Sanjay Chandrasekharan
- Associate Professor (G)
Homi Bhabha Centre for Science Education
- Adjunct Faculty
Interdisciplinary Program in Educational Technology
Indian Institute of Technology Bombay
- Associate Editor (2020-2022)
- Advisory Board Member
Studies in Applied Philosophy, Epistemology, and Rational Ethics
- Research Areas
- Education
- Training
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The Learning Sciences Research Group
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Courses
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Keynote Talks
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Selected Publications
Learning Sciences, New Computational Media, Science Cognition, Model-based Imagination and Reasoning, Philosophy of Modeling
Building Cognition, 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, Conceptual Development, and Conceptual Change, 2022
Advanced Topics in Cognition, 2023
Keynote Speaker, Engineering for Research Symposium 2020, ThoughtWorks India
Review Talk, Episteme 8
, Mumbai, 2020
Keynote Speaker, Model-based Reasoning Conference, Sestri Levante, Italy, 2015
Keynote Speaker, IEEE Technology for Education Conference, Kollam, Kerala, India, 2014
Google Scholar Page
ACM Author Page
24. Mashood, K. K., Khosla, K., Prasad,A., Sasidevan, V., Ashefas, M., Jose, C., Chandrasekharan,S. (2022). Participatory approach to introduce computational modeling at the undergraduate level, extending existing curricula and practices: Augmenting derivations. Physical Review Physics Education Research, 18, 020136
23. Pande, P., Chandrasekharan, S. (2021). Expertise as Sensorimotor Tuning: Perceptual Navigation Patterns Mark Representational Competence in Science. Research in Science Education, 52(2), 725-747.
22. Karnam, D.P., Agrawal, H., Parte, P., Ranjan, S., Borar, P., Kurup, P., Joel, A. J., Srinivasan, P. S., Suryawanshi, U., Sule, A., & Chandrasekharan, S. (2021). Touchy-Feely Vectors: a compensatory design approach to support model-based reasoning in developing country classrooms. Journal of Computer Assisted Learning, 37(2), 446-474.
21. Chandrasekharan, S., Nersessian, N.J. (2021). Rethinking correspondence: how the process of constructing models leads to discoveries and transfer in the bioengineering sciences.. Synthese, 198(21), 1-30.
20. Date, G., Dutta, D., Chandrasekharan, S.(2019). Solving for Pattern: An Ecological Approach to Reshape the Human Building Instinct. Environmental Values. 30(1), 65-92.
19. 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.
Follow-up paper, Proceedings of Cogsci 2019
18. Date, G., Chandrasekharan, S. (2017). Beyond Efficiency: Engineering for Sustainability Requires Solving for Pattern, Engineering Studies, 10(1), 12-37
17. 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.
16. Pande, P., & Chandrasekharan, S. (2017). Representational competence: Towards a distributed and embodied cognition account. Studies in Science Education, 53(1), 1-43.
15. 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.
14. Chandrasekharan, S., Nersessian, N.J. (2015). Building Cognition: the Construction of Computational Representations for Scientific Discovery. Cognitive Science, 39, 1727–1763.
13. 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.
12. Chandrasekharan, S. (2013). The Cognitive Science of Feynmen. Metascience, 22, 647–652
11. *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
10. Welsh, T. N., Wong, L., & Chandrasekharan, S. (2013). Factors that affect action possibility judgments: The assumed abilities of other people. Acta Psychologica, 143(2), 235-244.
9. Chandrasekharan, S., Nersessian, N.J., Subramanian, V. (2012). Computational Modeling: Is this the end of thought experiments in science?. In J. Brown, M. Frappier, & L. Meynell, eds. Thought Experiments in Philosophy, Science and the Arts. London: Routledge, 239-260.
8. Chandrasekharan, S., Tovey, M. (2012). Sum, Quorum, Tether: design principles for external representations that promote sustainability. Pragmatics and Cognition, 20 (3), 447-482.
7. 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.
Follow-up paper, Proceedings of Cogsci 2015
6. Villiger, M., Chandrasekharan, S., & Welsh, T. N. (2011). Activity of human motor system during action observation is modulated by object presence. Experimental Brain Research, 209(1), 85-93.
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.
Python Code, Interactive Simulation
Follow-up paper, Proceedings of Cogsci 2019
Interactive Simulation
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.
