominent model of selective attention, known as load theory, offers an account of how task demands determine when information is selected and an account of the efficiency of the selection process. However, load theory has several critical weaknesses that suggest that it is time for a new perspective. Here we review the strengths and weaknesses of load theory and offer an alternative biologically plausible computational account that is based on the neural theory of visual attention. We argue that this new perspective provides a detailed computational account of how bottom-up and top-down information is integrated to provide efficient attentional selection and allocation of perceptual processing resources. © 2014 New York Academy of Sciences.
Attention Modulates Spatial Precision in Multiple-Object Tracking.
Srivastava, Nisheeth; Vul, Ed
2016-01-01
We present a computational model of multiple-object tracking that makes trial-level predictions about the allocation of visual attention and the effect of this allocation on observers' ability to track multiple objects simultaneously. This model follows the intuition that increased attention to a location increases the spatial resolution of its internal representation. Using a combination of empirical and computational experiments, we demonstrate the existence of a tight coupling between cognitive and perceptual resources in this task: Low-level tracking of objects generates bottom-up predictions of error likelihood, and high-level attention allocation selectively reduces error probabilities in attended locations while increasing it at non-attended locations. Whereas earlier models of multiple-object tracking have predicted the big picture relationship between stimulus complexity and response accuracy, our approach makes accurate predictions of both the macro-scale effect of target number and velocity on tracking difficulty and micro-scale variations in difficulty across individual trials and targets arising from the idiosyncratic within-trial interactions of targets and distractors. Copyright © 2016 Cognitive Science Society, Inc.
ERIC Educational Resources Information Center
Hacioglu, Yasemin; Yamak, Havva; Kavak, Nusret
2016-01-01
The aim of this study is to reveal pre-service science teachers' cognitive structures regarding Science, Technology, Engineering, Mathematics (STEM) and science education. The study group of the study consisted of 192 pre-service science teachers. A Free Word Association Test (WAT) consisting of science, technology, engineering, mathematics and…
The Tractable Cognition Thesis
ERIC Educational Resources Information Center
van Rooij, Iris
2008-01-01
The recognition that human minds/brains are finite systems with limited resources for computation has led some researchers to advance the "Tractable Cognition thesis": Human cognitive capacities are constrained by computational tractability. This thesis, if true, serves cognitive psychology by constraining the space of computational-level theories…
NASA Astrophysics Data System (ADS)
Bautista, Nazan Uludag
2011-06-01
This study investigated the effectiveness of an Early Childhood Education science methods course that focused exclusively on providing various mastery (i.e., enactive, cognitive content, and cognitive pedagogical) and vicarious experiences (i.e., cognitive self-modeling, symbolic modeling, and simulated modeling) in increasing preservice elementary teachers' self-efficacy beliefs. Forty-four preservice elementary teachers participated in the study. Analysis of the quantitative (STEBI-b) and qualitative (informal surveys) data revealed that personal science teaching efficacy and science teaching outcome expectancy beliefs increased significantly over the semester. Enactive mastery, cognitive pedagogical mastery, symbolic modeling, and cognitive self-modeling were the major sources of self-efficacy. This list was followed by cognitive content mastery and simulated modeling. This study has implications for science teacher educators.
Connecting cognition and consumer choice.
Bartels, Daniel M; Johnson, Eric J
2015-02-01
We describe what can be gained from connecting cognition and consumer choice by discussing two contexts ripe for interaction between the two fields. The first-context effects on choice-has already been addressed by cognitive science yielding insights about cognitive process but there is promise for more interaction. The second is learning and representation in choice where relevant theories in cognitive science could be informed by consumer choice, and in return, could pose and answer new questions. We conclude by discussing how these two fields of research stand to benefit from more interaction, citing examples of how interfaces of cognitive science with other fields have been illuminating for theories of cognition. Copyright © 2014 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Schäfer, Andreas; Holz, Jan; Leonhardt, Thiemo; Schroeder, Ulrik; Brauner, Philipp; Ziefle, Martina
2013-06-01
In this study, we address the problem of low retention and high dropout rates of computer science university students in early semesters of the studies. Complex and high abstract mathematical learning materials have been identified as one reason for the dropout rate. In order to support the understanding and practicing of core mathematical concepts, we developed a game-based multitouch learning environment in which the need for a suitable learning environment for mathematical logic was combined with the ability to train cooperation and collaboration in a learning scenario. As application domain, the field of mathematical logic had been chosen. The development process was accomplished along three steps: First, ethnographic interviews were run with 12 students of computer science revealing typical problems with mathematical logic. Second, a multitouch learning environment was developed. The game consists of multiple learning and playing modes in which teams of students can collaborate or compete against each other. Finally, a twofold evaluation of the environment was carried out (user study and cognitive walk-through). Overall, the evaluation showed that the game environment was easy to use and rated as helpful: The chosen approach of a multiplayer game supporting competition, collaboration, and cooperation is perceived as motivating and "fun."
NASA Astrophysics Data System (ADS)
Pinnick, Cassandra L.
2008-11-01
This paper examines the relation between situated cognition theory in science education, and feminist standpoint theory in philosophy of science. It shows that situated cognition is an idea borrowed from a long since discredited philosophy of science. It argues that feminist standpoint theory ought not be indulged as it is a failed challenge to traditional philosophy of science. Standpoint theory diverts attention away from the abiding educational and career needs of women in science. In the interest of women in science, and in the interest of science, science educators would do best for their constituencies by a return to feminist philosophy understood as the demand for equal access and a level playing field for women in science and society.
Fasano, Fabrizio; Mitolo, Micaela; Gardini, Simona; Venneri, Annalena; Caffarra, Paolo; Pazzaglia, Francesca
2018-01-01
Recently, efforts have been made to combine complementary perspectives in the assessment of Alzheimer type dementia. Of particular interest is the definition of the fingerprints of an early stage of the disease known as Mild Cognitive Impairment or prodromal Alzheimer's Disease. Machine learning approaches have been shown to be extremely suitable for the implementation of such a combination. In the present pilot study we combined the machine learning approach with structural magnetic resonance imaging and cognitive test assessments to classify a small cohort of 11 healthy participants and 11 patients experiencing Mild Cognitive Impairment. Cognitive assessment included a battery of standardised tests and a battery of experimental visuospatial memory tests. Correct classification was achieved in 100% of the participants, suggesting that the combination of neuroimaging with more complex cognitive tests is suitable for early detection of Alzheimer Disease. In particular, the results highlighted the importance of the experimental visuospatial memory test battery in the efficiency of classification, suggesting that the high-level brain computational framework underpinning the participant's performance in these ecological tests may represent a "natural filter" in the exploration of cognitive patterns of information able to identify early signs of the disease. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.
Markowitz, Dina G; DuPré, Michael J
2007-01-01
The University of Rochester's Graduate Experience in Science Education (GESE) course familiarizes biomedical science graduate students interested in pursuing academic career tracks with a fundamental understanding of some of the theory, principles, and concepts of science education. This one-semester elective course provides graduate students with practical teaching and communication skills to help them better relate science content to, and increase their confidence in, their own teaching abilities. The 2-h weekly sessions include an introduction to cognitive hierarchies, learning styles, and multiple intelligences; modeling and coaching some practical aspects of science education pedagogy; lesson-planning skills; an introduction to instructional methods such as case studies and problem-based learning; and use of computer-based instructional technologies. It is hoped that the early development of knowledge and skills about teaching and learning will encourage graduate students to continue their growth as educators throughout their careers. This article summarizes the GESE course and presents evidence on the effectiveness of this course in providing graduate students with information about teaching and learning that they will use throughout their careers.
DuPré, Michael J.
2007-01-01
The University of Rochester's Graduate Experience in Science Education (GESE) course familiarizes biomedical science graduate students interested in pursuing academic career tracks with a fundamental understanding of some of the theory, principles, and concepts of science education. This one-semester elective course provides graduate students with practical teaching and communication skills to help them better relate science content to, and increase their confidence in, their own teaching abilities. The 2-h weekly sessions include an introduction to cognitive hierarchies, learning styles, and multiple intelligences; modeling and coaching some practical aspects of science education pedagogy; lesson-planning skills; an introduction to instructional methods such as case studies and problem-based learning; and use of computer-based instructional technologies. It is hoped that the early development of knowledge and skills about teaching and learning will encourage graduate students to continue their growth as educators throughout their careers. This article summarizes the GESE course and presents evidence on the effectiveness of this course in providing graduate students with information about teaching and learning that they will use throughout their careers. PMID:17785406
Parallel Distributed Processing at 25: further explorations in the microstructure of cognition.
Rogers, Timothy T; McClelland, James L
2014-08-01
This paper introduces a special issue of Cognitive Science initiated on the 25th anniversary of the publication of Parallel Distributed Processing (PDP), a two-volume work that introduced the use of neural network models as vehicles for understanding cognition. The collection surveys the core commitments of the PDP framework, the key issues the framework has addressed, and the debates the framework has spawned, and presents viewpoints on the current status of these issues. The articles focus on both historical roots and contemporary developments in learning, optimality theory, perception, memory, language, conceptual knowledge, cognitive control, and consciousness. Here we consider the approach more generally, reviewing the original motivations, the resulting framework, and the central tenets of the underlying theory. We then evaluate the impact of PDP both on the field at large and within specific subdomains of cognitive science and consider the current role of PDP models within the broader landscape of contemporary theoretical frameworks in cognitive science. Looking to the future, we consider the implications for cognitive science of the recent success of machine learning systems called "deep networks"-systems that build on key ideas presented in the PDP volumes. Copyright © 2014 Cognitive Science Society, Inc.
2015-12-01
combine satisficing behaviour with learning and adaptation through environmental feedback. This a sequential decision making with one alternative...next action that an opponent will most likely take in a strategic interaction. Also, cognitive models derived from instance- based learning theory (IBL... through instance- based learning . In Y. Li (Ed.), Lecture Notes in Computer Science (Vol. 6818, pp. 281-293). Heidelberg: Springer Berlin. Gonzalez, C
Perspectives on modeling in cognitive science.
Shiffrin, Richard M
2010-10-01
This commentary gives a personal perspective on modeling and modeling developments in cognitive science, starting in the 1950s, but focusing on the author's personal views of modeling since training in the late 1960s, and particularly focusing on advances since the official founding of the Cognitive Science Society. The range and variety of modeling approaches in use today are remarkable, and for many, bewildering. Yet to come to anything approaching adequate insights into the infinitely complex fields of mind, brain, and intelligent systems, an extremely wide array of modeling approaches is vital and necessary. Copyright © 2010 Cognitive Science Society, Inc.
Enquire within: cultural evolution and cognitive science.
Heyes, Cecilia
2018-04-05
Cultural evolution and cognitive science need each other. Cultural evolution needs cognitive science to find out whether the conditions necessary for Darwinian evolution are met in the cultural domain. Cognitive science needs cultural evolution to explain the origins of distinctively human cognitive processes. Focusing on the first question, I argue that cultural evolutionists can get empirical traction on third-way cultural selection by rooting the distinction between replication and reconstruction, two modes of cultural inheritance, in the distinction between System 1 and System 2 cognitive processes. This move suggests that cultural epidemiologists are right in thinking that replication has higher fidelity than reconstruction, and replication processes are not genetic adaptations for culture, but wrong to assume that replication is rare. If replication is not rare, an important requirement for third-way cultural selection, one-shot fidelity , is likely to be met. However, there are other requirements, overlooked by dual-inheritance theorists when they conflate strong (Darwinian) and weak (choice) senses of 'cultural selection', including dumb choices and recurrent fidelity In a second excursion into cognitive science, I argue that these requirements can be met by metacognitive social learning strategies , and trace the origins of these distinctively human cognitive processes to cultural evolution. Like other forms of cultural learning, they are not cognitive instincts but cognitive gadgets.This article is part of the theme issue 'Bridging cultural gaps: interdisciplinary studies in human cultural evolution'. © 2018 The Author(s).
NASA Astrophysics Data System (ADS)
Assadi, Amir H.
2001-11-01
Perceptual geometry is an emerging field of interdisciplinary research whose objectives focus on study of geometry from the perspective of visual perception, and in turn, apply such geometric findings to the ecological study of vision. Perceptual geometry attempts to answer fundamental questions in perception of form and representation of space through synthesis of cognitive and biological theories of visual perception with geometric theories of the physical world. Perception of form and space are among fundamental problems in vision science. In recent cognitive and computational models of human perception, natural scenes are used systematically as preferred visual stimuli. Among key problems in perception of form and space, we have examined perception of geometry of natural surfaces and curves, e.g. as in the observer's environment. Besides a systematic mathematical foundation for a remarkably general framework, the advantages of the Gestalt theory of natural surfaces include a concrete computational approach to simulate or recreate images whose geometric invariants and quantities might be perceived and estimated by an observer. The latter is at the very foundation of understanding the nature of perception of space and form, and the (computer graphics) problem of rendering scenes to visually invoke virtual presence.
Can cognitive science create a cognitive economics?
Chater, Nick
2015-02-01
Cognitive science can intersect with economics in at least three productive ways: by providing richer models of individual behaviour for use in economic analysis; by drawing from economic theory in order to model distributed cognition; and jointly to create more powerful 'rational' models of cognitive processes and social interaction. There is the prospect of moving from behavioural economics to a genuinely cognitive economics. Copyright © 2014. Published by Elsevier B.V.
THE INTERNAL ORGANIZATION OF COMPUTER MODELS OF COGNITIVE BEHAVIOR.
ERIC Educational Resources Information Center
BAKER, FRANK B.
IF COMPUTER PROGRAMS ARE TO SERVE AS USEFUL MODELS OF COGNITIVE BEHAVIOR, THEIR CREATORS MUST FACE THE NEED TO ESTABLISH AN INTERNAL ORGANIZATION FOR THEIR MODEL WHICH IMPLEMENTS THE HIGHER LEVEL COGNITIVE BEHAVIORS ASSOCIATED WITH THE HUMAN CAPACITY FOR SELF-DIRECTION, AUTOCRITICISM, AND ADAPTATION. PRESENT COMPUTER MODELS OF COGNITIVE BEHAVIOR…
Peretz, Chava; Korczyn, Amos D; Shatil, Evelyn; Aharonson, Vered; Birnboim, Smadar; Giladi, Nir
2011-01-01
Many studies have suggested that cognitive training can result in cognitive gains in healthy older adults. We investigated whether personalized computerized cognitive training provides greater benefits than those obtained by playing conventional computer games. This was a randomized double-blind interventional study. Self-referred healthy older adults (n = 155, 68 ± 7 years old) were assigned to either a personalized, computerized cognitive training or to a computer games group. Cognitive performance was assessed at baseline and after 3 months by a neuropsychological assessment battery. Differences in cognitive performance scores between and within groups were evaluated using mixed effects models in 2 approaches: adherence only (AO; n = 121) and intention to treat (ITT; n = 155). Both groups improved in cognitive performance. The improvement in the personalized cognitive training group was significant (p < 0.03, AO and ITT approaches) in all 8 cognitive domains. However, in the computer games group it was significant (p < 0.05) in only 4 (AO) or 6 domains (ITT). In the AO analysis, personalized cognitive training was significantly more effective than playing games in improving visuospatial working memory (p = 0.0001), visuospatial learning (p = 0.0012) and focused attention (p = 0.0019). Personalized, computerized cognitive training appears to be more effective than computer games in improving cognitive performance in healthy older adults. Further studies are needed to evaluate the ecological validity of these findings. Copyright © 2011 S. Karger AG, Basel.
The effect of technology on student science achievement
NASA Astrophysics Data System (ADS)
Hilton, June Kraft
2003-10-01
Prior research indicates that technology has had little effect on raising student achievement. Little empirical research exists, however, studying the effects of technology as a tool to improve student achievement through development of higher order thinking skills. Also, prior studies have not focused on the manner in which technology is being used in the classroom and at home to enhance teaching and learning. Empirical data from a secondary school representative of those in California were analyzed to determine the effects of technology on student science achievement. The quantitative analysis methods for the school data study included a multiple linear path analysis, using final course grade as the ultimate exogenous variable. In addition, empirical data from a nationwide survey on how Americans use the Internet were disaggregated by age and analyzed to determine the relationships between computer and Internet experience and (a) Internet use at home for school assignments and (b) more general computer use at home for school assignments for school age children. Analysis of data collected from the a "A Nation Online" Survey conducted by the United States Census Bureau assessed these relationships via correlations and cross-tabulations. Finally, results from these data analyses were assessed in conjunction with systemic reform efforts from 12 states designed to address improvements in science and mathematics education in light of the Third International Mathematics and Science Survey (TIMSS). Examination of the technology efforts in those states provided a more nuanced understanding of the impact technology has on student achievement. Key findings included evidence that technology training for teachers increased their use of the computer for instruction but students' final science course grade did not improve; school age children across the country did not use the computer at home for such higher-order cognitive activities as graphics and design or spreadsheets/databases; and states whose systemic reform initiatives included a mix of capacity building and alignment to state standards realized improved student achievement on the 2000 NAEP Science Assessment.
