Log in

Relevant bibliographies by topics / Cognitive science engineering / Journal articles

To see the other types of publications on this topic, follow the link: Cognitive science engineering.

Journal articles on the topic 'Cognitive science engineering'

Author: Grafiati

Published: 4 June 2021

Last updated: 1 February 2022

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Cognitive science engineering.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Wang, Yingxu, Bernard Carlos Widrow, Bo Zhang, et al. "Perspectives on the Field of Cognitive Informatics and its Future Development." International Journal of Cognitive Informatics and Natural Intelligence 5, no. 1 (2011): 1–17. http://dx.doi.org/10.4018/jcini.2011010101.

Full text

Abstract:

The contemporary wonder of sciences and engineering has recently refocused on the beginning point of: how the brain processes internal and external information autonomously and cognitively rather than imperatively like conventional computers. Cognitive Informatics (CI) is a transdisciplinary enquiry of computer science, information sciences, cognitive science, and intelligence science that investigates the internal information processing mechanisms and processes of the brain and natural intelligence, as well as their engineering applications in cognitive computing. This paper reports a set of eight position statements presented in the plenary panel of IEEE ICCI’10 on Cognitive Informatics and Its Future Development contributed from invited panelists who are part of the world’s renowned researchers and scholars in the field of cognitive informatics and cognitive computing.

APA, Harvard, Vancouver, ISO, and other styles

2

Raubal, Martin. "Cognitive Engineering for Geographic Information Science." Geography Compass 3, no. 3 (2009): 1087–104. http://dx.doi.org/10.1111/j.1749-8198.2009.00224.x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Wang, Yingxu, George Baciu, Yiyu Yao, et al. "Perspectives on Cognitive Informatics and Cognitive Computing." International Journal of Cognitive Informatics and Natural Intelligence 4, no. 1 (2010): 1–29. http://dx.doi.org/10.4018/jcini.2010010101.

Full text

Abstract:

Cognitive informatics is a transdisciplinary enquiry of computer science, information sciences, cognitive science, and intelligence science that investigates the internal information processing mechanisms and processes of the brain and natural intelligence, as well as their engineering applications in cognitive computing. Cognitive computing is an emerging paradigm of intelligent computing methodologies and systems based on cognitive informatics that implements computational intelligence by autonomous inferences and perceptions mimicking the mechanisms of the brain. This article presents a set of collective perspectives on cognitive informatics and cognitive computing, as well as their applications in abstract intelligence, computational intelligence, computational linguistics, knowledge representation, symbiotic computing, granular computing, semantic computing, machine learning, and social computing.

APA, Harvard, Vancouver, ISO, and other styles

4

Ross, Don. "Empiricism, sciences, and engineering: cognitive science as a zone of integration." Cognitive Processing 20, no. 2 (2019): 261–67. http://dx.doi.org/10.1007/s10339-019-00916-z.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Blomberg, Olle. "Conceptions of Cognition for Cognitive Engineering." International Journal of Aviation Psychology 21, no. 1 (2011): 85–104. http://dx.doi.org/10.1080/10508414.2011.537561.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

Wang, Yingxu. "On the Mathematical Theories and Cognitive Foundations of Information." International Journal of Cognitive Informatics and Natural Intelligence 9, no. 3 (2015): 42–64. http://dx.doi.org/10.4018/ijcini.2015070103.

Full text

Abstract:

A recent discovery in computer and software sciences is that information in general is a deterministic abstract quantity rather than a probability-based property of the nature. Information is a general form of abstract objects represented by symbolical, mathematical, communication, computing, and cognitive systems. Therefore, information science is one of the contemporary scientific disciplines collectively known as abstract sciences such as system, information, cybernetics, cognition, knowledge, and intelligence sciences. This paper presents the cognitive foundations, mathematical models, and formal properties of information towards an extended theory of information science. From this point of view, information is classified into the categories of classic, computational, and cognitive information in the contexts of communication, computation, and cognition, respectively. Based on the three generations of information theories, a coherent framework of contemporary information is introduced, which reveals the nature of information and the fundamental principles of information science and engineering.

APA, Harvard, Vancouver, ISO, and other styles

7

Woods, David D., Jennifer C. Watts, John M. Graham, Daniel L. Kidwell, and Philip J. Smith. "Teaching Cognitive Systems Engineering." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 40, no. 4 (1996): 259–63. http://dx.doi.org/10.1177/154193129604000425.

