Computing in K-12 STEM

A Phenomenological Approach

Our research on computational thinking in K-12 STEM education is grounded in a phenomenological approach (Sengupta, Dickes & Farris, 2018). This means that our goal is to develop a richer understanding of the experiences of computing in K-12 STEM from the perspectives of the students and the teachers. Our approach stands in contrast to the more prevalent technocentric approaches (Papert, 1987), where all questions about and "measures" of the experience of computing are reduced to the production of technological artifacts.

"Big-picture" papers: These papers sketch a phenomenological agenda for computing in K-12 STEM

  1. Sengupta, P., Dickes, A., & Farris, A. (2018). Toward a Phenomenology of Computational Thinking in STEM Education. In: Khine, M.S. (Ed.): Computational Thinking in STEM: Foundations and Research Highlights. Download
  2. Sengupta, P., Dickes, A.C., Farris, A.V., Karan, A., Martin, K., & Wright, M. (2015). Programming in K12 Science Classrooms. Communications of the ACM. Download
  3. Sengupta, P., Kinnebrew, J. S., Basu, S., Biswas, G., & Clark, D. (2013). Integrating computational thinking with K-12 science education using agent-based computation: A theoretical framework. Education and Information Technologies, 18(2), 351-380. Download

Empirical Studies of Computing in STEM

Note: Each of these studies proposes a "metaphor" for computational thinking, grounded in how the students and teachers make sense of and experience computation as part of the STEM classrooms and disciplinary contexts. Papers on teacher education and foregrounding teacher voice are marked #teachervoice.

Computational Thinking as Learning to Interpret Measurement and Motion

Farris, A., Dickes, A. C., & Sengupta, P. (2019). Learning to Interpret Measurement and Motion in Fourth Grade Computational Modeling. Science and Education, 28(8), 927-956. Download

Computational Thinking as Mechanistic Reasoning

Dickes, A. C., Sengupta, P., Farris, A. V., & Basu, S. (2016). Development of Mechanistic Reasoning and Multilevel Explanations of Ecology in Third Grade Using Agent‐Based Models. Science Education, 100(4), 734-776. Download

Computational Thinking as Epistemological Play

Sengupta, P., Kim, B., & Shanahan, M-.C. (2019). Playfully Coding Science: Views from Preservice Science Teacher Education. In: Sengupta, P., Kim, B., & Shanahan, M-.C. (Eds.). Critical, Transdisciplinary and Embodied Approaches in STEM Education. (pp 177 - 195). Springer. [LINK COMING SOON] #teachervoice

Computational Thinking as Perspectival Reasoning

Farris, A.V., & Sengupta, P. (2014). Perspectival Computational Thinking for Learning Physics: A Case Study of Collaborative Agent-based Modeling. Proceedings of the 12th International Conference of the Learning Sciences. (ICLS 2014), pp 1102 - 1107. Download

Computational Thinking as Designing for Others

Sengupta, P., Krishnan, G., Wright, M., & Ghassoul, C. (2015). Mathematical Machines & Integrated STEM: An Intersubjective Constructionist Approach. Communications in Computer and Information Science, Vol. 510, 272-288. Download

Computational Thinking in Conversations about Race

Hostetler, A., Sengupta, P., & Hollett, T. (2018). Unsilencing critical conversations in social-studies teacher education using agent-based modeling. Cognition and Instruction, 36(2), 139-170. Download #teachervoice

Computational Thinking as Aesthetic Experience

Farris, A. V., & Sengupta, P. (2016). Democratizing children's computation: Learning computational science as aesthetic experience. Educational Theory, 66(1-2), 279-296. Download

Computational Thinking as Disciplined Interpretations

Farris, A.V., Dickes, A.C., & Sengupta, P. (2016). Development of Disciplined Interpretation Using Computational Modeling in the Elementary Science Classroom. In: Proceedings of the 12th International Conference of the Learning Sciences (ICLS 2016), pp 282 – 289. Download

Computational Thinking as Mathematizing

Sengupta, P., Brown, B., Rushton, K., & Shanahan, M. C. (2018). Reframing coding as “Mathematization” in the K12 classroom: Views from teacher professional learning. Alberta Science Educational Journal, 45(2), 28-36. Download #teachervoice

Computational Thinking as Revoicing, Bridging and Stuttering Across Spaces

Van Eaton, G., Clark, D. B., & Sengupta, P. (2018). Revoicing, Bridging, and Stuttering Across Formal, Physical, and Virtual Spaces. International Journal of Gaming and Computer-Mediated Simulations, 10(2), 21-46. Download #teachervoice

Computational Thinking using SocioMathematical Norms

Dickes, A.C., Farris, A.V., & Sengupta, P. (2016). Integrating Agent-based Programming with Elementary Science: The Role of Sociomathematical Norms. In: Proceedings of the 24th International Conference on Computers in Education, pp 129 - 138. Download #teachervoice

Computational Thinking as Boundary Play in Public

Sengupta, P. & Shanahan, M.-C. (2017). Boundary Play and Pivots in Public Computation: New Directions in STEM Education. International Journal of Engineering Education, Vol. 33 (3), pp. 1124–1134. Download

Computational Thinking as Playing Modeling Games

Krinks, K. D., Sengupta, P., & Clark, D. B. (2019). Modeling Games in the K-12 Science Classroom. International Journal of Gaming and Computer-Mediated Simulations (IJGCMS), 11(1), 31-50. Download #teachervoice