Holmes, Emily A; James, Ella L; Kilford, Emma J; Deeprose, Catherine
2010-11-10
Flashbacks (intrusive memories of a traumatic event) are the hallmark feature of Post Traumatic Stress Disorder, however preventative interventions are lacking. Tetris may offer a 'cognitive vaccine' [1] against flashback development after trauma exposure. We previously reported that playing the computer game Tetris soon after viewing traumatic material reduced flashbacks compared to no-task [1]. However, two criticisms need to be addressed for clinical translation: (1) Would all games have this effect via distraction/enjoyment, or might some games even be harmful? (2) Would effects be found if administered several hours post-trauma? Accordingly, we tested Tetris versus an alternative computer game--Pub Quiz--which we hypothesized not to be helpful (Experiments 1 and 2), and extended the intervention interval to 4 hours (Experiment 2). The trauma film paradigm was used as an experimental analog for flashback development in healthy volunteers. In both experiments, participants viewed traumatic film footage of death and injury before completing one of the following: (1) no-task control condition (2) Tetris or (3) Pub Quiz. Flashbacks were monitored for 1 week. Experiment 1: 30 min after the traumatic film, playing Tetris led to a significant reduction in flashbacks compared to no-task control, whereas Pub Quiz led to a significant increase in flashbacks. Experiment 2: 4 hours post-film, playing Tetris led to a significant reduction in flashbacks compared to no-task control, whereas Pub Quiz did not. First, computer games can have differential effects post-trauma, as predicted by a cognitive science formulation of trauma memory. In both Experiments, playing Tetris post-trauma film reduced flashbacks. Pub Quiz did not have this effect, even increasing flashbacks in Experiment 1. Thus not all computer games are beneficial or merely distracting post-trauma - some may be harmful. Second, the beneficial effects of Tetris are retained at 4 hours post-trauma. Clinically, this delivers a feasible time-window to administer a post-trauma "cognitive vaccine".
Cognitive development in a secondary science setting
NASA Astrophysics Data System (ADS)
Endler, Lorna C.; Bond, Trevor
2000-12-01
Observations were made of the progressive change in the cognitive development of 141 students over the course of their secondary education in an Australian private school. Cognitive development was measured in years 8, 10 and 12 using Bond's Logical Orerations Test. Rasch analysis of each of the data sets provided ability estimates for students in the year groups of 1993 (year 8), 1995 (year 10) and 1997 (year 12). Twenty-nine students from the year group of 1993 were tested on all three occasions. We analysed data from these 29 students in order to investigate the children's cognitive development across years 8, 10 and 12. We also examined the influence of the Cognitive Acceleration through Science Education (CASE) Thinking Science program on the cognitive development and scholastic achievement of these students. We found increased mental growth between years 8 and 10 for most students in the Thinking Science cohort, which could not be predicted from their starting levels. There was a significant correlation between cognitive development and the scholastic achievement of these students. Although boys as a group were more advanced in cognitive development than girls in years 8 and 10, no difference was found in the rate of cognitive change based on sex up to year 10. However girls showed cognitive gains across years 10-12 which were not found in boys. The students who were new to the school also showed increased cognitive development in years 11 and 12. Students who had experienced the Thinking Science course were more cognitively developed than students who joined the school after the intervention had taken place. This study supports the claim of Adey and Shayer that there is a relationship between cognitive development and scholastic achievement, even though we used different measures of cognitive development and scholastic achievement.
ERIC Educational Resources Information Center
Ogden, William R.; Brewster, Patricia M.
The purpose of this study was to identify cognitive styles for successful and unsuccessful science students at the secondary level. Additional purposes were to identify common and unique elements in these composite cognitive styles and to substantiate the description of the groups of successful and unsuccessful science students according to the…
How to Teach for Social Justice: Lessons from "Uncle Tom's Cabin" and Cognitive Science
ERIC Educational Resources Information Center
Bracher, Mark
2009-01-01
The author explains how principles of cognitive science can help teachers of literature use texts as a means of increasing students' commitment to social justice. Applying these principles to a particular work, Uncle Tom's Cabin, he calls particular attention to the relationship between cognitive science and literary schemes for building reader…
NASA Astrophysics Data System (ADS)
Skells, Kristin Marie
Extant data was used to consider the association between science anxiety, social cognitive factors and STEM career aspirations of high school freshmen in general science classes. An adapted model based on social cognitive career theory (SCCT) was used to consider these relationships, with science anxiety functioning as a barrier in the model. The study assessed the following research questions: (1) Do social cognitive variables relate in the expected way to STEM career aspirations based on SCCT for ninth graders taking general science classes? (2) Is there an association between science anxiety and outcomes and processes identified in the SCCT model for ninth graders taking general science classes? (3) Does gender moderate these relationships? Results indicated that support was found for many of the central tenants of the SCCT model. Science anxiety was associated with prior achievement, self-efficacy, and science interest, although it did not relate directly to STEM career goals. Gender was found to moderate only the relationship between prior achievement and science self-efficacy.
Computer-Based Cognitive Training for Executive Functions after Stroke: A Systematic Review
van de Ven, Renate M.; Murre, Jaap M. J.; Veltman, Dick J.; Schmand, Ben A.
2016-01-01
Background: Stroke commonly results in cognitive impairments in working memory, attention, and executive function, which may be restored with appropriate training programs. Our aim was to systematically review the evidence for computer-based cognitive training of executive dysfunctions. Methods: Studies were included if they concerned adults who had suffered stroke or other types of acquired brain injury, if the intervention was computer training of executive functions, and if the outcome was related to executive functioning. We searched in MEDLINE, PsycINFO, Web of Science, and The Cochrane Library. Study quality was evaluated based on the CONSORT Statement. Treatment effect was evaluated based on differences compared to pre-treatment and/or to a control group. Results: Twenty studies were included. Two were randomized controlled trials that used an active control group. The other studies included multiple baselines, a passive control group, or were uncontrolled. Improvements were observed in tasks similar to the training (near transfer) and in tasks dissimilar to the training (far transfer). However, these effects were not larger in trained than in active control groups. Two studies evaluated neural effects and found changes in both functional and structural connectivity. Most studies suffered from methodological limitations (e.g., lack of an active control group and no adjustment for multiple testing) hampering differentiation of training effects from spontaneous recovery, retest effects, and placebo effects. Conclusions: The positive findings of most studies, including neural changes, warrant continuation of research in this field, but only if its methodological limitations are addressed. PMID:27148007
Conceptual Knowledge Acquisition in Biomedicine: A Methodological Review
Payne, Philip R.O.; Mendonça, Eneida A.; Johnson, Stephen B.; Starren, Justin B.
2007-01-01
The use of conceptual knowledge collections or structures within the biomedical domain is pervasive, spanning a variety of applications including controlled terminologies, semantic networks, ontologies, and database schemas. A number of theoretical constructs and practical methods or techniques support the development and evaluation of conceptual knowledge collections. This review will provide an overview of the current state of knowledge concerning conceptual knowledge acquisition, drawing from multiple contributing academic disciplines such as biomedicine, computer science, cognitive science, education, linguistics, semiotics, and psychology. In addition, multiple taxonomic approaches to the description and selection of conceptual knowledge acquisition and evaluation techniques will be proposed in order to partially address the apparent fragmentation of the current literature concerning this domain. PMID:17482521
NASA Astrophysics Data System (ADS)
Blancke, Stefaan; De Smedt, Johan; De Cruz, Helen; Boudry, Maarten; Braeckman, Johan
2012-08-01
This paper discusses the relationship between religion and science education in the light of the cognitive sciences. We challenge the popular view that science and religion are compatible, a view that suggests that learning and understanding evolutionary theory has no effect on students' religious beliefs and vice versa. We develop a cognitive perspective on how students manage to reconcile evolutionary theory with their religious beliefs. We underwrite the claim developed by cognitive scientists and anthropologists that religion is natural because it taps into people's intuitive understanding of the natural world which is constrained by essentialist, teleological and intentional biases. After contrasting the naturalness of religion with the unnaturalness of science, we discuss the difficulties cognitive and developmental scientists have identified in learning and accepting evolutionary theory. We indicate how religious beliefs impede students' understanding and acceptance of evolutionary theory. We explore a number of options available to students for reconciling an informed understanding of evolutionary theory with their religious beliefs. To conclude, we discuss the implications of our account for science and biology teachers.
What does semantic tiling of the cortex tell us about semantics?
Barsalou, Lawrence W
2017-10-01
Recent use of voxel-wise modeling in cognitive neuroscience suggests that semantic maps tile the cortex. Although this impressive research establishes distributed cortical areas active during the conceptual processing that underlies semantics, it tells us little about the nature of this processing. While mapping concepts between Marr's computational and implementation levels to support neural encoding and decoding, this approach ignores Marr's algorithmic level, central for understanding the mechanisms that implement cognition, in general, and conceptual processing, in particular. Following decades of research in cognitive science and neuroscience, what do we know so far about the representation and processing mechanisms that implement conceptual abilities? Most basically, much is known about the mechanisms associated with: (1) feature and frame representations, (2) grounded, abstract, and linguistic representations, (3) knowledge-based inference, (4) concept composition, and (5) conceptual flexibility. Rather than explaining these fundamental representation and processing mechanisms, semantic tiles simply provide a trace of their activity over a relatively short time period within a specific learning context. Establishing the mechanisms that implement conceptual processing in the brain will require more than mapping it to cortical (and sub-cortical) activity, with process models from cognitive science likely to play central roles in specifying the intervening mechanisms. More generally, neuroscience will not achieve its basic goals until it establishes algorithmic-level mechanisms that contribute essential explanations to how the brain works, going beyond simply establishing the brain areas that respond to various task conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.
From computers to cultivation: reconceptualizing evolutionary psychology
Barrett, Louise; Pollet, Thomas V.; Stulp, Gert
2014-01-01
Does evolutionary theorizing have a role in psychology? This is a more contentious issue than one might imagine, given that, as evolved creatures, the answer must surely be yes. The contested nature of evolutionary psychology lies not in our status as evolved beings, but in the extent to which evolutionary ideas add value to studies of human behavior, and the rigor with which these ideas are tested. This, in turn, is linked to the framework in which particular evolutionary ideas are situated. While the framing of the current research topic places the brain-as-computer metaphor in opposition to evolutionary psychology, the most prominent school of thought in this field (born out of cognitive psychology, and often known as the Santa Barbara school) is entirely wedded to the computational theory of mind as an explanatory framework. Its unique aspect is to argue that the mind consists of a large number of functionally specialized (i.e., domain-specific) computational mechanisms, or modules (the massive modularity hypothesis). Far from offering an alternative to, or an improvement on, the current perspective, we argue that evolutionary psychology is a mainstream computational theory, and that its arguments for domain-specificity often rest on shaky premises. We then go on to suggest that the various forms of e-cognition (i.e., embodied, embedded, enactive) represent a true alternative to standard computational approaches, with an emphasis on “cognitive integration” or the “extended mind hypothesis” in particular. We feel this offers the most promise for human psychology because it incorporates the social and historical processes that are crucial to human “mind-making” within an evolutionarily informed framework. In addition to linking to other research areas in psychology, this approach is more likely to form productive links to other disciplines within the social sciences, not least by encouraging a healthy pluralism in approach. PMID:25161633
1998-08-07
cognitive flexibility theory and generative learning theory which focus primarily on the individual student’s cognitive development , collaborative... develop "Handling Transfusion Hazards," a computer program based upon cognitive flexibility theory principles. The Program: Handling Transfusion Hazards...computer program was developed according to cognitive flexibility theory principles. A generative version was then developed by embedding
The Effects of Cognitive Conflict Management on Cognitive Development and Science Achievement
ERIC Educational Resources Information Center
Budiman, Zainol Badli; Halim, Lilia; Mohd Meerah, Subahan; Osman, Kamisah
2014-01-01
Three teaching methods were compared in this study, namely a Cognitive Conflict Management Module (CCM) that is infused into Cognitive Acceleration through Science Education (CASE), (Module A) CASE without CCM (Module B) and a conventional teaching method. This study employed a pre- and post-test quasi-experimental design using non-equivalent…
Knowledge and Regulation of Cognition in College Science Students
ERIC Educational Resources Information Center
Roshanaei, Mehrnaz
2014-01-01
The research focused on three issues in college science students: whether there was empirical support for the two factor (knowledge of cognition and regulation of cognition) view of metacognition, whether the two factors were related to each other, and whether either of the factors was related to empirical measures of cognitive and metacognitive…
ERIC Educational Resources Information Center
Nunez, Rafael
2012-01-01
"The Journal of the Learning Sciences" has devoted this special issue to the study of embodied cognition (as it applies to mathematics), a topic that for several decades has gained attention in the cognitive sciences and in mathematics education, in particular. In this commentary, the author aims to address crucial questions in embodied…
Data Mining and Knowledge Discover - IBM Cognitive Alternatives for NASA KSC
NASA Technical Reports Server (NTRS)
Velez, Victor Hugo
2016-01-01
Skillful tools in cognitive computing to transform industries have been found favorable and profitable for different Directorates at NASA KSC. In this study is shown how cognitive computing systems can be useful for NASA when computers are trained in the same way as humans are to gain knowledge over time. Increasing knowledge through senses, learning and a summation of events is how the applications created by the firm IBM empower the artificial intelligence in a cognitive computing system. NASA has explored and applied for the last decades the artificial intelligence approach specifically with cognitive computing in few projects adopting similar models proposed by IBM Watson. However, the usage of semantic technologies by the dedicated business unit developed by IBM leads these cognitive computing applications to outperform the functionality of the inner tools and present outstanding analysis to facilitate the decision making for managers and leads in a management information system.
Exploring the Structure of Spatial Representations
Madl, Tamas; Franklin, Stan; Chen, Ke; Trappl, Robert; Montaldi, Daniela
2016-01-01
It has been suggested that the map-like representations that support human spatial memory are fragmented into sub-maps with local reference frames, rather than being unitary and global. However, the principles underlying the structure of these ‘cognitive maps’ are not well understood. We propose that the structure of the representations of navigation space arises from clustering within individual psychological spaces, i.e. from a process that groups together objects that are close in these spaces. Building on the ideas of representational geometry and similarity-based representations in cognitive science, we formulate methods for learning dissimilarity functions (metrics) characterizing participants’ psychological spaces. We show that these learned metrics, together with a probabilistic model of clustering based on the Bayesian cognition paradigm, allow prediction of participants’ cognitive map structures in advance. Apart from insights into spatial representation learning in human cognition, these methods could facilitate novel computational tools capable of using human-like spatial concepts. We also compare several features influencing spatial memory structure, including spatial distance, visual similarity and functional similarity, and report strong correlations between these dimensions and the grouping probability in participants’ spatial representations, providing further support for clustering in spatial memory. PMID:27347681
Parallel photonic information processing at gigabyte per second data rates using transient states
NASA Astrophysics Data System (ADS)
Brunner, Daniel; Soriano, Miguel C.; Mirasso, Claudio R.; Fischer, Ingo
2013-01-01
The increasing demands on information processing require novel computational concepts and true parallelism. Nevertheless, hardware realizations of unconventional computing approaches never exceeded a marginal existence. While the application of optics in super-computing receives reawakened interest, new concepts, partly neuro-inspired, are being considered and developed. Here we experimentally demonstrate the potential of a simple photonic architecture to process information at unprecedented data rates, implementing a learning-based approach. A semiconductor laser subject to delayed self-feedback and optical data injection is employed to solve computationally hard tasks. We demonstrate simultaneous spoken digit and speaker recognition and chaotic time-series prediction at data rates beyond 1Gbyte/s. We identify all digits with very low classification errors and perform chaotic time-series prediction with 10% error. Our approach bridges the areas of photonic information processing, cognitive and information science.
2010-06-01
DATES COVEREDAPR 2009 – JAN 2010 (From - To) APR 2009 – JAN 2010 4. TITLE AND SUBTITLE EMERGING NEUROMORPHIC COMPUTING ARCHITECTURES AND ENABLING...14. ABSTRACT The highly cross-disciplinary emerging field of neuromorphic computing architectures for cognitive information processing applications...belief systems, software, computer engineering, etc. In our effort to develop cognitive systems atop a neuromorphic computing architecture, we explored
An Expert System toward Buiding An Earth Science Knowledge Graph
NASA Astrophysics Data System (ADS)
Zhang, J.; Duan, X.; Ramachandran, R.; Lee, T. J.; Bao, Q.; Gatlin, P. N.; Maskey, M.
2017-12-01
In this ongoing work, we aim to build foundations of Cognitive Computing for Earth Science research. The goal of our project is to develop an end-to-end automated methodology for incrementally constructing Knowledge Graphs for Earth Science (KG4ES). These knowledge graphs can then serve as the foundational components for building cognitive systems in Earth science, enabling researchers to uncover new patterns and hypotheses that are virtually impossible to identify today. In addition, this research focuses on developing mining algorithms needed to exploit these constructed knowledge graphs. As such, these graphs will free knowledge from publications that are generated in a very linear, deterministic manner, and structure knowledge in a way that users can both interact and connect with relevant pieces of information. Our major contributions are two-fold. First, we have developed an end-to-end methodology for constructing Knowledge Graphs for Earth Science (KG4ES) using existing corpus of journal papers and reports. One of the key challenges in any machine learning, especially deep learning applications, is the need for robust and large training datasets. We have developed techniques capable of automatically retraining models and incrementally building and updating KG4ES, based on ever evolving training data. We also adopt the evaluation instrument based on common research methodologies used in Earth science research, especially in Atmospheric Science. Second, we have developed an algorithm to infer new knowledge that can exploit the constructed KG4ES. In more detail, we have developed a network prediction algorithm aiming to explore and predict possible new connections in the KG4ES and aid in new knowledge discovery.