Full text

Abstract:

Our motivation for this paper is to stimulate discussions within the human factors community about teaching Cognitive Engineering at the undergraduate level. For the last fourteen years, the Cognitive Systems Engineering Laboratory at the Ohio State University has offered an undergraduate course in Cognitive Engineering (multiple offerings per year to Industrial Engineering, Industrial Design, Computer Science and Psychology students). In this paper, we will draw from our teaching experiences and describe our framework for teaching Cognitive Engineering.

APA, Harvard, Vancouver, ISO, and other styles

8

Woods, David D. "GUTs or no GUTs (Grand Unified Theories): Does/Can/Should Cognitive Engineering have G.U.T.s?" Proceedings of the Human Factors and Ergonomics Society Annual Meeting 46, no. 3 (2002): 468–71. http://dx.doi.org/10.1177/154193120204600353.

Full text

Abstract:

What are the GUTs of Cognitive Systems Engineering (CSE)? G.U.T. is an abbreviation for Grand Unified Theory. As Cognitive Science matured, Allen Newell proposed a unifying model of cognition expressed as a software architecture SOAR. Similarly, John Anderson developed ACTR also claiming it represented a unified theory of cognition in the form of a computer simulation. Both of these cognitive architectures are computer programs that claim to simulate or be the basis for creating simulations of how people perform and learn cognitive tasks. Taking the development of Cognitive Science as a possible analogy for the potential development of Cognitive Systems Engineering, this panel discussion provides a platform to stimulate a vigorous exchange of ideas about the foundation of and potential futures of CSE.

APA, Harvard, Vancouver, ISO, and other styles

9

Wang, Yingxu, Robert C. Berwick, Simon Haykin, et al. "Cognitive Informatics and Cognitive Computing in Year 10 and Beyond." International Journal of Cognitive Informatics and Natural Intelligence 5, no. 4 (2011): 1–21. http://dx.doi.org/10.4018/jcini.2011100101.

Full text

Abstract:

Cognitive Informatics (CI) is a transdisciplinary enquiry of computer science, information sciences, cognitive science, and intelligence science that investigates into the internal information processing mechanisms and processes of the brain and natural intelligence, as well as their engineering applications in cognitive computing. The latest advances in CI leads to the establishment of cognitive computing theories and methodologies, as well as the development of Cognitive Computers (CogC) that perceive, infer, and learn. This paper reports a set of nine position statements presented in the plenary panel of IEEE ICCI*CC’11 on Cognitive Informatics in Year 10 and Beyond contributed from invited panelists who are part of the world’s renowned researchers and scholars in the field of cognitive informatics and cognitive computing.

APA, Harvard, Vancouver, ISO, and other styles

10

REASON, JAMES. "Commentary Broadening the cognitive engineering horizons: more engineering, less cognition and no philosophy of science, please." Ergonomics 41, no. 2 (1998): 150–52. http://dx.doi.org/10.1080/001401398187161.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Wang, Yingxu. "On the Cognitive and Theoretical Foundations of Big Data Science and Engineering." New Mathematics and Natural Computation 13, no. 02 (2017): 101–17. http://dx.doi.org/10.1142/s1793005717400026.

Full text

Abstract:

Big data play an indispensable role not only in the cognitive mechanisms of human sensation, quantification, qualification, estimation, memory, and reasoning, but also in a wide range of engineering applications. A basic study on the theoretical foundations of big data science is presented with a coherent set of general principles and analytic methodologies for big data systems. Cognitive foundations of big data are explored in order to formally explain the origination and nature of big data. A set of mathematical models of big data are created that rigorously elicit the general essences and patterns of big data across pervasive domains in sciences, engineering, and societies. A significant finding towards big data science is that big data systems in nature are a recursive [Formula: see text]-dimensional-typed hyperstructure (RNTHS) rather than pure numbers. The fundamental topological property of big data reveals a set of denotational mathematical solutions for dealing with inherited complexities and unprecedented challenges in big data engineering.

APA, Harvard, Vancouver, ISO, and other styles

12

Fiore, Stephen M., Haydee M. Cuevas, and Eduardo Salas. "Putting Working Memory to Work: Integrating Cognitive Science Theories with Cognitive Engineering Research." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 47, no. 3 (2003): 508–12. http://dx.doi.org/10.1177/154193120304700354.

