Sanjay Chandrasekharan
- Associate Professor
Homi Bhabha Centre for Science Education
Tata Institute of Fundamental Research
- Adjunct Faculty
Interdisciplinary Program in Educational Technology
Indian Institute of Technology Bombay
- Research Areas
- Education
- Employment
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The Learning Sciences Research Group
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CV
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Assorted Stuff
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Courses
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Talks
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Publications
Learning Sciences, New Computational Media, Distributed Cognition, Embodied Cognition, Sustainability
Ph.D. Cognitive Science, Carleton University, Ottawa, Canada
Postdoctoral Fellow, School of Interactive Computing, Georgia Institute of Technology, Atlanta, USA
Postdoctoral Fellow, Cognitive and Motor Neuroscience Lab, Faculty of Kinesiology, University of Calgary, Canada
Senior Lecturer, Centre for Behavioral and Cognitive Sciences, University of Allahabad, India
Predoctoral Fellow, Adaptive Behavior and Cognition Group, Max Planck Institute for Human Development, Berlin, Germany
Cognition, Cognitive Development, Learning Theories, 2018
Advanced Topics in Cognition, 2018
Keynote Address, IEEE Technology for Education Conference, Kollam, Kerala, India, 2014
Keynote Address, Model-based Reasoning Conference, Sestri Levante, Italy, 2015
Google Scholar Page
ACM author page
17. Rahaman, J., Agrawal, H., Srivastava, N., Chandrasekharan, S. (2018). Recombinant enaction: manipulatives generate new procedures in the imagination, by extending and recombining action spaces. Cognitive Science, 42(2), 370–415.
16. Chandrasekharan, S., Nersessian, N.J. (2018). Rethinking correspondence: how the process of constructing models leads to discoveries and transfer in the bioengineering sciences.. Synthese, DOI 10.1007/s11229-017-1463-3
15.Date, G., Chandrasekharan, S. (2017). Beyond Efficiency: Engineering for Sustainability Requires Solving for Pattern, Engineering Studies, DOI: 10.1080/19378629.2017.1410160
14. Dutta, D., Chandrasekharan,S. (2017). Doing to being: farming actions in a community coalesce into pro-environment motivations and values. Environmental Education Research, 1-19.
13. Pande, P., & Chandrasekharan, S. (2017). Representational competence: Towards a distributed and embodied cognition account. Studies in Science Education,53(1), 1-43.
12. Chandrasekharan, S. (2016). Beyond Telling: Where New Computational Media is Taking Model-Based Reasoning. In Model-Based Reasoning in Science and Technology, Volume 27 of the series Studies in Applied Philosophy, Epistemology and Rational Ethics, pp 471-487, Springer, Heidelberg.
11. Chandrasekharan, S., Nersessian, N.J. (2015). Building Cognition: the Construction of Computational Representations for Scientific Discovery. Cognitive Science, 39, 1727–1763.
10. Chandrasekharan, S. (2014). Becoming Knowledge: Cognitive and Neural Mechanisms that Support Scientific Intuition. In Osbeck, L., Held, B.(Eds.). Rational Intuition: Philosophical Roots, Scientific Investigations. Cambridge University Press. New York.
9. Chandrasekharan, S. (2013). The Cognitive Science of Feynmen. Metascience, 22, 647–652
8. *Aurigemma, J., Chandrasekharan, S., Newstetter, W., Nersessian, N.J. (2013). Turning experiments into objects: the cognitive processes involved in the design of a lab-on-a-chip device. Journal of Engineering Education, 102(1), 117-140.
*All authors contributed equally
7. Chandrasekharan, S., Tovey, M. (2012). Sum, Quorum, Tether: design principles for external representations that promote sustainability. Pragmatics and Cognition, 20 (3), 447-482.
6. Chandrasekharan, S., Binsted, G. Ayres, F., Higgins, L., Welsh, T.N. (2012). Factors that Affect Action Possibility Judgments: Recent Experience with the Action and the Current Body State. The Quarterly Journal of Experimental Psychology, 65(5), 976-993.
5. Chandrasekharan, S., Mazalek, A., Chen, Y., Nitsche, M., Ranjan, A. (2010). Ideomotor Design: using common coding theory to derive novel video game interactions. Pragmatics & Cognition, 18 (2), 313-339.
4. Chandrasekharan, S., Osbeck, L. (2010). Rethinking Situatedness: Environment Structure in the Time of the Common Code. Theory & Psychology, 20 (2), 171-207.
3. Chandrasekharan, S. (2009). Building to discover: a common coding model. Cognitive Science, 33 (6), 1059-1086.
2. Chandrasekharan, S., Stewart T.C. (2007). The origin of epistemic structures and proto-representations. Adaptive Behavior, 15 (3), 329-353.
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1. Chandrasekharan, S. (2006). Money as Epistemic Structure. Comment on the target article "Money as tool, money as drug: The biological psychology of a strong incentive", by Stephen E. G. Lea and Paul Webley, Behavioral and Brain Sciences, 29 (2), 183-184.