Cognitive Science and Science Education.
ERIC Educational Resources Information Center
Carey, Susan
1986-01-01
The premise behind the cognitive approach to teaching is that understanding results when new learning is integrated with existing knowledge. But the goal of science instruction is to replace existing ideas with new theories. Current research in science education seeks to resolve these conflicting instructional approaches. (Author/VM)
Cognitive apprenticeship in health sciences education: a qualitative review.
Lyons, Kayley; McLaughlin, Jacqueline E; Khanova, Julia; Roth, Mary T
2017-08-01
Cognitive apprenticeship theory emphasizes the process of making expert thinking "visible" to students and fostering the cognitive and meta-cognitive processes required for expertise. The purpose of this review was to evaluate the use of cognitive apprenticeship theory with the primary aim of understanding how and to what extent the theory has been applied to the design, implementation, and analysis of education in the health sciences. The initial search yielded 149 articles, with 45 excluded because they contained the term "cognitive apprenticeship" only in reference list. The remaining 104 articles were categorized using a theory talk coding scheme. An in depth qualitative synthesis and review was conducted for the 26 articles falling into the major theory talk category. Application of cognitive apprenticeship theory tended to focus on the methods dimension (e.g., coaching, mentoring, scaffolding), with some consideration for the content and sociology dimensions. Cognitive apprenticeship was applied in various disciplines (e.g., nursing, medicine, veterinary) and educational settings (e.g., clinical, simulations, online). Health sciences education researchers often used cognitive apprenticeship to inform instructional design and instrument development. Major recommendations from the literature included consideration for contextual influences, providing faculty development, and expanding application of the theory to improve instructional design and student outcomes. This body of research provides critical insight into cognitive apprenticeship theory and extends our understanding of how to develop expert thinking in health sciences students. New research directions should apply the theory into additional aspects of health sciences educational research, such as classroom learning and interprofessional education.
BioSIGHT: Interactive Visualization Modules for Science Education
NASA Technical Reports Server (NTRS)
Wong, Wee Ling
1998-01-01
Redefining science education to harness emerging integrated media technologies with innovative pedagogical goals represents a unique challenge. The Integrated Media Systems Center (IMSC) is the only engineering research center in the area of multimedia and creative technologies sponsored by the National Science Foundation. The research program at IMSC is focused on developing advanced technologies that address human-computer interfaces, database management, and high-speed network capabilities. The BioSIGHT project at is a demonstration technology project in the area of education that seeks to address how such emerging multimedia technologies can make an impact on science education. The scope of this project will help solidify NASA's commitment for the development of innovative educational resources that promotes science literacy for our students and the general population as well. These issues must be addressed as NASA marches toward the goal of enabling human space exploration that requires an understanding of life sciences in space. The IMSC BioSIGHT lab was established with the purpose of developing a novel methodology that will map a high school biology curriculum into a series of interactive visualization modules that can be easily incorporated into a space biology curriculum. Fundamental concepts in general biology must be mastered in order to allow a better understanding and application for space biology. Interactive visualization is a powerful component that can capture the students' imagination, facilitate their assimilation of complex ideas, and help them develop integrated views of biology. These modules will augment the role of the teacher and will establish the value of student-centered interactivity, both in an individual setting as well as in a collaborative learning environment. Students will be able to interact with the content material, explore new challenges, and perform virtual laboratory simulations. The BioSIGHT effort is truly cross-disciplinary in nature and requires expertise from many areas including Biology, Computer Science Electrical Engineering, Education, and the Cognitive Sciences. The BioSIGHT team includes a scientific illustrator, educational software designer, computer programmers as well as IMSC graduate and undergraduate students.
Fiore, Stephen M.; Wiltshire, Travis J.
2016-01-01
In this paper we advance team theory by describing how cognition occurs across the distribution of members and the artifacts and technology that support their efforts. We draw from complementary theorizing coming out of cognitive engineering and cognitive science that views forms of cognition as external and extended and integrate this with theorizing on macrocognition in teams. Two frameworks are described that provide the groundwork for advancing theory and aid in the development of more precise measures for understanding team cognition via focus on artifacts and the technologies supporting their development and use. This includes distinctions between teamwork and taskwork and the notion of general and specific competencies from the organizational sciences along with the concepts of offloading and scaffolding from the cognitive sciences. This paper contributes to the team cognition literature along multiple lines. First, it aids theory development by synthesizing a broad set of perspectives on the varied forms of cognition emerging in complex collaborative contexts. Second, it supports research by providing diagnostic guidelines to study how artifacts are related to team cognition. Finally, it supports information systems designers by more precisely describing how to conceptualize team-supporting technology and artifacts. As such, it provides a means to more richly understand process and performance as it occurs within sociotechnical systems. Our overarching objective is to show how team cognition can both be more clearly conceptualized and more precisely measured by integrating theory from cognitive engineering and the cognitive and organizational sciences. PMID:27774074
Fiore, Stephen M; Wiltshire, Travis J
2016-01-01
In this paper we advance team theory by describing how cognition occurs across the distribution of members and the artifacts and technology that support their efforts. We draw from complementary theorizing coming out of cognitive engineering and cognitive science that views forms of cognition as external and extended and integrate this with theorizing on macrocognition in teams. Two frameworks are described that provide the groundwork for advancing theory and aid in the development of more precise measures for understanding team cognition via focus on artifacts and the technologies supporting their development and use. This includes distinctions between teamwork and taskwork and the notion of general and specific competencies from the organizational sciences along with the concepts of offloading and scaffolding from the cognitive sciences. This paper contributes to the team cognition literature along multiple lines. First, it aids theory development by synthesizing a broad set of perspectives on the varied forms of cognition emerging in complex collaborative contexts. Second, it supports research by providing diagnostic guidelines to study how artifacts are related to team cognition. Finally, it supports information systems designers by more precisely describing how to conceptualize team-supporting technology and artifacts. As such, it provides a means to more richly understand process and performance as it occurs within sociotechnical systems. Our overarching objective is to show how team cognition can both be more clearly conceptualized and more precisely measured by integrating theory from cognitive engineering and the cognitive and organizational sciences.
ERIC Educational Resources Information Center
Manoj, T. I.; Devanathan, S.
2010-01-01
This research study is the report of an experiment conducted to find out the effects of web based inquiry science environment on cognitive outcomes in Biological science in correlation to Emotional intelligence. Web based inquiry science environment (WISE) provides a platform for creating inquiry-based science projects for students to work…
Neurobiological roots of language in primate audition: common computational properties.
Bornkessel-Schlesewsky, Ina; Schlesewsky, Matthias; Small, Steven L; Rauschecker, Josef P
2015-03-01
Here, we present a new perspective on an old question: how does the neurobiology of human language relate to brain systems in nonhuman primates? We argue that higher-order language combinatorics, including sentence and discourse processing, can be situated in a unified, cross-species dorsal-ventral streams architecture for higher auditory processing, and that the functions of the dorsal and ventral streams in higher-order language processing can be grounded in their respective computational properties in primate audition. This view challenges an assumption, common in the cognitive sciences, that a nonhuman primate model forms an inherently inadequate basis for modeling higher-level language functions. Copyright © 2014 Elsevier Ltd. All rights reserved.
Human white matter and knowledge representation
2018-01-01
Understanding how knowledge is represented in the human brain is a fundamental challenge in neuroscience. To date, most of the work on this topic has focused on knowledge representation in cortical areas and debated whether knowledge is represented in a distributed or localized fashion. Fang and colleagues provide evidence that brain connections and the white matter supporting such connections might play a significant role. The work opens new avenues of investigation, breaking through disciplinary boundaries across network neuroscience, computational neuroscience, cognitive science, and classical lesion studies. PMID:29698391
Human white matter and knowledge representation.
Pestilli, Franco
2018-04-01
Understanding how knowledge is represented in the human brain is a fundamental challenge in neuroscience. To date, most of the work on this topic has focused on knowledge representation in cortical areas and debated whether knowledge is represented in a distributed or localized fashion. Fang and colleagues provide evidence that brain connections and the white matter supporting such connections might play a significant role. The work opens new avenues of investigation, breaking through disciplinary boundaries across network neuroscience, computational neuroscience, cognitive science, and classical lesion studies.
The first Italian doctorate (PhD Course) in Physics Education Research
NASA Astrophysics Data System (ADS)
Michelini, Marisa; Santi, Lorenzo
2008-05-01
The first PhD Italian course in Physics Education Research in Udine aims to qualify young researchers and teachers coming from all the Italian groups of research in the field. It becomes a context for developing research projects carried out following parallel research lines on: Teaching/Learning paths for didactic innovation, cognitive research, ICT for strategies to overcome conceptual knots in physics; E-learning for personalization; d) Computer on-line experiments and modelling; e) Teacher formation and training; f) Informal learning in science.
The Implications of Cognitive Psychology for Computer-Based Learning Tools.
ERIC Educational Resources Information Center
Kozma, Robert B.
1987-01-01
Defines cognitive computer tools as software programs that use the control capabilities of computers to amplify, extend, or enhance human cognition; suggests seven ways in which computers can aid learning; and describes the "Learning Tool," a software package for the Apple Macintosh microcomputer that is designed to aid learning of…
NASA Astrophysics Data System (ADS)
Hong, Jon-Chao; Hwang, Ming-Yueh; Tai, Kai-Hsin; Tsai, Chi-Ruei
2017-12-01
Based on the cognitive-affective theory, the present study designed a science inquiry learning model, predict-observe-explain (POE), and implemented it in an app called "WhyWhy" to examine the effectiveness of students' science inquiry learning practice. To understand how POE can affect the cognitive-affective learning process, as well as the learning progress, a pretest and a posttest were given to 152 grade 5 elementary school students. The students practiced WhyWhy during six sessions over 6 weeks, and data related to interest in learning science (ILS), cognitive anxiety (CA), and extraneous cognitive load (ECL) were collected and analyzed through confirmatory factor analysis with structure equation modeling. The results showed that students with high ILS have low CA and ECL. In addition, the results also indicated that students with a high level of self-confidence enhancement showed significant improvement in the posttest. The implications of this study suggest that by using technology-enhanced science learning, the POE model is a practical approach to motivate students to learn.
Bridging views in cinema: a review of the art and science of view integration.
Levin, Daniel T; Baker, Lewis J
2017-09-01
Recently, there has been a surge of interest in the relationship between film and cognitive science. This is reflected in a new science of cinema that can help us both to understand this art form, and to produce new insights about cognition and perception. In this review, we begin by describing how the initial development of cinema involved close observation of audience response. This allowed filmmakers to develop an informal theory of visual cognition that helped them to isolate and creatively recombine fundamental elements of visual experience. We review research exploring naturalistic forms of visual perception and cognition that have opened the door to a productive convergence between the dynamic visual art of cinema and science of visual cognition that can enrich both. In particular, we discuss how parallel understandings of view integration in cinema and in cognitive science have been converging to support a new understanding of meaningful visual experience. WIREs Cogn Sci 2017, 8:e1436. doi: 10.1002/wcs.1436 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.
Garrido, Gemma; Barrios, Maite; Penadés, Rafael; Enríquez, Maria; Garolera, Maite; Aragay, Núria; Pajares, Marta; Vallès, Vicenç; Delgado, Luis; Alberni, Joan; Faixa, Carlota; Vendrell, Josep M
2013-11-01
Quality of life (QoL) is an important outcome in the treatment of schizophrenia. Cognitive deficits have an impact on functional outcomes. Cognitive remediation therapy is emerging as a psychological intervention that targets cognitive impairment, but the effect of computer-assisted cognitive remediation on neuropsychology and social functioning and wellbeing remains unclear. The aim of the current study is to investigate the neurocognitive outcomes of computer-assisted cognitive remediation (CACR) therapy in a sample of schizophrenia patients, and to measure the quality of life and self-esteem as secondary outcomes. Sixty-seven people with schizophrenia were randomly assigned to computer-assisted cognitive remediation or an active control condition. The main outcomes were neuropsychological measures and secondary outcomes (self-esteem and quality of life). Measurements were recorded at baseline and post-treatment. The CACR therapy group improved in speed of processing, working memory and reasoning and problem-solving cognitive domains. QoL and self-esteem measures also showed significant improvements over time in this group. Computer-assisted cognitive remediation therapy for people with schizophrenia achieved improvements in neuropsychological performance and in QoL and self-esteem measurements. © 2013 Elsevier B.V. All rights reserved.
ERIC Educational Resources Information Center
Nunez, Rafael E.
This paper gives a brief introduction to a discipline called the cognitive science of mathematics. The theoretical background of the arguments is based on embodied cognition and findings in cognitive linguistics. It discusses Mathematical Idea Analysis, a set of techniques for studying implicit structures in mathematics. Particular attention is…
Aicardi, Christine
2014-03-01
Taking up the view that semi-institutional gatherings such as clubs, societies, research schools, have been instrumental in creating sheltered spaces from which many a 20th-century project-driven interdisciplinary research programme could develop and become established within the institutions of science, the paper explores the history of one such gathering from its inception in the early 1980s into the 2000s, the Helmholtz Club, which brought together scientists from such various research fields as neuroanatomy, neurophysiology, psychophysics, computer science and engineering, who all had an interest in the study of the visual system and of higher cognitive functions relying on visual perception such as visual consciousness. It argues that British molecular biologist turned South Californian neuroscientist Francis Crick had an early and lasting influence over the Helmholtz Club of which he was a founding pillar, and that from its inception, the club served as a constitutive element in his long-term plans for a neuroscience of vision and of cognition. Further, it argues that in this role, the Helmholtz Club served many purposes, the primary of which was to be a social forum for interdisciplinary discussion, where 'discussion' was not mere talk but was imbued with an epistemic value and as such, carefully cultivated. Finally, it questions what counts as 'doing science' and in turn, definitions of success and failure-and provides some material evidence towards re-appraising the successfulness of Crick's contribution to the neurosciences. Copyright © 2013 The Author. Published by Elsevier Ltd.. All rights reserved.
Wang, Ming-Te; Ye, Feifei; Degol, Jessica Lauren
2017-08-01
Career aspirations in science, technology, engineering, and mathematics (STEM) are formulated in adolescence, making the high school years a critical time period for identifying the cognitive and motivational factors that increase the likelihood of future STEM employment. While past research has mainly focused on absolute cognitive ability levels in math and verbal domains, the current study tested whether relative cognitive strengths and interests in math, science, and verbal domains in high school were more accurate predictors of STEM career decisions. Data were drawn from a national longitudinal study in the United States (N = 1762; 48 % female; the first wave during ninth grade and the last wave at age 33). Results revealed that in the high-verbal/high-math/high-science ability group, individuals with higher science task values and lower orientation toward altruism were more likely to select STEM occupations. In the low-verbal/moderate-math/moderate-science ability group, individuals with higher math ability and higher math task values were more likely to select STEM occupations. The findings suggest that youth with asymmetrical cognitive ability profiles are more likely to select careers that utilize their cognitive strengths rather than their weaknesses, while symmetrical cognitive ability profiles may grant youth more flexibility in their options, allowing their interests and values to guide their career decisions.
Acquiring neural signals for developing a perception and cognition model
NASA Astrophysics Data System (ADS)
Li, Wei; Li, Yunyi; Chen, Genshe; Shen, Dan; Blasch, Erik; Pham, Khanh; Lynch, Robert
2012-06-01
The understanding of how humans process information, determine salience, and combine seemingly unrelated information is essential to automated processing of large amounts of information that is partially relevant, or of unknown relevance. Recent neurological science research in human perception, and in information science regarding contextbased modeling, provides us with a theoretical basis for using a bottom-up approach for automating the management of large amounts of information in ways directly useful for human operators. However, integration of human intelligence into a game theoretic framework for dynamic and adaptive decision support needs a perception and cognition model. For the purpose of cognitive modeling, we present a brain-computer-interface (BCI) based humanoid robot system to acquire brainwaves during human mental activities of imagining a humanoid robot-walking behavior. We use the neural signals to investigate relationships between complex humanoid robot behaviors and human mental activities for developing the perception and cognition model. The BCI system consists of a data acquisition unit with an electroencephalograph (EEG), a humanoid robot, and a charge couple CCD camera. An EEG electrode cup acquires brainwaves from the skin surface on scalp. The humanoid robot has 20 degrees of freedom (DOFs); 12 DOFs located on hips, knees, and ankles for humanoid robot walking, 6 DOFs on shoulders and arms for arms motion, and 2 DOFs for head yaw and pitch motion. The CCD camera takes video clips of the human subject's hand postures to identify mental activities that are correlated to the robot-walking behaviors. We use the neural signals to investigate relationships between complex humanoid robot behaviors and human mental activities for developing the perception and cognition model.