Full text

APA, Harvard, Vancouver, ISO, and other styles

13

Alty, James L. "Engineering for the Mind: Cognitive Science and Musical Composition." Journal of New Music Research 31, no. 3 (2002): 249–55. http://dx.doi.org/10.1076/jnmr.31.3.249.14189.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Sangaiah, Arun Kumar, Hoang Pham, Mu-Yen Chen, Huimin Lu, and Francesco Mercaldo. "Cognitive data science methods and models for engineering applications." Soft Computing 23, no. 19 (2019): 9045–48. http://dx.doi.org/10.1007/s00500-019-04262-2.

Full text

APA, Harvard, Vancouver, ISO, and other styles

15

Ismafairus Abd Hamid, Aini, Jafri Malin Abdullah, and Norsiah Fauzan. "The Future of Cognitive Neuroscience." International Journal of Engineering & Technology 7, no. 3.22 (2018): 1. http://dx.doi.org/10.14419/ijet.v7i3.22.17111.

Full text

Abstract:

Cognitive neuroscience is an interdisciplinary area focusing on the application of neuroscience knowledge in areas such as neuroimaging studies, computer science, psychology, marketing, business, general and special education, social sciences, engineering, biology, learning science, health, etcetra. It is a new emerging field that may help Malaysia in the move towards 2050 for the development of economic, improve levels of knowledge and education, intensify healthcare, enhance people’s well-being and expand network collaboration. Academicians, scientists, industry and educators must concentrate on the application cognitive neuroscience in their field of studies. There is a lack of neuroscientists in these fields, and concentrated efforts must come from the top down as well as the bottom up. We need to bring brain and mind sciences and neuroscience to a reputable level that will improve physical and mental health and increase creativity and innovation in Malaysia: A national institute to amalgamate the creative and innovative mind, behaviour, and brain sciences and neuroscience must be established.

APA, Harvard, Vancouver, ISO, and other styles

16

Castro, Nichol, and Cynthia S. Q. Siew. "Contributions of modern network science to the cognitive sciences: revisiting research spirals of representation and process." Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences 476, no. 2238 (2020): 20190825. http://dx.doi.org/10.1098/rspa.2019.0825.

Full text

Abstract:

Modelling the structure of cognitive systems is a central goal of the cognitive sciences—a goal that has greatly benefitted from the application of network science approaches. This paper provides an overview of how network science has been applied to the cognitive sciences, with a specific focus on the two research ‘spirals’ of cognitive sciences related to the representation and processes of the human mind. For each spiral, we first review classic papers in the psychological sciences that have drawn on graph-theoretic ideas or frameworks before the advent of modern network science approaches. We then discuss how current research in these areas has been shaped by modern network science, which provides the mathematical framework and methodological tools for psychologists to (i) represent cognitive network structure and (ii) investigate and model the psychological processes that occur in these cognitive networks. Finally, we briefly comment on the future of, and the challenges facing, cognitive network science.

APA, Harvard, Vancouver, ISO, and other styles

17

AKINCI, T. Çetin. "A vıew to cognItıve engıneerıng." International Conference on Technics, Technologies and Education, ICTTE 2019 (2019): 29–34. http://dx.doi.org/10.15547/ictte.2019.01.105.

Full text

Abstract:

Cognitive engineering is the application of artificial intelligence, cognitive psychology and many different disciplines to human-machine systems with various software hardware elements. Cognitive engineering is supported by engineering disciplines and health, medical, psychology, sociology and even philosophical sciences. In this sense, it can be accepted as an interdisciplinary new science. Cognitive engineering is the transformation of human thought and psychology, even philosophy, into systems by modelling with software programs. Thus, machines or systems can be provided with more humane thinking and decision making capabilities than artificial intelligence. In this study, general information about Cognitive Engineering discipline will be given and recent applications in this field will be discussed.

APA, Harvard, Vancouver, ISO, and other styles

18

Nersessian, Nancy J. "The Cognitive-Cultural Systems of the Research Laboratory." Organization Studies 27, no. 1 (2006): 125–45. http://dx.doi.org/10.1177/0170840606061842.

Full text

Abstract:

A central challenge for science studies researchers in developing accounts of knowledge construction in science and engineering is to integrate the cognitive, social, cultural, and material dimensions of practice. Within science studies there is a perceived divide between cognitive practices, on the one hand, and cultural practices, on the other. Any such divide, though at times analytically useful, is artificial. Producing scientific knowledge requires the kind of sophisticated cognition that only rich social, cultural, and material environments can enable. This paper aims to move in the direction of an integrative account of these dimensions of practice. It discusses model-based reasoning practices in biomedical engineering research laboratories construed as ‘evolving cognitive-cultural systems’.

APA, Harvard, Vancouver, ISO, and other styles

19

Flogie, Andrej, and Boris Aberšek. "TRANSDISCIPLINARY APPROACH OF SCIENCE, TECHNOLOGY, ENGINEERING AND MATHEMATICS EDUCATION." Journal of Baltic Science Education 14, no. 6 (2015): 779–90. http://dx.doi.org/10.33225/jbse/15.14.779.

Full text

Abstract:

At the end of 20th century and especially in this century the education field is undergoing a significant change not only as a result of technological innovations but also pedagogical innovations on the bases of artificial intelligence (AI), cognitive science and neuroscience. What interested us was the attitude of students and teachers towards these changes. In the research the participating students were arranged in two groups, the control group (CG), where conventional lessons were carried out and the experimental group (EG), in which teachers used a transdisciplinary cognitive neuroeducation model. The performance data for the both groups was acquired via questionnaire adopted from TIMSS research. The teachers’ attitude towards these changes was mostly monitored via qualitative research. As is apparent from the results, a positive shift can be seen in the students’ attitude towards school. And this positive attitude towards school can create in students the suitable motivation, which is the first and most important step towards quality knowledge. A positive shift was also made in the minds of the teachers. Key words: artificial intelligence, cognitive science, cognitive neuroeducation model, multidisciplinarity, neuroscience, transdisciplinary model.

APA, Harvard, Vancouver, ISO, and other styles

20

Stacy, Webb, and Jean MacMillan. "Cognitive bias in software engineering." Communications of the ACM 38, no. 6 (1995): 57–63. http://dx.doi.org/10.1145/203241.203256.

Full text

APA, Harvard, Vancouver, ISO, and other styles

21

WATANUKI, Keiichi. "New Trends of Kansei, Emotional, and Cognitive Science and Engineering." Proceedings of Mechanical Engineering Congress, Japan 2019 (2019): F25101. http://dx.doi.org/10.1299/jsmemecj.2019.f25101.

Full text

APA, Harvard, Vancouver, ISO, and other styles

22

Tchoshanov, M. A. "Learning Sciences Perspective on Engineering of Distance Learning. Part 1." Vysshee Obrazovanie v Rossii = Higher Education in Russia 30, no. 2 (2021): 33–49. http://dx.doi.org/10.31992/0869-3617-2021-30-2-33-49.

Full text

Abstract:

There is an on-going debate in the literature on theoretical underpinnings of distance learning. Scholars consider different theoretical perspectives including but not limited to theory of independence and autonomy, theory of industrialization, and theory of interaction and communication through the lens of a traditional Learning Theory approach. There is a lack of discussion on a potential role of a newly emerging field of Learning Sciences in framing the theory of distance learning. Thus, in this paper we provide a theoretical analysis of the Learning Sciences as a new approach to understand distance learning in the era of Information and Communication Technology (ICT). Learning sciences is an interdisciplinary field that studies teaching and learning. This emerging innovative field includes but is not limited to multiple disciplines such as cognitive science, educational psychology, anthropology, computer science, to name a few. The Learning Sciences’ major objective is to understand and design effective learning environments, including distance learning, based on the latest findings about the processes involved in human learning.

APA, Harvard, Vancouver, ISO, and other styles

23

Tchoshanov, M. A. "Learning Sciences Perspective on Engineering of Distance Learning. Part 2." Vysshee Obrazovanie v Rossii = Higher Education in Russia 30, no. 3 (2021): 43–58. http://dx.doi.org/10.31992/0869-3617-2021-30-3-43-58.

Full text

Abstract:

There is an on-going debate in the literature on theoretical underpinnings of distance learning. Scholars consider different theoretical perspectives including but not limited to theory of independence and autonomy, theory of industrialization, and theory of interaction and communication through the lens of a traditional Learning Theory approach. There is a lack of discussion on a potential role of a newly emerging field of Learning Sciences in framing the theory of distance learning. Thus, in this paper we provide a theoretical analysis of the Learning Sciences as a new approach to understand distance learning in the era of Information and Communication Technology (ICT). Learning Sciences is an interdisciplinary field that studies teaching and learning. This emerging innovative field includes but is not limited to multiple disciplines such as cognitive science, educational psychology, anthropology, computer science, to name a few. The Learning Sciences’ major objective is to understand and design effective learning environments, including distance learning, based on the latest findings about the processes involved in human learning.