Discovering Psychological Principles by Mining Naturally Occurring Data Sets.
Goldstone, Robert L; Lupyan, Gary
2016-07-01
The very expertise with which psychologists wield their tools for achieving laboratory control may have had the unwelcome effect of blinding psychologists to the possibilities of discovering principles of behavior without conducting experiments. When creatively interrogated, a diverse range of large, real-world data sets provides powerful diagnostic tools for revealing principles of human judgment, perception, categorization, decision-making, language use, inference, problem solving, and representation. Examples of these data sets include patterns of website links, dictionaries, logs of group interactions, collections of images and image tags, text corpora, history of financial transactions, trends in twitter tag usage and propagation, patents, consumer product sales, performance in high-stakes sporting events, dialect maps, and scientific citations. The goal of this issue is to present some exemplary case studies of mining naturally existing data sets to reveal important principles and phenomena in cognitive science, and to discuss some of the underlying issues involved with conducting traditional experiments, analyses of naturally occurring data, computational modeling, and the synthesis of all three methods. Copyright © 2016 Cognitive Science Society, Inc.
Wild, Katherine V.; Mattek, Nora; Maxwell, Shoshana A.; Dodge, Hiroko H.; Jimison, Holly B.; Kaye, Jeffrey A.
2012-01-01
Background This study examines differences in computer related self-efficacy and anxiety in subgroups of older adults, and changes in those measures following exposure to a systematic training program and subsequent computer use. Methods Participants were volunteers in the Intelligent Systems for Assessment of Aging Changes Study (ISAAC) carried out by the Oregon Center for Aging and Technology. Participants were administered two questionnaires prior to training and again one year later, related to computer self-efficacy and anxiety. Continuous recording of computer use was also assessed for a subset of participants. Results Baseline comparisons by gender, age, education, living arrangement, and computer proficiency, but not cognitive status, yielded significant differences in confidence and anxiety related to specific aspects of computer use. At one-year follow-up, participants reported less anxiety and greater confidence. However, the benefits of training and exposure varied by group and task. Comparisons based on cognitive status showed that the cognitively intact participants benefited more from training and/or experience with computers than did participants with Mild Cognitive Impairment (MCI), who after one year continued to report less confidence and more anxiety regarding certain aspects of computer use. Conclusion After one year of consistent computer use, cognitively intact participants in this study reported reduced levels of anxiety and increased self-confidence in their ability to perform specific computer tasks. Participants with MCI at baseline were less likely to demonstrate increased efficacy or confidence than their cognitively intact counterparts. PMID:23102124
ERIC Educational Resources Information Center
Smart, Julie B.; Marshall, Jeff C.
2013-01-01
Classroom discourse can affect various aspects of student learning in science. The present study examines interactions between classroom discourse, specifically teacher questioning, and related student cognitive engagement in middle school science. Observations were conducted throughout the school year in 10 middle school science classrooms using…
Computer mouse movement patterns: A potential marker of mild cognitive impairment.
Seelye, Adriana; Hagler, Stuart; Mattek, Nora; Howieson, Diane B; Wild, Katherine; Dodge, Hiroko H; Kaye, Jeffrey A
2015-12-01
Subtle changes in cognitively demanding activities occur in MCI but are difficult to assess with conventional methods. In an exploratory study, we examined whether patterns of computer mouse movements obtained from routine home computer use discriminated between older adults with and without MCI. Participants were 42 cognitively intact and 20 older adults with MCI enrolled in a longitudinal study of in-home monitoring technologies. Mouse pointer movement variables were computed during one week of routine home computer use using algorithms that identified and characterized mouse movements within each computer use session. MCI was associated with making significantly fewer total mouse moves ( p <.01), and making mouse movements that were more variable, less efficient, and with longer pauses between movements ( p <.05). Mouse movement measures were significantly associated with several cognitive domains ( p 's<.01-.05). Remotely monitored computer mouse movement patterns are a potential early marker of real-world cognitive changes in MCI.
Cognitive abilities of health and art college students a pilot study.
AlAbdulwahab, Sami S; Kachanathu, Shaji John; AlKhamees, Abdullah K
2016-05-01
[Purpose] The selection of a college major is a struggle that high school students undergo every year; however, there is a dearth of studies examining the role of cognitive ability tests as a tool for determining the aptitude of prospective students. Hence, the purpose of this study was to assess cognitive ability differences among students. [Subjects and Methods] A convenience sample of 60 college students (30 health science and 30 art students) with a mean age of 19 ± 1.6 years, voluntarily participated in this study. Cognitive ability was assessed using the self-administered Cognitive Assessment of Minnesota (CAM) scale under the supervision of a researcher. [Results] The findings indicated that there was a significant cognitive ability difference between health science and art students, especially in the cognitive components of knowledge, calculation, and thinking. However, the difference in the social cognitive component of both the health science and art students was not significant. [Conclusion] The results indicate that the health science students' cognitive abilities were better than those of the art students. This finding implies that it is important for high school graduates to undertake a cognitive ability assessment prior to choosing a subject major. Hence, it is recommended that cognitive scales should be included as an aptitude assessment tool for the decision-makers and prospective students to determine an appropriate career, since it might reduce the percentage of university drop-out ratio.
The Effects of Item Format and Cognitive Domain on Students' Science Performance in TIMSS 2011
NASA Astrophysics Data System (ADS)
Liou, Pey-Yan; Bulut, Okan
2017-12-01
The purpose of this study was to examine eighth-grade students' science performance in terms of two test design components, item format, and cognitive domain. The portion of Taiwanese data came from the 2011 administration of the Trends in International Mathematics and Science Study (TIMSS), one of the major international large-scale assessments in science. The item difficulty analysis was initially applied to show the proportion of correct items. A regression-based cumulative link mixed modeling (CLMM) approach was further utilized to estimate the impact of item format, cognitive domain, and their interaction on the students' science scores. The results of the proportion-correct statistics showed that constructed-response items were more difficult than multiple-choice items, and that the reasoning cognitive domain items were more difficult compared to the items in the applying and knowing domains. In terms of the CLMM results, students tended to obtain higher scores when answering constructed-response items as well as items in the applying cognitive domain. When the two predictors and the interaction term were included together, the directions and magnitudes of the predictors on student science performance changed substantially. Plausible explanations for the complex nature of the effects of the two test-design predictors on student science performance are discussed. The results provide practical, empirical-based evidence for test developers, teachers, and stakeholders to be aware of the differential function of item format, cognitive domain, and their interaction in students' science performance.
Research Institute for Advanced Computer Science: Annual Report October 1998 through September 1999
NASA Technical Reports Server (NTRS)
Leiner, Barry M.; Gross, Anthony R. (Technical Monitor)
1999-01-01
The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center (ARC). It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. ARC has been designated NASA's Center of Excellence in Information Technology. In this capacity, ARC is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA ARC and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth. (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, and visiting scientist programs, designed to encourage and facilitate collaboration between the university and NASA information technology research communities.
Research Institute for Advanced Computer Science
NASA Technical Reports Server (NTRS)
Gross, Anthony R. (Technical Monitor); Leiner, Barry M.
2000-01-01
The Research Institute for Advanced Computer Science (RIACS) carries out basic research and technology development in computer science, in support of the National Aeronautics and Space Administration's missions. RIACS is located at the NASA Ames Research Center. It currently operates under a multiple year grant/cooperative agreement that began on October 1, 1997 and is up for renewal in the year 2002. Ames has been designated NASA's Center of Excellence in Information Technology. In this capacity, Ames is charged with the responsibility to build an Information Technology Research Program that is preeminent within NASA. RIACS serves as a bridge between NASA Ames and the academic community, and RIACS scientists and visitors work in close collaboration with NASA scientists. RIACS has the additional goal of broadening the base of researchers in these areas of importance to the nation's space and aeronautics enterprises. RIACS research focuses on the three cornerstones of information technology research necessary to meet the future challenges of NASA missions: (1) Automated Reasoning for Autonomous Systems. Techniques are being developed enabling spacecraft that will be self-guiding and self-correcting to the extent that they will require little or no human intervention. Such craft will be equipped to independently solve problems as they arise, and fulfill their missions with minimum direction from Earth; (2) Human-Centered Computing. Many NASA missions require synergy between humans and computers, with sophisticated computational aids amplifying human cognitive and perceptual abilities; (3) High Performance Computing and Networking. Advances in the performance of computing and networking continue to have major impact on a variety of NASA endeavors, ranging from modeling and simulation to data analysis of large datasets to collaborative engineering, planning and execution. In addition, RIACS collaborates with NASA scientists to apply information technology research to a variety of NASA application domains. RIACS also engages in other activities, such as workshops, seminars, and visiting scientist programs, designed to encourage and facilitate collaboration between the university and NASA information technology research communities.
The Interdisciplinarity of Collaborations in Cognitive Science.
Bergmann, Till; Dale, Rick; Sattari, Negin; Heit, Evan; Bhat, Harish S
2017-07-01
We introduce a new metric for interdisciplinarity, based on co-author publication history. A published article that has co-authors with quite different publication histories can be deemed relatively "interdisciplinary," in that the article reflects a convergence of previous research in distinct sets of publication outlets. In recent work, we have shown that this interdisciplinarity metric can predict citations. Here, we show that the journal Cognitive Science tends to contain collaborations that are relatively high on this interdisciplinarity metric, at about the 80th percentile of all journals across both social and natural sciences. Following on Goldstone and Leydesdorff (2006), we describe how scientometric tools provide a valuable means of assessing the role of cognitive science in broader scientific work, and also as a tool to investigate teamwork and distributed cognition. We describe how data-driven metrics of this kind may facilitate this exploration without relying upon rapidly changing discipline and topic keywords associated with publications. Copyright © 2016 Cognitive Science Society, Inc.
NASA Astrophysics Data System (ADS)
Zaleski, Diana Janet
2011-12-01
The National Board for Professional Teaching Standards claims to identify effective educators through their certification process. However, research concerning National Board Certified Teachers (NBCT) is inconclusive. The purpose of this study was to examine the direct and indirect effects of NBCT on the cognitive engagement of high school science students. Multilevel mediation modeling was used to examine the direct and indirect effects of teacher certification on students' cognitive engagement in science and whether students' expectancies for success and perceptions of task value mediate these effects. Students of NBCT were found to be more cognitively engaged in science than students of non-NBCT; however, students' expectancies for success and perceptions of task value did not mediate this relationship. In addition, students with more positive expectancies for success and perceptions of task value were more cognitively engaged in science. These findings support the proposition that the National Board certification process at least identifies effective educators.
Cognitive Approaches for Medicine in Cloud Computing.
Ogiela, Urszula; Takizawa, Makoto; Ogiela, Lidia
2018-03-03
This paper will present the application potential of the cognitive approach to data interpretation, with special reference to medical areas. The possibilities of using the meaning approach to data description and analysis will be proposed for data analysis tasks in Cloud Computing. The methods of cognitive data management in Cloud Computing are aimed to support the processes of protecting data against unauthorised takeover and they serve to enhance the data management processes. The accomplishment of the proposed tasks will be the definition of algorithms for the execution of meaning data interpretation processes in safe Cloud Computing. • We proposed a cognitive methods for data description. • Proposed a techniques for secure data in Cloud Computing. • Application of cognitive approaches for medicine was described.
The cognitive science of visual-spatial displays: implications for design.
Hegarty, Mary
2011-07-01
This paper reviews cognitive science perspectives on the design of visual-spatial displays and introduces the other papers in this topic. It begins by classifying different types of visual-spatial displays, followed by a discussion of ways in which visual-spatial displays augment cognition and an overview of the perceptual and cognitive processes involved in using displays. The paper then argues for the importance of cognitive science methods to the design of visual displays and reviews some of the main principles of display design that have emerged from these approaches to date. Cognitive scientists have had good success in characterizing the performance of well-defined tasks with relatively simple visual displays, but many challenges remain in understanding the use of complex displays for ill-defined tasks. Current research exemplified by the papers in this topic extends empirical approaches to new displays and domains, informs the development of general principles of graphic design, and addresses current challenges in display design raised by the recent explosion in availability of complex data sets and new technologies for visualizing and interacting with these data. Copyright © 2011 Cognitive Science Society, Inc.
ERIC Educational Resources Information Center
Posner, Michael I.
This paper reviews the aspects of cognitive science that relate best to using electrical and magnetic recording to understand the function of brain systems. It outlines a framework for relating cognitive activities of daily life (typing, reading) to underlying neural systems. The framework uses five levels of analysis: task, elementary operations,…
Understanding human visual systems and its impact on our intelligent instruments
NASA Astrophysics Data System (ADS)
Strojnik Scholl, Marija; Páez, Gonzalo; Scholl, Michelle K.
2013-09-01
We review the evolution of machine vision and comment on the cross-fertilization from the neural sciences onto flourishing fields of neural processing, parallel processing, and associative memory in optical sciences and computing. Then we examine how the intensive efforts in mapping the human brain have been influenced by concepts in computer sciences, control theory, and electronic circuits. We discuss two neural paths that employ the input from the vision sense to determine the navigational options and object recognition. They are ventral temporal pathway for object recognition (what?) and dorsal parietal pathway for navigation (where?), respectively. We describe the reflexive and conscious decision centers in cerebral cortex involved with visual attention and gaze control. Interestingly, these require return path though the midbrain for ocular muscle control. We find that the cognitive psychologists currently study human brain employing low-spatial-resolution fMRI with temporal response on the order of a second. In recent years, the life scientists have concentrated on insect brains to study neural processes. We discuss how reflexive and conscious gaze-control decisions are made in the frontal eye field and inferior parietal lobe, constituting the fronto-parietal attention network. We note that ethical and experiential learnings impact our conscious decisions.
ERIC Educational Resources Information Center
Blancke, Stefaan; De Smedt, Johan; De Cruz, Helen; Boudry, Maarten; Braeckman, Johan
2012-01-01
This paper discusses the relationship between religion and science education in the light of the cognitive sciences. We challenge the popular view that science and religion are compatible, a view that suggests that learning and understanding evolutionary theory has no effect on students' religious beliefs and vice versa. We develop a cognitive…
Embodied Cognition and Curriculum Construction
ERIC Educational Resources Information Center
Wang, Mei-qian; Zheng, Xu-dong
2018-01-01
The disembodiment of cognitive science has resulted in curricula with disembodied concepts and practice. The emergence of the embodied cognitive science provoked public reflections on the nature of the curriculum. This has elevated the body from the "peripheral" position to the "central" position, acting as the subject in…
The semantic distance task: Quantifying semantic distance with semantic network path length.
Kenett, Yoed N; Levi, Effi; Anaki, David; Faust, Miriam
2017-09-01
Semantic distance is a determining factor in cognitive processes, such as semantic priming, operating upon semantic memory. The main computational approach to compute semantic distance is through latent semantic analysis (LSA). However, objections have been raised against this approach, mainly in its failure at predicting semantic priming. We propose a novel approach to computing semantic distance, based on network science methodology. Path length in a semantic network represents the amount of steps needed to traverse from 1 word in the network to the other. We examine whether path length can be used as a measure of semantic distance, by investigating how path length affect performance in a semantic relatedness judgment task and recall from memory. Our results show a differential effect on performance: Up to 4 steps separating between word-pairs, participants exhibit an increase in reaction time (RT) and decrease in the percentage of word-pairs judged as related. From 4 steps onward, participants exhibit a significant decrease in RT and the word-pairs are dominantly judged as unrelated. Furthermore, we show that as path length between word-pairs increases, success in free- and cued-recall decreases. Finally, we demonstrate how our measure outperforms computational methods measuring semantic distance (LSA and positive pointwise mutual information) in predicting participants RT and subjective judgments of semantic strength. Thus, we provide a computational alternative to computing semantic distance. Furthermore, this approach addresses key issues in cognitive theory, namely the breadth of the spreading activation process and the effect of semantic distance on memory retrieval. (PsycINFO Database Record (c) 2017 APA, all rights reserved).
NASA Astrophysics Data System (ADS)
Siegel, Z.; Siegel, Edward Carl-Ludwig
2011-03-01
RANDOMNESS of Numbers cognitive-semantics DEFINITION VIA Cognition QUERY: WHAT???, NOT HOW?) VS. computer-``science" mindLESS number-crunching (Harrel-Sipser-...) algorithmics Goldreich "PSEUDO-randomness"[Not.AMS(02)] mea-culpa is ONLY via MAXWELL-BOLTZMANN CLASSICAL-STATISTICS(NOT FDQS!!!) "hot-plasma" REPULSION VERSUS Newcomb(1881)-Weyl(1914;1916)-Benford(1938) "NeWBe" logarithmic-law digit-CLUMPING/ CLUSTERING NON-Randomness simple Siegel[AMS Joint.Mtg.(02)-Abs. # 973-60-124] algebraic-inversion to THE QUANTUM and ONLY BEQS preferentially SEQUENTIALLY lower-DIGITS CLUMPING/CLUSTERING with d = 0 BEC, is ONLY VIA Siegel-Baez FUZZYICS=CATEGORYICS (SON OF TRIZ)/"Category-Semantics"(C-S), latter intersection/union of Lawvere(1964)-Siegel(1964)] category-theory (matrix: MORPHISMS V FUNCTORS) "+" cognitive-semantics'' (matrix: ANTONYMS V SYNONYMS) yields Siegel-Baez FUZZYICS=CATEGORYICS/C-S tabular list-format matrix truth-table analytics: MBCS RANDOMNESS TRUTH/EMET!!!