APA, Harvard, Vancouver, ISO, and other styles

24

Lintern, Gavan. "Special issue on Cognitive Engineering." International Journal of Aviation Psychology 9, no. 3 (1999): 199–201. http://dx.doi.org/10.1207/s15327108ijap0903_1.

Full text

APA, Harvard, Vancouver, ISO, and other styles

25

Zednik, Carlos, and Frank Jäkel. "Bayesian reverse-engineering considered as a research strategy for cognitive science." Synthese 193, no. 12 (2016): 3951–85. http://dx.doi.org/10.1007/s11229-016-1180-3.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Bret, Michel, Marie-Hélène Tramus, and Alain Berthoz. "Interacting with an Intelligent Dancing Figure: Artistic Experiments at the Crossroads between Art and Cognitive Science." Leonardo 38, no. 1 (2005): 46–53. http://dx.doi.org/10.1162/leon.2005.38.1.46.

Full text

Abstract:

The authors (a neurophysiologist and two computer artists) give an account of a collaboration that took place within the framework of a study—cum— artistic experiment on virtual interactive figures at the boundary of art and cognitive science. This study, called “‘Intelligent’ Interactivity (Connectionism, Evolutionary Science and Artificial Life) in Digital Arts in Relation with the Physiology of the Perception of Action and Movement,” was supported by the Cognitique 2000 Program on Art and Cognition, an initiative of the French Ministry of Research.

APA, Harvard, Vancouver, ISO, and other styles

27

Tattegrain-Veste, Hέlène, Thierry Bellet, Annie Pauziέ, and Andrέ Chapon. "Computational Driver Model in Transport Engineering: COSMODRIVE." Transportation Research Record: Journal of the Transportation Research Board 1550, no. 1 (1996): 1–7. http://dx.doi.org/10.1177/0361198196155000101.

Full text

Abstract:

With regard to road safety issues, a deep understanding of the driver as a logic system is crucial to predict the most probable behavior according to the contextual elements. Knowledge and data about human functional abilities exist. But the problem is to organize and structure them. The development of a computational approach in driver modelization is addressed. In the first part, a brief historical overview is presented of available driver models in ergonomics and psychological areas, and the distinction between predictive and explicative models in an implementation perspective is the focus. In the second part, the computational aspect of the work is described, along with the software concepts, the cognitive modeling needs, and the implementation choices. Object-oriented techniques were chosen because they provide a modular overview of the general system and offer a convenient representation of cognitive processes. Object-oriented formalism, in particular object modeling technique diagrams, acts as a bridge between the two domains of computer science and the human sciences. The objective is to determine whether it is possible to implement reliably a driver model using the techniques from artificial intelligence and based on the theoretical knowledge from cognitive sciences research. This attempt to establish links between different scientific domains, requiring a common tool, is a challenge. A first step of a work that will have to be developed in a long-term time scale, taking into account its quite ambitious objective, is described.

APA, Harvard, Vancouver, ISO, and other styles

28

Jondral, Friedrich. "Cognitive Radio: A Communications Engineering View." IEEE Wireless Communications 14, no. 4 (2007): 28–33. http://dx.doi.org/10.1109/mwc.2007.4300980.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

Kirlik, Alex. "Relevance versus generalization in cognitive engineering." Cognition, Technology & Work 14, no. 3 (2012): 213–20. http://dx.doi.org/10.1007/s10111-011-0204-5.

Full text

APA, Harvard, Vancouver, ISO, and other styles

30

Wang, Yingxu, James A. Anderson, George Baciu, et al. "Perspectives on eBrain and Cognitive Computing." International Journal of Cognitive Informatics and Natural Intelligence 6, no. 4 (2012): 1–21. http://dx.doi.org/10.4018/jcini.2012100101.

Full text

Abstract:

Cognitive Informatics (CI) is a discipline spanning across computer science, information science, cognitive science, brain science, intelligence science, knowledge science, and cognitive linguistics. CI aims to investigate the internal information processing mechanisms and processes of the brain, the underlying abstract intelligence theories and denotational mathematics, and their engineering applications in cognitive computing and computational intelligence. This paper reports a set of nine position statements presented in the plenary panel of IEEE ICCI*CC’12 on eBrain and Cognitive Computers contributed from invited panelists who are part of the world’s renowned researchers and scholars in the field of cognitive informatics and cognitive computing.