The Episodic Nature of Experience: A Dynamical Systems Analysis.
Sreekumar, Vishnu; Dennis, Simon; Doxas, Isidoros
2017-07-01
Context is an important construct in many domains of cognition, including learning, memory, and emotion. We used dynamical systems methods to demonstrate the episodic nature of experience by showing a natural separation between the scales over which within-context and between-context relationships operate. To do this, we represented an individual's emails extending over about 5 years in a high-dimensional semantic space and computed the dimensionalities of the subspaces occupied by these emails. Personal discourse has a two-scaled geometry with smaller within-context dimensionalities than between-context dimensionalities. Prior studies have shown that reading experience (Doxas, Dennis, & Oliver, 2010) and visual experience (Sreekumar, Dennis, Doxas, Zhuang, & Belkin, 2014) have a similar two-scaled structure. Furthermore, the recurrence plot of the emails revealed that experience is predictable and hierarchical, supporting the constructs of some influential theories of memory. The results demonstrate that experience is not scale-free and provide an important target for accounts of how experience shapes cognition. Copyright © 2016 Cognitive Science Society, Inc.
Conceptual Metaphor and Embodied Cognition in Science Learning: Introduction to Special Issue
ERIC Educational Resources Information Center
Amin, Tamer G.; Jeppsson, Fredrik; Haglund, Jesper
2015-01-01
This special issue of "International Journal of Science Education" is based on the theme "Conceptual Metaphor and Embodied Cognition in Science Learning." The idea for this issue grew out of a symposium organized on this topic at the conference of the European Science Education Research Association (ESERA) in September 2013.…
Mathematical representations in science: a cognitive-historical case history.
Tweney, Ryan D
2009-10-01
The important role of mathematical representations in scientific thinking has received little attention from cognitive scientists. This study argues that neglect of this issue is unwarranted, given existing cognitive theories and laws, together with promising results from the cognitive historical analysis of several important scientists. In particular, while the mathematical wizardry of James Clerk Maxwell differed dramatically from the experimental approaches favored by Michael Faraday, Maxwell himself recognized Faraday as "in reality a mathematician of a very high order," and his own work as in some respects a re-representation of Faraday's field theory in analytic terms. The implications of the similarities and differences between the two figures open new perspectives on the cognitive role of mathematics as a learned mode of representation in science. Copyright © 2009 Cognitive Science Society, Inc.
ERIC Educational Resources Information Center
Nir-Gal, Ofra; Klein, Pnina S.
2004-01-01
This study was designed to examine the effect of different kinds of adult mediation on the cognitive performance of young children who used computers. The study sample included 150 kindergarten children aged 5-6. The findings indicate that children who engaged in adult-mediated computer activity improved the level of their cognitive performance on…
Wild, Katherine V; Mattek, Nora C; Maxwell, Shoshana A; Dodge, Hiroko H; Jimison, Holly B; Kaye, Jeffrey A
2012-11-01
This study examines differences in computer-related self-efficacy and anxiety in subgroups of older adults, and changes in those measures after exposure to a systematic training program and subsequent computer use. Participants were volunteers in the Intelligent Systems for Assessment of Aging Changes study (ISAAC) carried out by the Oregon Center for Aging and Technology. Participants were administered two questionnaires before training and again 1 year later, which were related to computer self-efficacy and anxiety. Continuous recording of computer use was also assessed for a subset of participants. Baseline comparisons by sex, age, education, living arrangement, and computer proficiency, but not cognitive status, yielded significant differences in confidence and anxiety related to specific aspects of computer use. At 1-year follow-up, participants reported less anxiety and greater confidence. However, the benefits of training and exposure varied by group and task. Comparisons based on cognitive status showed that the cognitively intact participants benefited more from training and/or experience with computers than did participants with mild cognitive impairment (MCI), who after 1 year continued to report less confidence and more anxiety regarding certain aspects of computer use. After 1 year of consistent computer use, cognitively intact participants in this study reported reduced levels of anxiety and increased self-confidence in their ability to perform specific computer tasks. Participants with MCI at baseline were less likely to demonstrate increased efficacy or confidence than their cognitively intact counterparts. Copyright © 2012 The Alzheimer's Association. Published by Elsevier Inc. All rights reserved.
Alien Mindscapes—A Perspective on the Search for Extraterrestrial Intelligence
NASA Astrophysics Data System (ADS)
Cabrol, Nathalie A.
2016-09-01
Advances in planetary and space sciences, astrobiology, and life and cognitive sciences, combined with developments in communication theory, bioneural computing, machine learning, and big data analysis, create new opportunities to explore the probabilistic nature of alien life. Brought together in a multidisciplinary approach, they have the potential to support an integrated and expanded Search for Extraterrestrial Intelligence (SETI1), a search that includes looking for life as we do not know it. This approach will augment the odds of detecting a signal by broadening our understanding of the evolutionary and systemic components in the search for extraterrestrial intelligence (ETI), provide more targets for radio and optical SETI, and identify new ways of decoding and coding messages using universal markers.
Effects of Computer Cognitive Training on Depression in Cognitively Impaired Seniors
ERIC Educational Resources Information Center
Allen, Nara L.
2016-01-01
The aim of the present study was to investigate the effects of a computer cognitive training program on depression levels in older mildly cognitive impaired individuals. Peterson et al. (1999), defines mild cognitive impairment (MCI) as a transitional stage in which an individual's memory deteriorates and his likelihood of developing Alzheimer's…
Hoping for more: How cognitive science has and hasn't been helpful to the OCD clinician.
Ouimet, Allison J; Ashbaugh, Andrea R; Radomsky, Adam S
2018-04-12
Cognitive-behavioural models of obsessive-compulsive disorder (OCD) stemmed from knowledge acquired from cognitive science. Researchers continue to apply basic cognitive-affective science methods to understanding OCD, with the overarching goal of improving and refining evidence-based treatments. However, the degree to which such research has contributed to this goal is unclear. We reviewed OCD research in the general areas that comprise basic cognitive science, and evaluated the degree to which it has contributed to our understanding of the development, maintenance, and treatment of OCD. We focused on studies that either compared people with and without OCD and/or used experimental psychopathology methods with human participants, and attempted to resolve some of the conflicting theories related to the importance of cognitive deficits vs. cognitive biases. Overall, we observed equivocal findings for deficits in perception, attention, memory, and executive functioning. Moreover, many so-called deficits were moderated and/or explained by OCD-relevant beliefs, highlighting the role of confidence in cognitive processes as integral to our understanding of OCD. We discussed these findings in terms of cognitive measurement, cognitive-behavioural models, and clinical applicability, and made recommendations for future research that may offer innovation and insight helpful to clinicians working to improve the symptoms and lives of people with OCD. Copyright © 2018 Elsevier Ltd. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Slepoy, Alexander; Mitchell, Scott A.; Backus, George A.
2008-09-01
Sandia National Laboratories is investing in projects that aim to develop computational modeling and simulation applications that explore human cognitive and social phenomena. While some of these modeling and simulation projects are explicitly research oriented, others are intended to support or provide insight for people involved in high consequence decision-making. This raises the issue of how to evaluate computational modeling and simulation applications in both research and applied settings where human behavior is the focus of the model: when is a simulation 'good enough' for the goals its designers want to achieve? In this report, we discuss two years' worthmore » of review and assessment of the ASC program's approach to computational model verification and validation, uncertainty quantification, and decision making. We present a framework that extends the principles of the ASC approach into the area of computational social and cognitive modeling and simulation. In doing so, we argue that the potential for evaluation is a function of how the modeling and simulation software will be used in a particular setting. In making this argument, we move from strict, engineering and physics oriented approaches to V&V to a broader project of model evaluation, which asserts that the systematic, rigorous, and transparent accumulation of evidence about a model's performance under conditions of uncertainty is a reasonable and necessary goal for model evaluation, regardless of discipline. How to achieve the accumulation of evidence in areas outside physics and engineering is a significant research challenge, but one that requires addressing as modeling and simulation tools move out of research laboratories and into the hands of decision makers. This report provides an assessment of our thinking on ASC Verification and Validation, and argues for further extending V&V research in the physical and engineering sciences toward a broader program of model evaluation in situations of high consequence decision-making.« less
ERIC Educational Resources Information Center
Machamer, Peter; Douglas, Heather
1999-01-01
Criticizes Hugh Lacey's separation of cognitive values and social values in discussions of the nature of science. Claims that attempting to distinguish between cognitive and social ignores crucial complexities in the development and use of knowledge. Proposes that the proper distinction be between legitimate and illegitimate reasons in science as…
Penicillin for Education: How Cognitive Science Can Contribute to Education.
ERIC Educational Resources Information Center
Bruer, John T.
1995-01-01
Education can benefit from knowledge derived from cognitive and developmental psychology. Family demographics have actually improved between 1970 and 90 and so have NAEP scores. Three innovative programs demonstrating cognitive science applications include the Teaching Number Sense elementary math program, reciprocal teaching (reading strategy),…
The potential of using quantum theory to build models of cognition.
Wang, Zheng; Busemeyer, Jerome R; Atmanspacher, Harald; Pothos, Emmanuel M
2013-10-01
Quantum cognition research applies abstract, mathematical principles of quantum theory to inquiries in cognitive science. It differs fundamentally from alternative speculations about quantum brain processes. This topic presents new developments within this research program. In the introduction to this topic, we try to answer three questions: Why apply quantum concepts to human cognition? How is quantum cognitive modeling different from traditional cognitive modeling? What cognitive processes have been modeled using a quantum account? In addition, a brief introduction to quantum probability theory and a concrete example is provided to illustrate how a quantum cognitive model can be developed to explain paradoxical empirical findings in psychological literature. © 2013 Cognitive Science Society, Inc.
Mill and mental phenomena: critical contributions to a science of cognition.
Bistricky, Steven L
2013-06-01
Attempts to define cognition preceded John Stuart Mill's life and continue to this day. John Stuart Mill envisioned a science of mental phenomena informed by associationism, empirical introspection, and neurophysiology, and he advanced specific ideas that still influence modern conceptions of cognition. The present article briefly reviews Mill's personal history and the times in which he lived, and it traces the evolution of ideas that have run through him to contemporary cognitive concepts. The article also highlights contemporary problems in defining cognition and supports specific criteria regarding what constitutes cognition.
Lyons, Bayard E; Austin, Daniel; Seelye, Adriana; Petersen, Johanna; Yeargers, Jonathan; Riley, Thomas; Sharma, Nicole; Mattek, Nora; Wild, Katherine; Dodge, Hiroko; Kaye, Jeffrey A
2015-01-01
Traditionally, assessment of functional and cognitive status of individuals with dementia occurs in brief clinic visits during which time clinicians extract a snapshot of recent changes in individuals' health. Conventionally, this is done using various clinical assessment tools applied at the point of care and relies on patients' and caregivers' ability to accurately recall daily activity and trends in personal health. These practices suffer from the infrequency and generally short durations of visits. Since 2004, researchers at the Oregon Center for Aging and Technology (ORCATECH) at the Oregon Health and Science University have been working on developing technologies to transform this model. ORCATECH researchers have developed a system of continuous in-home monitoring using pervasive computing technologies that make it possible to more accurately track activities and behaviors and measure relevant intra-individual changes. We have installed a system of strategically placed sensors in over 480 homes and have been collecting data for up to 8 years. Using this continuous in-home monitoring system, ORCATECH researchers have collected data on multiple behaviors such as gait and mobility, sleep and activity patterns, medication adherence, and computer use. Patterns of intra-individual variation detected in each of these areas are used to predict outcomes such as low mood, loneliness, and cognitive function. These methods have the potential to improve the quality of patient health data and in turn patient care especially related to cognitive decline. Furthermore, the continuous real-world nature of the data may improve the efficiency and ecological validity of clinical intervention studies.
Lyons, Bayard E.; Austin, Daniel; Seelye, Adriana; Petersen, Johanna; Yeargers, Jonathan; Riley, Thomas; Sharma, Nicole; Mattek, Nora; Wild, Katherine; Dodge, Hiroko; Kaye, Jeffrey A.
2015-01-01
Traditionally, assessment of functional and cognitive status of individuals with dementia occurs in brief clinic visits during which time clinicians extract a snapshot of recent changes in individuals’ health. Conventionally, this is done using various clinical assessment tools applied at the point of care and relies on patients’ and caregivers’ ability to accurately recall daily activity and trends in personal health. These practices suffer from the infrequency and generally short durations of visits. Since 2004, researchers at the Oregon Center for Aging and Technology (ORCATECH) at the Oregon Health and Science University have been working on developing technologies to transform this model. ORCATECH researchers have developed a system of continuous in-home monitoring using pervasive computing technologies that make it possible to more accurately track activities and behaviors and measure relevant intra-individual changes. We have installed a system of strategically placed sensors in over 480 homes and have been collecting data for up to 8 years. Using this continuous in-home monitoring system, ORCATECH researchers have collected data on multiple behaviors such as gait and mobility, sleep and activity patterns, medication adherence, and computer use. Patterns of intra-individual variation detected in each of these areas are used to predict outcomes such as low mood, loneliness, and cognitive function. These methods have the potential to improve the quality of patient health data and in turn patient care especially related to cognitive decline. Furthermore, the continuous real-world nature of the data may improve the efficiency and ecological validity of clinical intervention studies. PMID:26113819
Computational Investigations of Multiword Chunks in Language Learning.
McCauley, Stewart M; Christiansen, Morten H
2017-07-01
Second-language learners rarely arrive at native proficiency in a number of linguistic domains, including morphological and syntactic processing. Previous approaches to understanding the different outcomes of first- versus second-language learning have focused on cognitive and neural factors. In contrast, we explore the possibility that children and adults may rely on different linguistic units throughout the course of language learning, with specific focus on the granularity of those units. Following recent psycholinguistic evidence for the role of multiword chunks in online language processing, we explore the hypothesis that children rely more heavily on multiword units in language learning than do adults learning a second language. To this end, we take an initial step toward using large-scale, corpus-based computational modeling as a tool for exploring the granularity of speakers' linguistic units. Employing a computational model of language learning, the Chunk-Based Learner, we compare the usefulness of chunk-based knowledge in accounting for the speech of second-language learners versus children and adults speaking their first language. Our findings suggest that while multiword units are likely to play a role in second-language learning, adults may learn less useful chunks, rely on them to a lesser extent, and arrive at them through different means than children learning a first language. Copyright © 2017 Cognitive Science Society, Inc.
Rational approximations to rational models: alternative algorithms for category learning.
Sanborn, Adam N; Griffiths, Thomas L; Navarro, Daniel J
2010-10-01
Rational models of cognition typically consider the abstract computational problems posed by the environment, assuming that people are capable of optimally solving those problems. This differs from more traditional formal models of cognition, which focus on the psychological processes responsible for behavior. A basic challenge for rational models is thus explaining how optimal solutions can be approximated by psychological processes. We outline a general strategy for answering this question, namely to explore the psychological plausibility of approximation algorithms developed in computer science and statistics. In particular, we argue that Monte Carlo methods provide a source of rational process models that connect optimal solutions to psychological processes. We support this argument through a detailed example, applying this approach to Anderson's (1990, 1991) rational model of categorization (RMC), which involves a particularly challenging computational problem. Drawing on a connection between the RMC and ideas from nonparametric Bayesian statistics, we propose 2 alternative algorithms for approximate inference in this model. The algorithms we consider include Gibbs sampling, a procedure appropriate when all stimuli are presented simultaneously, and particle filters, which sequentially approximate the posterior distribution with a small number of samples that are updated as new data become available. Applying these algorithms to several existing datasets shows that a particle filter with a single particle provides a good description of human inferences.
ERIC Educational Resources Information Center
Batchelor, J.; And Others
1988-01-01
The study compared computer assisted cognitive retraining of 47 patients with severe closed head injury with comparable noncomputerized treatment techniques. Results on neuropsychological tests did not support the increased effectiveness of the computer assisted cognitive therapy. (DB)
NASA Astrophysics Data System (ADS)
Okanoya, Kazuo
2014-09-01
The comparative computational approach of Fitch [1] attempts to renew the classical David Marr paradigm of computation, algorithm, and implementation, by introducing evolutionary view of the relationship between neural architecture and cognition. This comparative evolutionary view provides constraints useful in narrowing down the problem space for both cognition and neural mechanisms. I will provide two examples from our own studies that reinforce and extend Fitch's proposal.
Unobtrusive monitoring of computer interactions to detect cognitive status in elders.