APA, Harvard, Vancouver, ISO, and other styles

31

TOKOSUMI, Akifumi. "Cognitive Science and Kansei Engineering : Expansion from Knowledge Computing to Kansei Computing." Journal of the Society of Mechanical Engineers 102, no. 965 (1999): 203–5. http://dx.doi.org/10.1299/jsmemag.102.965_203.

Full text

APA, Harvard, Vancouver, ISO, and other styles

32

WATANUKI, Keiichi. "AI/IoT/VR/HMI-based Kansei, Emotional, and Cognitive Science and Engineering." Proceedings of Mechanical Engineering Congress, Japan 2020 (2020): F12101. http://dx.doi.org/10.1299/jsmemecj.2020.f12101.

Full text

APA, Harvard, Vancouver, ISO, and other styles

33

Reising, Dal Vernon C. "Book review of Cognitive Systems Engineering." International Journal of Aviation Psychology 9, no. 3 (1999): 291–302. http://dx.doi.org/10.1207/s15327108ijap0903_6.

Full text

APA, Harvard, Vancouver, ISO, and other styles

34

Zhong, Ying Hong, and Hong Wei Liu. "A Research Methodology Based on Design Science for the Construction of Cognitive Maps: The Case of a Chinese Steel Company’s Strategic Decision Making." Advanced Materials Research 204-210 (February 2011): 2098–102. http://dx.doi.org/10.4028/www.scientific.net/amr.204-210.2098.

Full text

Abstract:

In turbulent business environment, executives’ cognition plays an important role in their understanding and the process of decision making. Cognitive map helps the senior executives in their thought process. The construction of information-based cognitive map, however, is a wicked problem, which could hardly be tackled by hard systems methodologies. Design science provides a good solution. This paper puts forward a research methodology, which is divided into six activities, to build up an information systems (IS) based cognitive map for cognitive decision support. The methodology is demonstrated by a case study of a Chinese steel company’s strategic decision making.

APA, Harvard, Vancouver, ISO, and other styles

35

Wang, Yingxu, Gabriele Fariello, Marina L. Gavrilova, et al. "Perspectives on Cognitive Computers and Knowledge Processors." International Journal of Cognitive Informatics and Natural Intelligence 7, no. 3 (2013): 1–24. http://dx.doi.org/10.4018/ijcini.2013070101.

Full text

Abstract:

Cognitive Informatics (CI) is a contemporary multidisciplinary field spanning across computer science, information science, cognitive science, brain science, intelligence science, knowledge science, cognitive linguistics, and cognitive philosophy. CI aims to investigate the internal information processing mechanisms and processes of the brain, the underlying abstract intelligence theories and denotational mathematics, and their engineering applications in cognitive computing and computational intelligence. This paper reports a set of eleven position statements presented in the plenary panel of IEEE ICCI*CC’13 on Cognitive Computers and Knowledge Processors contributed from invited panelists who are part of the world’s renowned researchers and scholars in the field of cognitive informatics and cognitive computing.

APA, Harvard, Vancouver, ISO, and other styles

36

Henderson, Charles, José P. Mestre, and Linda L. Slakey. "Cognitive Science Research Can Improve Undergraduate STEM Instruction." Policy Insights from the Behavioral and Brain Sciences 2, no. 1 (2015): 51–60. http://dx.doi.org/10.1177/2372732215601115.

Full text

Abstract:

This article explores the directions needed to facilitate widespread adoption of the findings of cognitive science (CS) into undergraduate instruction in the disciplines of science, technology, engineering, and mathematics (STEM). The emerging research tradition of STEM discipline-based education research (DBER) is introduced briefly, with a focus on physics education research (PER). Examples of cognitive science research that are beginning to affect classroom practice are introduced, as well as examples that have direct implications for improving STEM instructional practices, yet remain largely unknown in the STEM community. Two barriers slow the implementation of CS findings in undergraduate STEM instruction. The first is lack of communication between cognitive science and STEM DBER researchers. The second is that, even when strong curricula and instructional practices are developed, there are many structural obstacles that make it difficult for STEM instructors to implement new instructional strategies. We provide an overview of current efforts to overcome these structural obstacles, and suggest policy implications for the cognitive science and DBER research communities that could facilitate the development, evaluation, and adoption of research-based instructional strategies in STEM undergraduate education.