Jimison, Holly; Pavel, Misha; McKanna, James; Pavel, Jesse
2004-09-01
The U.S. has experienced a rapid growth in the use of computers by elders. E-mail, Web browsing, and computer games are among the most common routine activities for this group of users. In this paper, we describe techniques for unobtrusively monitoring naturally occurring computer interactions to detect sustained changes in cognitive performance. Researchers have demonstrated the importance of the early detection of cognitive decline. Users over the age of 75 are at risk for medically related cognitive problems and confusion, and early detection allows for more effective clinical intervention. In this paper, we present algorithms for inferring a user's cognitive performance using monitoring data from computer games and psychomotor measurements associated with keyboard entry and mouse movement. The inferences are then used to classify significant performance changes, and additionally, to adapt computer interfaces with tailored hints and assistance when needed. These methods were tested in a group of elders in a residential facility.
Cognitive architectures: choreographing the dance of mental operations with the task environment.
Gray, Wayne D
2008-06-01
In this article, I present the ideas and trends that have given rise to the use of cognitive architectures in human factors and provide a cognitive engineering-oriented taxonomy of these architectures and a snapshot of their use for cognitive engineering. Architectures of cognition have had a long history in human factors but a brief past. The long history entails a 50-year preamble, whereas the explosion of work in the current decade reflects the brief past. Understanding this history is key to understanding the current and future prospects for applying cognitive science theory to human factors practice. The review defines three formative eras in cognitive engineering research: the 1950s, 1980s, and now. In the first era, the fledging fields of cognitive science and human factors emphasized characteristics of the dancer the limited capacity or bounded rationality view of the mind, and the ballroom, the task environment. The second era emphasized the dance (i.e., the dynamic interaction between mental operations and task environment). The third era has seen the rise of cognitive architectures as tools for choreographing the dance of mental operations within the complex environments posed by human factors practice. Hybrid architectures present the best vector for introducing cognitive science theories into a renewed engineering-based human factors. The taxonomy provided in this article may provide guidance on when and whether to apply a cognitive science or a hybrid architecture to a human factors issue.
Haptic augmentation of science instruction: Does touch matter?
NASA Astrophysics Data System (ADS)
Jones, M. Gail; Minogue, James; Tretter, Thomas R.; Negishi, Atsuko; Taylor, Russell
2006-01-01
This study investigated the impact of haptic augmentation of a science inquiry program on students' learning about viruses and nanoscale science. The study assessed how the addition of different types of haptic feedback (active touch and kinesthetic feedback) combined with computer visualizations influenced middle and high school students' experiences. The influences of a PHANToM (a sophisticated haptic desktop device), a Sidewinder (a haptic gaming joystick), and a mouse (no haptic feedback) interface were compared. The levels of engagement in the instruction and students' attitudes about the instructional program were assessed using a combination of constructed response and Likert scale items. Potential cognitive differences were examined through an analysis of spontaneously generated analogies that appeared during student discourse. Results showed that the addition of haptic feedback from the haptic-gaming joystick and the PHANToM provided a more immersive learning environment that not only made the instruction more engaging but may also influence the way in which the students construct their understandings about abstract science concepts.
NASA Astrophysics Data System (ADS)
Hutson, Matthew
2018-05-01
In their adaptability, young children demonstrate common sense, a kind of intelligence that, so far, computer scientists have struggled to reproduce. Gary Marcus, a developmental cognitive scientist at New York University in New York City, believes the field of artificial intelligence (AI) would do well to learn lessons from young thinkers. Researchers in machine learning argue that computers trained on mountains of data can learn just about anything—including common sense—with few, if any, programmed rules. But Marcus says computer scientists are ignoring decades of work in the cognitive sciences and developmental psychology showing that humans have innate abilities—programmed instincts that appear at birth or in early childhood—that help us think abstractly and flexibly. He believes AI researchers ought to include such instincts in their programs. Yet many computer scientists, riding high on the successes of machine learning, are eagerly exploring the limits of what a naïve AI can do. Computer scientists appreciate simplicity and have an aversion to debugging complex code. Furthermore, big companies such as Facebook and Google are pushing AI in this direction. These companies are most interested in narrowly defined, near-term problems, such as web search and facial recognition, in which blank-slate AI systems can be trained on vast data sets and work remarkably well. But in the longer term, computer scientists expect AIs to take on much tougher tasks that require flexibility and common sense. They want to create chatbots that explain the news, autonomous taxis that can handle chaotic city traffic, and robots that nurse the elderly. Some computer scientists are already trying. Such efforts, researchers hope, will result in AIs that sit somewhere between pure machine learning and pure instinct. They will boot up following some embedded rules, but will also learn as they go.
ERIC Educational Resources Information Center
Liu, Yi-Lin; Liang, Chaoyun
2014-01-01
Using science majors as an example, we analyzed how generative cognition, organizational culture, and personality traits affect student imagination, and examined the mediating effects of generative cognition and organizational culture. A total of 473 undergraduates enrolled in physical, chemical, mathematical, and biological science programs…
The Relation between Cognitive and Metacognitive Strategic Processing during a Science Simulation
ERIC Educational Resources Information Center
Dinsmore, Daniel L.; Zoellner, Brian P.
2018-01-01
Background: This investigation was designed to uncover the relations between students' cognitive and metacognitive strategies used during a complex climate simulation. While cognitive strategy use during science inquiry has been studied, the factors related to this strategy use, such as concurrent metacognition, prior knowledge, and prior…
ERIC Educational Resources Information Center
Taconis, Ruurd; de Putter-Smits, Lesley G. M.; Henry, Steven; den Brok, Perry J.; Beijaard, Douwe
2010-01-01
Forming a science-oriented identity is considered a process underlying both interest and achievement in science education. A questionnaire is developed for describing "identities as learners" and evaluating their science orientedness. The instrument (k = 65) focuses on cognitive aspects. An internal coherence of .88 was found. Five…
Social Cognitive Predictors of Mexican American High School Students' Math/Science Career Goals
ERIC Educational Resources Information Center
Garriott, Patton O.; Raque-Bogdan, Trisha L.; Zoma, Lorrine; Mackie-Hernandez, Dylan; Lavin, Kelly
2017-01-01
This study tested a social cognitive model of math/science career goals in a sample (N = 258) of Mexican American high school students. Familism and proximal family supports for math/science careers were examined as predictors of math/science: performance accomplishments, self-efficacy, interests, and goals. Results showed that the hypothesized…
PERFORMANCE OF A COMPUTER-BASED ASSESSMENT OF COGNITIVE FUNCTION MEASURES IN TWO COHORTS OF SENIORS
Espeland, Mark A.; Katula, Jeffrey A.; Rushing, Julia; Kramer, Arthur F.; Jennings, Janine M.; Sink, Kaycee M.; Nadkarni, Neelesh K.; Reid, Kieran F.; Castro, Cynthia M.; Church, Timothy; Kerwin, Diana R.; Williamson, Jeff D.; Marottoli, Richard A.; Rushing, Scott; Marsiske, Michael; Rapp, Stephen R.
2013-01-01
Background Computer-administered assessment of cognitive function is being increasingly incorporated in clinical trials, however its performance in these settings has not been systematically evaluated. Design The Seniors Health and Activity Research Program (SHARP) pilot trial (N=73) developed a computer-based tool for assessing memory performance and executive functioning. The Lifestyle Interventions and Independence for Seniors (LIFE) investigators incorporated this battery in a full scale multicenter clinical trial (N=1635). We describe relationships that test scores have with those from interviewer-administered cognitive function tests and risk factors for cognitive deficits and describe performance measures (completeness, intra-class correlations). Results Computer-based assessments of cognitive function had consistent relationships across the pilot and full scale trial cohorts with interviewer-administered assessments of cognitive function, age, and a measure of physical function. In the LIFE cohort, their external validity was further demonstrated by associations with other risk factors for cognitive dysfunction: education, hypertension, diabetes, and physical function. Acceptable levels of data completeness (>83%) were achieved on all computer-based measures, however rates of missing data were higher among older participants (odds ratio=1.06 for each additional year; p<0.001) and those who reported no current computer use (odds ratio=2.71; p<0.001). Intra-class correlations among clinics were at least as low (ICC≤0.013) as for interviewer measures (ICC≤0.023), reflecting good standardization. All cognitive measures loaded onto the first principal component (global cognitive function), which accounted for 40% of the overall variance. Conclusion Our results support the use of computer-based tools for assessing cognitive function in multicenter clinical trials of older individuals. PMID:23589390
Metacognition: computation, biology and function
Fleming, Stephen M.; Dolan, Raymond J.; Frith, Christopher D.
2012-01-01
Many complex systems maintain a self-referential check and balance. In animals, such reflective monitoring and control processes have been grouped under the rubric of metacognition. In this introductory article to a Theme Issue on metacognition, we review recent and rapidly progressing developments from neuroscience, cognitive psychology, computer science and philosophy of mind. While each of these areas is represented in detail by individual contributions to the volume, we take this opportunity to draw links between disciplines, and highlight areas where further integration is needed. Specifically, we cover the definition, measurement, neurobiology and possible functions of metacognition, and assess the relationship between metacognition and consciousness. We propose a framework in which level of representation, order of behaviour and access consciousness are orthogonal dimensions of the conceptual landscape. PMID:22492746
Prerequisites for Computer-Aided Cognitive Rehabilitation.
ERIC Educational Resources Information Center
Legrand, Colette
1989-01-01
This paper describes computer-aided cognitive rehabilitation for mentally deficient persons. It lists motor, cognitive, emotional, and educational prerequisites to such rehabilitation and states advantages and disadvantages in using the prerequisites. (JDD)
Designing for deeper learning in a blended computer science course for middle school students
NASA Astrophysics Data System (ADS)
Grover, Shuchi; Pea, Roy; Cooper, Stephen
2015-04-01
The focus of this research was to create and test an introductory computer science course for middle school. Titled "Foundations for Advancing Computational Thinking" (FACT), the course aims to prepare and motivate middle school learners for future engagement with algorithmic problem solving. FACT was also piloted as a seven-week course on Stanford's OpenEdX MOOC platform for blended in-class learning. Unique aspects of FACT include balanced pedagogical designs that address the cognitive, interpersonal, and intrapersonal aspects of "deeper learning"; a focus on pedagogical strategies for mediating and assessing for transfer from block-based to text-based programming; curricular materials for remedying misperceptions of computing; and "systems of assessments" (including formative and summative quizzes and tests, directed as well as open-ended programming assignments, and a transfer test) to get a comprehensive picture of students' deeper computational learning. Empirical investigations, accomplished over two iterations of a design-based research effort with students (aged 11-14 years) in a public school, sought to examine student understanding of algorithmic constructs, and how well students transferred this learning from Scratch to text-based languages. Changes in student perceptions of computing as a discipline were measured. Results and mixed-method analyses revealed that students in both studies (1) achieved substantial learning gains in algorithmic thinking skills, (2) were able to transfer their learning from Scratch to a text-based programming context, and (3) achieved significant growth toward a more mature understanding of computing as a discipline. Factor analyses of prior computing experience, multivariate regression analyses, and qualitative analyses of student projects and artifact-based interviews were conducted to better understand the factors affecting learning outcomes. Prior computing experiences (as measured by a pretest) and math ability were found to be strong predictors of learning outcomes.
Review of Research on the Cognitive Effects of Computer-Assisted Learning.
ERIC Educational Resources Information Center
Mandinach, E.; And Others
This review of the research on the cognitive effects of computer-assisted instruction begins with an overview of the ACCCEL (Assessing Cognitive Consequences of Computer Environments for Learning) research program at the University of California at Berkeley, which consists of several interrelated studies examining the acquisition of such higher…
NASA Astrophysics Data System (ADS)
Brier, Soren
1998-07-01
The ability of systems to be anticipatory seems to be intricate connected with the ability to observe and to cognate by reducing complexity through signification. The semantic capacity of living systems, the cognitive ability to assign meaning to differences perturbating the system's self-organization, seems to be the prerequisite for the phenomenon of communication, language and consciousness. In cybernetics Bateson developed the idea that information is a difference that makes a difference and second order cybernetics developed the concept of organisms as self-organized and self-produced systems (autopoietic) as the prerequisite of life and cognition. The cognitive ability seems to be qualitative different from what so far is computable on any known machine although parts of different aspects of the process can be partly simulated in AI, neutral network and AL. In semiotics the fundamental process of cognition and communication is called semiosis or signification and C. S. Peirce created a special triadic, objective idealistic, pragmatic and evolutionary philosophy to be able to give a fruitful description of the process and its relation to logic and the concept of natural law. Both second order cybernetics and semiotics sees information and meaning as something produced by individual organisms through structural couplings to the environments or other individuals through historical drift and further developed in social communication. Luhmann points out that social communication also only functions through structural couplings which he calls generalized media such as science, art, power, love and money. Peirce talks of the semiotic net as a triadic view of meanings developing through history and in animals through evolution. In accordance with this Wittgenstein points out that signification is created in language games developed in specific life forms. Life forms are the things we do in society such as seducing, commanding and explaining. As animals do not have language in the true sense I have extended his concept into ethology and bio-semiotics by talking of sign games related to specific motivations and innate response mechanisms. Life as such seems to be an anticipatory function generating expectations through evolution through open genetic programs as Konrad Lorenz pointed out. The phenomenon of imprinting in ducks for instance is a standard example of programmed anticipation. Expectations are expectations of meaning and order (information) related to the semiosphere the organism constructs as its individual world view and live in. (The Umwelt of von Uexküll). On this basis events that perpetuates the semiosphere are reduced to meaning, i.e. something related to the survival and procreation of the individual living system, it conatus, to use one of Spinoza's terms. The framework of cybersemiotics, uniting second order cybernetics, semiotics and language game theory, is created to make transdisciplinary concepts and models that can handle the process of cognition, information and communication across the domains of the sciences, the arts and social sciences in a non-reductionistic way. It is seen as an alternative based on biological and semiotic thinking (biosemiotics) to the functionalistic information processing paradigm of cognitive science that is build on the computer as paradigm and based on classical logic and mechanistic physics—and therefore has severe problems of dealing with semantics and signification.
Computational models of music perception and cognition II: Domain-specific music processing
NASA Astrophysics Data System (ADS)
Purwins, Hendrik; Grachten, Maarten; Herrera, Perfecto; Hazan, Amaury; Marxer, Ricard; Serra, Xavier
2008-09-01
In Part I [Purwins H, Herrera P, Grachten M, Hazan A, Marxer R, Serra X. Computational models of music perception and cognition I: The perceptual and cognitive processing chain. Physics of Life Reviews 2008, in press, doi:10.1016/j.plrev.2008.03.004], we addressed the study of cognitive processes that underlie auditory perception of music, and their neural correlates. The aim of the present paper is to summarize empirical findings from music cognition research that are relevant to three prominent music theoretic domains: rhythm, melody, and tonality. Attention is paid to how cognitive processes like category formation, stimulus grouping, and expectation can account for the music theoretic key concepts in these domains, such as beat, meter, voice, consonance. We give an overview of computational models that have been proposed in the literature for a variety of music processing tasks related to rhythm, melody, and tonality. Although the present state-of-the-art in computational modeling of music cognition definitely provides valuable resources for testing specific hypotheses and theories, we observe the need for models that integrate the various aspects of music perception and cognition into a single framework. Such models should be able to account for aspects that until now have only rarely been addressed in computational models of music cognition, like the active nature of perception and the development of cognitive capacities from infancy to adulthood.
Cyberpsychology: a human-interaction perspective based on cognitive modeling.
Emond, Bruno; West, Robert L
2003-10-01
This paper argues for the relevance of cognitive modeling and cognitive architectures to cyberpsychology. From a human-computer interaction point of view, cognitive modeling can have benefits both for theory and model building, and for the design and evaluation of sociotechnical systems usability. Cognitive modeling research applied to human-computer interaction has two complimentary objectives: (1) to develop theories and computational models of human interactive behavior with information and collaborative technologies, and (2) to use the computational models as building blocks for the design, implementation, and evaluation of interactive technologies. From the perspective of building theories and models, cognitive modeling offers the possibility to anchor cyberpsychology theories and models into cognitive architectures. From the perspective of the design and evaluation of socio-technical systems, cognitive models can provide the basis for simulated users, which can play an important role in usability testing. As an example of application of cognitive modeling to technology design, the paper presents a simulation of interactive behavior with five different adaptive menu algorithms: random, fixed, stacked, frequency based, and activation based. Results of the simulation indicate that fixed menu positions seem to offer the best support for classification like tasks such as filing e-mails. This research is part of the Human-Computer Interaction, and the Broadband Visual Communication research programs at the National Research Council of Canada, in collaboration with the Carleton Cognitive Modeling Lab at Carleton University.
Spatial Thinking in Atmospheric Science Education
NASA Astrophysics Data System (ADS)
McNeal, P. M.; Petcovic, H. L.; Ellis, T. D.