APA, Harvard, Vancouver, ISO, and other styles

37

Zhou, Xiao Hong, Liang Wang, and Yi Cheng Hu. "Neuro-Industrial Engineering: Research and Practice." Applied Mechanics and Materials 268-270 (December 2012): 2022–25. http://dx.doi.org/10.4028/www.scientific.net/amm.268-270.2022.

Full text

Abstract:

With the development of science and technology, traditional Industrial Engineering (IE) gradually intersects with newly established Cognitive Neuroscience, Neuro-IE appears as a result. Means of Cognitive Neuroscience and Physiopsychology are mainly adopted in Neuro-IE and a great deal of research is done in many areas of production management and safety production, design of man-machine system and mentality, etc. Relevant results will show people a deep understanding of men’s decision-making and brain function and bring IE into Neuroscience, which plays an important role in scene design, production design, safety production et al.

APA, Harvard, Vancouver, ISO, and other styles

38

Hazzan, Orit. "Cognitive and social aspects of software engineering." ACM SIGCSE Bulletin 35, no. 3 (2003): 3–6. http://dx.doi.org/10.1145/961290.961516.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Kaur, Inderjit. "Science, Technology, Engineering and Mathematics (STEM) Comics as Cognitive Learning Enhancers for Malaysians." Malaysian Journal of Medical Sciences 26, no. 5 (2019): 158–59. http://dx.doi.org/10.21315/mjms2019.26.5.16.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Santisteban-Espejo, Antonio, Fernando Campos, Jesus Chato-Astrain, et al. "Identification of Cognitive and Social Framework of Tissue Engineering by Science Mapping Analysis." Tissue Engineering Part C: Methods 25, no. 1 (2019): 37–48. http://dx.doi.org/10.1089/ten.tec.2018.0213.

Full text

APA, Harvard, Vancouver, ISO, and other styles

41

Zimmerman, Corinne, and Steve Croker. "A Prospective Cognition Analysis of Scientific Thinking and the Implications for Teaching and Learning Science." Journal of Cognitive Education and Psychology 13, no. 2 (2014): 245–57. http://dx.doi.org/10.1891/1945-8959.13.2.245.

Full text

Abstract:

With increased focus on the importance of teaching and learning in the science, technology, engineering, and mathematics disciplines, both educational researchers and cognitive psychologists have been tackling the issues of how best to teach science concepts and scientific thinking skills. As a cultural activity, the practice of science by professional scientists is inherently prospective. Recent calls to make science education more “authentic” necessitate an analysis of the prospective, cumulative, and collaborative nature of science learning and science teaching. We analyze scientific thinking through the lens of prospective cognition by focusing on the anticipatory, social, situated, and multiscale aspects of engaging in science. We then address some of the implications for science education that result from our analysis.

APA, Harvard, Vancouver, ISO, and other styles

42

Ione, Amy. "Cognitive Science, Literature and the Arts." Leonardo 39, no. 3 (2006): 261–62. http://dx.doi.org/10.1162/leon.2006.39.3.261.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

Klein, G., S. Wiggins, and S. Deal. "Cognitive Systems Engineering: The Hype and the Hope." Computer 41, no. 3 (2008): 95–97. http://dx.doi.org/10.1109/mc.2008.81.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

Klein, Stacy S., and Robert D. Sherwood. "Biomedical Engineering and Cognitive Science as the Basis for Secondary Science Curriculum Development: A Three Year Study." School Science and Mathematics 105, no. 8 (2005): 384–401. http://dx.doi.org/10.1111/j.1949-8594.2005.tb18059.x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

45

Neerincx, Mark A. "Situated cognitive engineering for crew support in space." Personal and Ubiquitous Computing 15, no. 5 (2010): 445–56. http://dx.doi.org/10.1007/s00779-010-0319-3.

Full text

APA, Harvard, Vancouver, ISO, and other styles

46

Alalouch, Chaham. "Cognitive Styles, Gender, and Student Academic Performance in Engineering Education." Education Sciences 11, no. 9 (2021): 502. http://dx.doi.org/10.3390/educsci11090502.

Full text

Abstract:

Cognitive styles affect the learning process positively if tasks are matched to the cognitive style of learners. This effect becomes more pronounced in complex education, such as in engineering. We attempted to critically assess the effect of cognitive styles and gender on students’ academic performance in eight engineering majors to understand whether a cognitive style preference is associated with certain majors. We used the Cognitive Style Indicator (CoSI) with a sample of n = 584 engineering students. Multiple standard statistical tests, regression tree analysis, and cluster analysis showed that none of the three cognitive styles was exclusively associated with better performance. However, students who had a stronger preference for a cognitive style were more likely to perform better. Gender, the major, and students’ clarity about their cognitive style were shown to be the best predictors of academic performance. Female students performed better and were clearer about their preferred cognitive style, whereas male students were more capable of adapting to different learning tasks. Furthermore, certain engineering majors were shown to be associated with certain cognitive styles. We concluded the study with theoretical and practical implications for engineering education and suggestions for further research.