2016-12-01
Atmospheric science is a STEM discipline that involves the visualization of three-dimensional processes from two-dimensional maps, interpretation of computer-generated graphics and hand plotting of isopleths. Thus, atmospheric science draws heavily upon spatial thinking. Research has shown that spatial thinking ability can be a predictor of early success in STEM disciplines and substantial evidence demonstrates that spatial thinking ability is improved through various interventions. Therefore, identification of the spatial thinking skills and cognitive processes used in atmospheric science is the first step toward development of instructional strategies that target these skills and scaffold the learning of students in atmospheric science courses. A pilot study of expert and novice meteorologists identified mental animation and disembedding as key spatial skills used in the interpretation of multiple weather charts and images. Using this as a starting point, we investigated how these spatial skills, together with expertise, domain specific knowledge, and working memory capacity affect the ability to produce an accurate forecast. Participants completed a meteorology concept inventory, experience questionnaire and psychometric tests of spatial thinking ability and working memory capacity prior to completing a forecasting task. A quantitative analysis of the collected data investigated the effect of the predictor variables on the outcome task. A think-aloud protocol with individual participants provided a qualitative look at processes such as task decomposition, rule-based reasoning and the formation of mental models in an attempt to understand how individuals process this complex data and describe outcomes of particular meteorological scenarios. With our preliminary results we aim to inform atmospheric science education from a cognitive science perspective. The results point to a need to collaborate with the atmospheric science community broadly, such that multiple educational pipelines are affected including university meteorology courses for majors and non-majors, military weather forecaster preparation and professional training for operational meteorologists, thus improving student learning and the continued development of the current and future workforce.
Coherence in the Visual Imagination.
Vertolli, Michael O; Kelly, Matthew A; Davies, Jim
2018-04-01
An incoherent visualization is when aspects of different senses of a word (e.g., the biological "mouse" vs. the computer "mouse") are present in the same visualization (e.g., a visualization of a biological mouse in the same image with a computer tower). We describe and implement a new model of creating contextual coherence in the visual imagination called Coherencer, based on the SOILIE model of imagination. We show that Coherencer is able to generate scene descriptions that are more coherent than SOILIE's original approach as well as a parallel connectionist algorithm that is considered competitive in the literature on general coherence. We also show that co-occurrence probabilities are a better association representation than holographic vectors and that better models of coherence improve the resulting output independent of the association type that is used. Theoretically, we show that Coherencer is consistent with other models of cognitive generation. In particular, Coherencer is a similar, but more cognitively plausible model than the C 3 model of concept combination created by Costello and Keane (2000). We show that Coherencer is also consistent with both the modal schematic indices of perceptual symbol systems theory (Barsalou, 1999) and the amodal contextual constraints of Thagard's (2002) theory of coherence. Finally, we describe how Coherencer is consistent with contemporary research on the hippocampus, and we show evidence that the process of making a visualization coherent is serial. Copyright © 2017 Cognitive Science Society, Inc.
Secomb, Jacinta; McKenna, Lisa; Smith, Colleen
2012-12-01
To provide evidence on the effectiveness of simulation activities on the clinical decision-making abilities of undergraduate nursing students. Based on previous research, it was hypothesised that the higher the cognitive score, the greater the ability a nursing student would have to make informed valid decisions in their clinical practice. Globally, simulation is being espoused as an education method that increases the competence of health professionals. At present, there is very little evidence to support current investment in time and resources. Following ethical approval, fifty-eight third-year undergraduate nursing students were randomised in a pretest-post-test group-parallel controlled trial. The learning environment preferences (LEP) inventory was used to test cognitive abilities in order to refute the null hypothesis that activities in computer-based simulated learning environments have a negative effect on cognitive abilities when compared with activities in skills laboratory simulated learning environments. There was no significant difference in cognitive development following two cycles of simulation activities. Therefore, it is reasonable to assume that two simulation tasks, either computer-based or laboratory-based, have no effect on an undergraduate student's ability to make clinical decisions in practice. However, there was a significant finding for non-English first-language students, which requires further investigation. More longitudinal studies that quantify the education effects of simulation on the cognitive, affective and psychomotor attributes of health science students and professionals from both English-speaking and non-English-speaking backgrounds are urgently required. It is also recommended that to achieve increased participant numbers and prevent non-participation owing to absenteeism, further studies need to be imbedded directly into curricula. This investigation confirms the effect of simulation activities on real-life clinical practice, and the comparative learning benefits with traditional clinical practice and university education remain unknown. © 2012 Blackwell Publishing Ltd.
From Universal Laws of Cognition to Specific Cognitive Models
ERIC Educational Resources Information Center
Chater, Nick; Brown, Gordon D. A.
2008-01-01
The remarkable successes of the physical sciences have been built on highly general quantitative laws, which serve as the basis for understanding an enormous variety of specific physical systems. How far is it possible to construct universal principles in the cognitive sciences, in terms of which specific aspects of perception, memory, or decision…
ERIC Educational Resources Information Center
Klahr, David; Li, Junlei
2005-01-01
Can cognitive research generate usable knowledge for elementary science instruction? Can issues raised by classroom practice drive the agenda of laboratory cognitive research? Answering yes to both questions, we advocate building a reciprocal interface between basic and applied research. We discuss five studies of the teaching, learning, and…
Science Teaching Based on Cognitive Load Theory: Engaged Students, but Cognitive Deficiencies
ERIC Educational Resources Information Center
Meissner, Barbara; Bogner, Franz X.
2012-01-01
To improve science learning under demanding conditions, we designed an out-of-school lesson in compliance with cognitive load theory (CLT). We extracted student clusters based on individual effectiveness, and compared instructional efficiency, mental effort, and persistence of learning. The present study analyses students' engagement. 50.0% of our…
The Status of Cognitive Psychology Journals: An Impact Factor Approach
ERIC Educational Resources Information Center
Togia, Aspasia
2013-01-01
The purpose of this study was to examine the impact factor of cognitive psychology journals indexed in the Science and Social Sciences edition of "Journal Citation Reports" ("JCR") database over a period of 10 consecutive years. Cognitive psychology journals were indexed in 11 different subject categories of the database. Their mean impact factor…
At the Root of Embodied Cognition: Cognitive Science Meets Neurophysiology
ERIC Educational Resources Information Center
Garbarini, Francesca; Adenzato, Mauro
2004-01-01
Recent experimental research in the field of neurophysiology has led to the discovery of two classes of visuomotor neurons: canonical neurons and mirror neurons. In light of these studies, we propose here an overview of two classical themes in the cognitive science panorama: James Gibson's theory of affordances and Eleanor Rosch's principles of…
Cognitive Science and Military Training.
ERIC Educational Resources Information Center
Halff, Henry M.; And Others
1986-01-01
Four new military training systems offer the opportunity for the application of cognitive science. They are the following: (1) a family of memorization games; (2) a simulator with a graphic, schematic student interface; (3) a system for solving problems of relative motion; and (4) a method of building cognitive skills for air-intercept control.…
Effects of a Modified Thinking Science Program for Year 8 Students of Various Abilities
ERIC Educational Resources Information Center
Mobbs, Ellen
2016-01-01
The aim of this research was to identify whether students of various academic abilities would achieve positive gains in cognitive ability after completing a modified cognitive acceleration program based on the Cognitive Acceleration through Science Education (CASE) program. This research was quasi-experimental in design, with small samples of…
The Challenges of Scientific Literacy: From the Viewpoint of Second-Generation Cognitive Science
ERIC Educational Resources Information Center
Klein, Perry D.
2006-01-01
Recent trends in cognitive science have not made scientific literacy easier to attain, but they have made the practices through which educators meet its challenges more interpretable. Traditionally, cognitive scientists viewed knowledge as a set of propositions comprised of classical concepts, thought as logical inference and language as a literal…
Mill and Mental Phenomena: Critical Contributions to a Science of Cognition
Bistricky, Steven L.
2013-01-01
Attempts to define cognition preceded John Stuart Mill’s life and continue to this day. John Stuart Mill envisioned a science of mental phenomena informed by associationism, empirical introspection, and neurophysiology, and he advanced specific ideas that still influence modern conceptions of cognition. The present article briefly reviews Mill’s personal history and the times in which he lived, and it traces the evolution of ideas that have run through him to contemporary cognitive concepts. The article also highlights contemporary problems in defining cognition and supports specific criteria regarding what constitutes cognition. PMID:25379235
Computer Aided Training of Cognitive Processing Strategies with Developmentally Handicapped Adults.
ERIC Educational Resources Information Center
Ryba, Kenneth A.; And Others
1985-01-01
Correlational results involving 60 developmentally handicaped adults indicated that a computerized cross-modal memory game had a highly significant relationship with most cognitive and motor coordination measures. Computer aided training was not effective in improving overall cognitive functioning. There was no evidence of cognitive skills being…
Scaffolding scientific discussion using socially relevant representations in networked multimedia
NASA Astrophysics Data System (ADS)
Hoadley, Christopher M.
1999-11-01
How do students make use of social cues when learning on the computer? This work examines how students in a middle-school science course learned through on-line peer discussion. Cognitive accounts of collaboration stress interacting with ideas, while socially situated accounts stress the interpersonal context. The design of electronic environments allows investigation into the interrelation of cognitive and social dimensions. I use on-line peer discussion to investigate how socially relevant representations in interfaces can aid learning. First, I identify some of the variables that affect individual participation in on-line discussion, including interface features. Individual participation is predicted by student attitudes towards learning from peers. Second, I describe the range of group outcomes for these on-line discussions. There is a large effect of discussion group on learning outcomes which is not reducible to group composition or gross measures of group process. Third, I characterize how students (individually) construct understanding from these group discussions. Learning in the on-line discussions is shown to be a result of sustained interaction over time, not merely encountering or expressing ideas. Experimental manipulations in the types of social cues available to students suggest that many students do use socially relevant representations to support their understanding of multiple viewpoints and science reasoning. Personalizing scientific disputes can afford reflection on the nature of scientific discovery and advance. While there are many individual differences in how social representations are used by students in learning, overall learning benefits for certain social representations can be shown. This work has profound implications for design of collaborative instructional methods, equitable access to science learning, design of instructional technology, and understanding of learning and cognition in social settings.
Dormitory of Physical and Engineering Sciences: Sleeping Beauties May Be Sleeping Innovations
van Raan, Anthony F. J.
2015-01-01
A ‘Sleeping Beauty in Science’ is a publication that goes unnoticed (‘sleeps’) for a long time and then, almost suddenly, attracts a lot of attention (‘is awakened by a prince’). The aim of this paper is to present a general methodology to investigate (1) important properties of Sleeping Beauties such as the time-dependent distribution, author characteristics, journals and fields, and (2) the cognitive environment of Sleeping Beauties. We are particularly interested to find out to what extent Sleeping Beauties are application-oriented and thus are potential Sleeping Innovations. In this study we focus primarily on physics (including materials science and astrophysics) and present first results for chemistry and for engineering & computer science. We find that more than half of the SBs are application-oriented. To study the cognitive environments of Sleeping Beauties we develop a new approach in which the cognitive environment of the SBs is analyzed, based on the mapping of Sleeping Beauties using their citation links and conceptual relations, particularly co-citation mapping. In this way we investigate the research themes in which the SBs are ‘used’ and possible causes of why the premature work in the SBs becomes topical, i.e., the trigger of the awakening of the SBs. This approach is tested with a blue skies SB and an application-oriented SB. We think that the mapping procedures discussed in this paper are not only important for bibliometric analyses. They also provide researchers with useful, interactive tools to discover both relevant older work as well as new developments, for instance in themes related to Sleeping Beauties that are also Sleeping Innovations. PMID:26469987
Cognitive Computing for Security.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Debenedictis, Erik; Rothganger, Fredrick; Aimone, James Bradley
Final report for Cognitive Computing for Security LDRD 165613. It reports on the development of hybrid of general purpose/ne uromorphic computer architecture, with an emphasis on potential implementation with memristors.
Holmes, Emily A.; James, Ella L.; Kilford, Emma J.; Deeprose, Catherine
2010-01-01
Background Flashbacks (intrusive memories of a traumatic event) are the hallmark feature of Post Traumatic Stress Disorder, however preventative interventions are lacking. Tetris may offer a ‘cognitive vaccine’ [1] against flashback development after trauma exposure. We previously reported that playing the computer game Tetris soon after viewing traumatic material reduced flashbacks compared to no-task [1]. However, two criticisms need to be addressed for clinical translation: (1) Would all games have this effect via distraction/enjoyment, or might some games even be harmful? (2) Would effects be found if administered several hours post-trauma? Accordingly, we tested Tetris versus an alternative computer game – Pub Quiz – which we hypothesized not to be helpful (Experiments 1 and 2), and extended the intervention interval to 4 hours (Experiment 2). Methodology/Principal Findings The trauma film paradigm was used as an experimental analog for flashback development in healthy volunteers. In both experiments, participants viewed traumatic film footage of death and injury before completing one of the following: (1) no-task control condition (2) Tetris or (3) Pub Quiz. Flashbacks were monitored for 1 week. Experiment 1: 30 min after the traumatic film, playing Tetris led to a significant reduction in flashbacks compared to no-task control, whereas Pub Quiz led to a significant increase in flashbacks. Experiment 2: 4 hours post-film, playing Tetris led to a significant reduction in flashbacks compared to no-task control, whereas Pub Quiz did not. Conclusions/Significance First, computer games can have differential effects post-trauma, as predicted by a cognitive science formulation of trauma memory. In both Experiments, playing Tetris post-trauma film reduced flashbacks. Pub Quiz did not have this effect, even increasing flashbacks in Experiment 1. Thus not all computer games are beneficial or merely distracting post-trauma - some may be harmful. Second, the beneficial effects of Tetris are retained at 4 hours post-trauma. Clinically, this delivers a feasible time-window to administer a post-trauma “cognitive vaccine”. PMID:21085661
The Biological Relevance of Artificial Life: Lessons from Artificial Intelligence
NASA Technical Reports Server (NTRS)
Colombano, Silvano
2000-01-01
There is no fundamental reason why A-life couldn't simply be a branch of computer science that deals with algorithms that are inspired by, or emulate biological phenomena. However, if these are the limits we place on this field, we miss the opportunity to help advance Theoretical Biology and to contribute to a deeper understanding of the nature of life. The history of Artificial Intelligence provides a good example, in that early interest in the nature of cognition quickly was lost to the process of building tools, such as "expert systems" that, were certainly useful, but provided little insight in the nature of cognition. Based on this lesson, I will discuss criteria for increasing the biological relevance of A-life and the probability that this field may provide a theoretical foundation for Biology.
Relational Integration as a Predictor of Academic Achievement
ERIC Educational Resources Information Center
Krumm, Stefan; Lipnevich, Anastasiya A.; Schmidt-Atzert, Lothar; Buhner, Markus
2012-01-01
The current study aimed at applying a broad model of cognitive functions to predict performance in science and language courses at school as well as performance in a science course at university. We hypothesized that performance in science courses was predominantly related to the cognitive function known as relational integration, whereas…
The Relationship of Mentoring on Middle School Girls' Science-Related Attitudes
ERIC Educational Resources Information Center
Clark, Lynette M.
2013-01-01
This quantitative study examined the science-related attitudes of middle school girls who attended a science-focused mentoring program and those of middle school girls who attended a traditional mentoring program. Theories related to this study include social cognitive theory, cognitive development theory, and possible selves' theory. These…
Teaching School Science within the Cognitive and Affective Domains
ERIC Educational Resources Information Center
Tan, Kok Siang; Heng, Chong Yong; Tan, Shuhui
2013-01-01
In classrooms, science is usually taught within the cognitive domain while the psychomotor learning domain is achieved through performing science experiments in the laboratory. Although students attend civic and moral education and pastoral care classes where values and life skills are often taught directly, learning experiences in most school…
ERIC Educational Resources Information Center
Quimby, Julie L.; Seyala, Nazar D.; Wolfson, Jane L.
2007-01-01
The authors examined the influence of social cognitive variables on students' interest in environmental science careers and investigated differences between White and ethnic minority students on several career-related variables. The sample consisted of 161 undergraduate science majors (124 White students, 37 ethnic minority students). Results of…
From self-observation to imitation: visuomotor association on a robotic hand.
Chaminade, Thierry; Oztop, Erhan; Cheng, Gordon; Kawato, Mitsuo
2008-04-15
Being at the crux of human cognition and behaviour, imitation has become the target of investigations ranging from experimental psychology and neurophysiology to computational sciences and robotics. It is often assumed that the imitation is innate, but it has more recently been argued, both theoretically and experimentally, that basic forms of imitation could emerge as a result of self-observation. Here, we tested this proposal on a realistic experimental platform, comprising an associative network linking a 16 degrees of freedom robotic hand and a simple visual system. We report that this minimal visuomotor association is sufficient to bootstrap basic imitation. Our results indicate that crucial features of human imitation, such as generalization to new actions, may emerge from a connectionist associative network. Therefore, we suggest that a behaviour as complex as imitation could be, at the neuronal level, founded on basic mechanisms of associative learning, a notion supported by a recent proposal on the developmental origin of mirror neurons. Our approach can be applied to the development of realistic cognitive architectures for humanoid robots as well as to shed new light on the cognitive processes at play in early human cognitive development.
A social-cognitive framework of multidisciplinary team innovation.
Paletz, Susannah B F; Schunn, Christian D
2010-01-01
The psychology of science typically lacks integration between cognitive and social variables. We present a new framework of team innovation in multidisciplinary science and engineering groups that ties factors from both literatures together. We focus on the effects of a particularly challenging social factor, knowledge diversity, which has a history of mixed effects on creativity, most likely because those effects are mediated and moderated by cognitive and additional social variables. In addition, we highlight the distinction between team innovative processes that are primarily divergent versus convergent; we propose that the social and cognitive implications are different for each, providing a possible explanation for knowledge diversity's mixed results on team outcomes. Social variables mapped out include formal roles, communication norms, sufficient participation and information sharing, and task conflict; cognitive variables include analogy, information search, and evaluation. This framework provides a roadmap for research that aims to harness the power of multidisciplinary teams. Copyright © 2009 Cognitive Science Society, Inc.
Donnarumma, Francesco; Maisto, Domenico; Pezzulo, Giovanni
2016-01-01
How do humans and other animals face novel problems for which predefined solutions are not available? Human problem solving links to flexible reasoning and inference rather than to slow trial-and-error learning. It has received considerable attention since the early days of cognitive science, giving rise to well known cognitive architectures such as SOAR and ACT-R, but its computational and brain mechanisms remain incompletely known. Furthermore, it is still unclear whether problem solving is a “specialized” domain or module of cognition, in the sense that it requires computations that are fundamentally different from those supporting perception and action systems. Here we advance a novel view of human problem solving as probabilistic inference with subgoaling. In this perspective, key insights from cognitive architectures are retained such as the importance of using subgoals to split problems into subproblems. However, here the underlying computations use probabilistic inference methods analogous to those that are increasingly popular in the study of perception and action systems. To test our model we focus on the widely used Tower of Hanoi (ToH) task, and show that our proposed method can reproduce characteristic idiosyncrasies of human problem solvers: their sensitivity to the “community structure” of the ToH and their difficulties in executing so-called “counterintuitive” movements. Our analysis reveals that subgoals have two key roles in probabilistic inference and problem solving. First, prior beliefs on (likely) useful subgoals carve the problem space and define an implicit metric for the problem at hand—a metric to which humans are sensitive. Second, subgoals are used as waypoints in the probabilistic problem solving inference and permit to find effective solutions that, when unavailable, lead to problem solving deficits. Our study thus suggests that a probabilistic inference scheme enhanced with subgoals provides a comprehensive framework to study problem solving and its deficits. PMID:27074140
Koperwhats, Martha A; Chang, Wei-Chih; Xiao, Jianguo
2002-01-01
Digital imaging technology promises efficient, economical, and fast service for patient care, but the challenges are great in the transition from film to a filmless (digital) environment. This change has a significant impact on the film library's personnel (film librarians) who play a leading roles in storage, classification, and retrieval of images. The objectives of this project were to study film library errors and the usability of a physical computerized system that could not be changed, while developing an intervention to reduce errors and test the usability of the intervention. Cognitive and human factors analysis were used to evaluate human-computer interaction. A workflow analysis was performed to understand the film and digital imaging processes. User and task analyses were applied to account for all behaviors involved in interaction with the system. A heuristic evaluation was used to probe the usability issues in the picture archiving and communication systems (PACS) modules. Simplified paper-based instructions were designed to familiarize the film librarians with the digital system. A usability survey evaluated the effectiveness of the instruction. The user and task analyses indicated that different users faced challenges based on their computer literacy, education, roles, and frequency of use of diagnostic imaging. The workflow analysis showed that the approaches to using the digital library differ among the various departments. The heuristic evaluation of the PACS modules showed the human-computer interface to have usability issues that prevented easy operation. Simplified instructions were designed for operation of the modules. Usability surveys conducted before and after revision of the instructions showed that performance improved. Cognitive and human factor analysis can help film librarians and other users adapt to the filmless system. Use of cognitive science tools will aid in successful transition of the film library from a film environment to a digital environment.
Donnarumma, Francesco; Maisto, Domenico; Pezzulo, Giovanni
2016-04-01
How do humans and other animals face novel problems for which predefined solutions are not available? Human problem solving links to flexible reasoning and inference rather than to slow trial-and-error learning. It has received considerable attention since the early days of cognitive science, giving rise to well known cognitive architectures such as SOAR and ACT-R, but its computational and brain mechanisms remain incompletely known. Furthermore, it is still unclear whether problem solving is a "specialized" domain or module of cognition, in the sense that it requires computations that are fundamentally different from those supporting perception and action systems. Here we advance a novel view of human problem solving as probabilistic inference with subgoaling. In this perspective, key insights from cognitive architectures are retained such as the importance of using subgoals to split problems into subproblems. However, here the underlying computations use probabilistic inference methods analogous to those that are increasingly popular in the study of perception and action systems. To test our model we focus on the widely used Tower of Hanoi (ToH) task, and show that our proposed method can reproduce characteristic idiosyncrasies of human problem solvers: their sensitivity to the "community structure" of the ToH and their difficulties in executing so-called "counterintuitive" movements. Our analysis reveals that subgoals have two key roles in probabilistic inference and problem solving. First, prior beliefs on (likely) useful subgoals carve the problem space and define an implicit metric for the problem at hand-a metric to which humans are sensitive. Second, subgoals are used as waypoints in the probabilistic problem solving inference and permit to find effective solutions that, when unavailable, lead to problem solving deficits. Our study thus suggests that a probabilistic inference scheme enhanced with subgoals provides a comprehensive framework to study problem solving and its deficits.
Potential of Cognitive Computing and Cognitive Systems
NASA Astrophysics Data System (ADS)
Noor, Ahmed K.
2015-01-01
Cognitive computing and cognitive technologies are game changers for future engineering systems, as well as for engineering practice and training. They are major drivers for knowledge automation work, and the creation of cognitive products with higher levels of intelligence than current smart products. This paper gives a brief review of cognitive computing and some of the cognitive engineering systems activities. The potential of cognitive technologies is outlined, along with a brief description of future cognitive environments, incorporating cognitive assistants - specialized proactive intelligent software agents designed to follow and interact with humans and other cognitive assistants across the environments. The cognitive assistants engage, individually or collectively, with humans through a combination of adaptive multimodal interfaces, and advanced visualization and navigation techniques. The realization of future cognitive environments requires the development of a cognitive innovation ecosystem for the engineering workforce. The continuously expanding major components of the ecosystem include integrated knowledge discovery and exploitation facilities (incorporating predictive and prescriptive big data analytics); novel cognitive modeling and visual simulation facilities; cognitive multimodal interfaces; and cognitive mobile and wearable devices. The ecosystem will provide timely, engaging, personalized / collaborative, learning and effective decision making. It will stimulate creativity and innovation, and prepare the participants to work in future cognitive enterprises and develop new cognitive products of increasing complexity. http://www.aee.odu.edu/cognitivecomp
Fiedler, Klaus
2016-02-01
Drawing on illustrative examples of the functional and cognitive psychology in contemporary research, the present article emphasizes the primacy of functional relationships, which provide the fundament for all attempts to uncover invisible cognitive processes. Cognitive research is not only inherently more difficult and much more ambitious than functional research. It also suffers from several home-made problems, such as unwarranted inferences from model fitting, the mediation-analysis cult and the failure to take environmental influences into account. However, despite the primacy of functional psychology and the problems associated with the ambitious goals of cognitive research, the two partners in this unequal pair are firmly connected and jointly responsible for the most impressive examples of progress in behavioural science. © 2015 International Union of Psychological Science.
Milic, Natasa M.; Masic, Srdjan; Milin-Lazovic, Jelena; Trajkovic, Goran; Bukumiric, Zoran; Savic, Marko; Milic, Nikola V.; Cirkovic, Andja; Gajic, Milan; Kostic, Mirjana; Ilic, Aleksandra; Stanisavljevic, Dejana
2016-01-01
Background The scientific community increasingly is recognizing the need to bolster standards of data analysis given the widespread concern that basic mistakes in data analysis are contributing to the irreproducibility of many published research findings. The aim of this study was to investigate students’ attitudes towards statistics within a multi-site medical educational context, monitor their changes and impact on student achievement. In addition, we performed a systematic review to better support our future pedagogical decisions in teaching applied statistics to medical students. Methods A validated Serbian Survey of Attitudes Towards Statistics (SATS-36) questionnaire was administered to medical students attending obligatory introductory courses in biostatistics from three medical universities in the Western Balkans. A systematic review of peer-reviewed publications was performed through searches of Scopus, Web of Science, Science Direct, Medline, and APA databases through 1994. A meta-analysis was performed for the correlation coefficients between SATS component scores and statistics achievement. Pooled estimates were calculated using random effects models. Results SATS-36 was completed by 461 medical students. Most of the students held positive attitudes towards statistics. Ability in mathematics and grade point average were associated in a multivariate regression model with the Cognitive Competence score, after adjusting for age, gender and computer ability. The results of 90 paired data showed that Affect, Cognitive Competence, and Effort scores demonstrated significant positive changes. The Cognitive Competence score showed the largest increase (M = 0.48, SD = 0.95). The positive correlation found between the Cognitive Competence score and students’ achievement (r = 0.41; p<0.001), was also shown in the meta-analysis (r = 0.37; 95% CI 0.32–0.41). Conclusion Students' subjective attitudes regarding Cognitive Competence at the beginning of the biostatistics course, which were directly linked to mathematical knowledge, affected their attitudes at the end of the course that, in turn, influenced students' performance. This indicates the importance of positively changing not only students’ cognitive competency, but also their perceptions of gained competency during the biostatistics course. PMID:27764123
Milic, Natasa M; Masic, Srdjan; Milin-Lazovic, Jelena; Trajkovic, Goran; Bukumiric, Zoran; Savic, Marko; Milic, Nikola V; Cirkovic, Andja; Gajic, Milan; Kostic, Mirjana; Ilic, Aleksandra; Stanisavljevic, Dejana
2016-01-01
The scientific community increasingly is recognizing the need to bolster standards of data analysis given the widespread concern that basic mistakes in data analysis are contributing to the irreproducibility of many published research findings. The aim of this study was to investigate students' attitudes towards statistics within a multi-site medical educational context, monitor their changes and impact on student achievement. In addition, we performed a systematic review to better support our future pedagogical decisions in teaching applied statistics to medical students. A validated Serbian Survey of Attitudes Towards Statistics (SATS-36) questionnaire was administered to medical students attending obligatory introductory courses in biostatistics from three medical universities in the Western Balkans. A systematic review of peer-reviewed publications was performed through searches of Scopus, Web of Science, Science Direct, Medline, and APA databases through 1994. A meta-analysis was performed for the correlation coefficients between SATS component scores and statistics achievement. Pooled estimates were calculated using random effects models. SATS-36 was completed by 461 medical students. Most of the students held positive attitudes towards statistics. Ability in mathematics and grade point average were associated in a multivariate regression model with the Cognitive Competence score, after adjusting for age, gender and computer ability. The results of 90 paired data showed that Affect, Cognitive Competence, and Effort scores demonstrated significant positive changes. The Cognitive Competence score showed the largest increase (M = 0.48, SD = 0.95). The positive correlation found between the Cognitive Competence score and students' achievement (r = 0.41; p<0.001), was also shown in the meta-analysis (r = 0.37; 95% CI 0.32-0.41). Students' subjective attitudes regarding Cognitive Competence at the beginning of the biostatistics course, which were directly linked to mathematical knowledge, affected their attitudes at the end of the course that, in turn, influenced students' performance. This indicates the importance of positively changing not only students' cognitive competency, but also their perceptions of gained competency during the biostatistics course.
Cowell, Rosemary A; Bussey, Timothy J; Saksida, Lisa M
2012-11-01
We describe how computational models can be useful to cognitive and behavioral neuroscience, and discuss some guidelines for deciding whether a model is useful. We emphasize that because instantiating a cognitive theory as a computational model requires specification of an explicit mechanism for the function in question, it often produces clear and novel behavioral predictions to guide empirical research. However, computational modeling in cognitive and behavioral neuroscience remains somewhat rare, perhaps because of misconceptions concerning the use of computational models (in particular, connectionist models) in these fields. We highlight some common misconceptions, each of which relates to an aspect of computational models: the problem space of the model, the level of biological organization at which the model is formulated, and the importance (or not) of biological plausibility, parsimony, and model parameters. Careful consideration of these aspects of a model by empiricists, along with careful delineation of them by modelers, may facilitate communication between the two disciplines and promote the use of computational models for guiding cognitive and behavioral experiments. Copyright © 2012 Elsevier Ltd. All rights reserved.
Synthesizing Results From Empirical Research on Computer-Based Scaffolding in STEM Education
Belland, Brian R.; Walker, Andrew E.; Kim, Nam Ju; Lefler, Mason
2016-01-01
Computer-based scaffolding assists students as they generate solutions to complex problems, goals, or tasks, helping increase and integrate their higher order skills in the process. However, despite decades of research on scaffolding in STEM (science, technology, engineering, and mathematics) education, no existing comprehensive meta-analysis has synthesized the results of these studies. This review addresses that need by synthesizing the results of 144 experimental studies (333 outcomes) on the effects of computer-based scaffolding designed to assist the full range of STEM learners (primary through adult education) as they navigated ill-structured, problem-centered curricula. Results of our random effect meta-analysis (a) indicate that computer-based scaffolding showed a consistently positive (ḡ = 0.46) effect on cognitive outcomes across various contexts of use, scaffolding characteristics, and levels of assessment and (b) shed light on many scaffolding debates, including the roles of customization (i.e., fading and adding) and context-specific support. Specifically, scaffolding’s influence on cognitive outcomes did not vary on the basis of context-specificity, presence or absence of scaffolding change, and logic by which scaffolding change is implemented. Scaffolding’s influence was greatest when measured at the principles level and among adult learners. Still scaffolding’s effect was substantial and significantly greater than zero across all age groups and assessment levels. These results suggest that scaffolding is a highly effective intervention across levels of different characteristics and can largely be designed in many different ways while still being highly effective. PMID:28344365
Belland, Brian R; Walker, Andrew E; Kim, Nam Ju; Lefler, Mason
2017-04-01
Computer-based scaffolding assists students as they generate solutions to complex problems, goals, or tasks, helping increase and integrate their higher order skills in the process. However, despite decades of research on scaffolding in STEM (science, technology, engineering, and mathematics) education, no existing comprehensive meta-analysis has synthesized the results of these studies. This review addresses that need by synthesizing the results of 144 experimental studies (333 outcomes) on the effects of computer-based scaffolding designed to assist the full range of STEM learners (primary through adult education) as they navigated ill-structured, problem-centered curricula. Results of our random effect meta-analysis (a) indicate that computer-based scaffolding showed a consistently positive (ḡ = 0.46) effect on cognitive outcomes across various contexts of use, scaffolding characteristics, and levels of assessment and (b) shed light on many scaffolding debates, including the roles of customization (i.e., fading and adding) and context-specific support. Specifically, scaffolding's influence on cognitive outcomes did not vary on the basis of context-specificity, presence or absence of scaffolding change, and logic by which scaffolding change is implemented. Scaffolding's influence was greatest when measured at the principles level and among adult learners. Still scaffolding's effect was substantial and significantly greater than zero across all age groups and assessment levels. These results suggest that scaffolding is a highly effective intervention across levels of different characteristics and can largely be designed in many different ways while still being highly effective.
Department-Level Representations: A New Approach to the Study of Science Teacher Cognition
ERIC Educational Resources Information Center
Hutner, Todd L.; Markman, Arthur B.
2016-01-01
Research on science teacher cognition is important as findings from this research can be used to improve teacher training, leading to improved classroom practice. Previous research has often relied on two underlying assumptions: Cognition is an individual process, and these processes are detailed and introspective. In this paper, we put forth a…
Parental Loss and Eating-Related Cognitions and Behaviors in College-Age Women
ERIC Educational Resources Information Center
Beam, Minna R.; Servaty-Seib, Heather L.; Mathews, Laura
2004-01-01
To examine the eating-related cognitions and behaviors of college-age women who had experienced parental death, parental divorce, or neither loss condition, we recruited 48 women from science and social science departments at a state university in the Southeast. All participants completed the Mizes Anorectic Cognitions Scale (MAC) and the Bulimia…
Towards Cognitive Load Theory as Guideline for Instructional Design in Science Education
ERIC Educational Resources Information Center
Meissner, Barbara; Bogner, Franz X.
2013-01-01
We applied cognitive load theory in an heuristic out-of-school science lesson. The lesson comprises experiments concerning major attributes of NaCl and was designed for 5th to 8th grade students. Our interest focused on whether cognitive load theory provides sufficient guidelines for instructional design in the field of heuristic science…
An Investigation of Some Cognitive Style Variables and Their Relationships to Science Achievement.
ERIC Educational Resources Information Center
Zambotti, Geno; Fazio, Frank
This study was designed to survey the cognitive style preferences of college students. Two instruments were used in obtaining data for this inquiry. The Cognitive Preference Survey for Physical Science, developed by the authors, gave three preference scores: Memory, a preference for simple content facts; Principle, for a concept or theoretical…
ERIC Educational Resources Information Center
Gebre, Engida
2018-01-01
This paper presents a descriptive case study where infographics--visual representation of data and ideas--have been used as cognitive tools to facilitate learning with multiple representations in the context of secondary school students' science news reporting. Despite the complementary nature of the two research foci, studies on cognitive tools…