APA, Harvard, Vancouver, ISO, and other styles

47

Buchanan, Allen. "Cognitive enhancement and education." Theory and Research in Education 9, no. 2 (2011): 145–62. http://dx.doi.org/10.1177/1477878511409623.

Full text

Abstract:

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 stem-cell grown neural tissue, transcranial magnetic stimulation, computer/brain interface technologies, and (perhaps someday) modification of human embryos by genetic engineering and/or synthetic biology techniques. The same liberal—democratic values that support education as a public institutional endeavor also supply reasons for institutionalizing and publicly supporting BCE. Pursuing the goals of education may require changing what we have hitherto regarded as the individual’s ‘natural’ potential, even in the case of normal individuals, and this may require recourse to BCE. The prospect of BCE raises no novel issues of distributive justice. Like other beneficial innovations, BCEs have the potential to worsen existing unjust inequalities, but they also have the potential to ameliorate them.

APA, Harvard, Vancouver, ISO, and other styles

48

Wachowski, Witold M. "What it is like to be a pickpocket." Culture & Psychology 26, no. 4 (2019): 907–18. http://dx.doi.org/10.1177/1354067x19894934.

Full text

Abstract:

This study aims to show the socio-cognitive engineering of the pickpocket craft from the point of view of cognitive ecology. Being a pickpocket has a wider, existential status; studying it goes beyond the field of cognitive sciences. My ambitions are more modest: I try to show that the question about what it is like to be someone like a pickpocket is also a question about the cognitive structure of his or her activity space. In this light, I analyze some aspects of the reality presented in the movie Pickpocket by Robert Bresson. From the ecological point of view, scenes from the old movie present pickpocketing techniques in the context of the opportunities and constraints of a given environment. I claim that studies like this require integrating certain conceptual tools, like distributed cognition approach, ecological psychology, and cognitive studies of design.

APA, Harvard, Vancouver, ISO, and other styles

49

Kim, DaeEun. "Special Feature on Advanced Mobile Robotics." Applied Sciences 9, no. 21 (2019): 4686. http://dx.doi.org/10.3390/app9214686.

Full text

Abstract:

Mobile robots and their applications are involved with many research fields including electrical engineering, mechanical engineering, computer science, artificial intelligence and cognitive science [...]

APA, Harvard, Vancouver, ISO, and other styles

50

Agustin, Mita Dwi, Albertus Djoko Lesmono, and Heny Mulyo Widodo. "MODEL PROBLEM BASED LEARNING (PBL) DENGAN PENDEKATAN SCIENCE TECHNOLOGY ENGINEERING MATHEMATICS (STEM) DALAM PEMBELAJARAN FISIKA MATERI ELASTISITAS DI KELAS XI MIPA 4 SMA NEGERI 2 JEMBER." JURNAL PEMBELAJARAN FISIKA 9, no. 2 (2020): 50. http://dx.doi.org/10.19184/jpf.v9i1.17964.

Full text

Abstract:

The Problem Based Learning (PBL) model has been applied in Indonesia for a long time. The Problem Based Learning (PBL) model with the approach of Science, Technology, Engineering, and Mathematics (STEM) is new in the world of education. When students are introduced to the new learning model, it will make students have a high curiosity and a great desire to learn. Having a great desire to learn will affect student learning outcomes. Problem Based Learning (PBL) model with the approach of Science, Technology, Engineering, and Mathematics (STEM) is expected to improve student learning outcomes in the cognitive domain. This study aims to describe student learning outcomes using the Problem Based Learning (PBL) model which is integrated with Science, Technology, Engineering, and Mathematics (STEM) on the subject of elasticity. This type of research is a true experimental research design with pretest-posttest control-design conducted in class XI MIPA 4. The conclusion of this study is the Problem Based Learning (PBL) model with the approach of Science, Technology, Engineering, and Mathematics (STEM) can improve student learning outcomes in the cognitive domain in learning physics in class XI MIPA 4 SMA NEGERI 2 JEMBER.

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!