Abstract
This chapter describes and discusses a study that has as its focus the theory-driven and collaborative design of interventions in higher education using a design-based research approach. The study investigates how to integrate computational thinking (CT) with computational things in the context of two case studies involving teachers and students from Media Studies and Philosophy. The theoretical framework consists of CT, computational things, situated and embodied cognition and learning, and design for learning. This framework has informed the preliminary general-substantive and general-procedural design principles that have guided the design of interventions. The interventions designed consist of computational things in the form of idea generation tools that support students in decomposing core models and provide students with tangible representations of abstract subject concepts. Furthermore, the tools require students to engage with algorithmic processes and compute with concepts. Results from the first iteration show there is potential in the tangible representations of abstractions and in the decomposition of core models. However, some students are unfamiliar with working at this level of decomposition and abandon algorithmic processing to engage in abstract discussion. Thus, the most promising potential is the computational thing as conversation tool and object to think with and secondarily the computational thing as idea generation tool.
References
Abrahamson, D., & Bakker, A. (2016). Making sense of movement in embodied design for mathematics learning. Cognitive Research: Principles and Implications, 1(1), 33.
Arthur, W. B. (2009). The nature of technology: What it is and how it evolves. New York, NY: Simon and Schuster.
Barab, S., & Squire, K. (2004). Design-based research: Putting a stake in the ground. The Journal of the Learning Sciences, 13(1), 1–14.
Bonet, E. (2011). Comments on the logic and rhetoric of Ramon Llull. In A. Fidora & C. Sierra (Eds.), Ramon Llull, from the Ars Magna to artificial intelligence. Barcelona, Spain: Artificial Intelligence Research Institute.
Braun, V., & Clarke, V. (2006). Using thematic analysis in psychology. Qualitative Research in Psychology, 3(2), 77–101.
Brown, J. S., Collins, A., & Duguid, P. (1989). Situated cognition and the culture of learning. Educational Researcher, 18(1), 32–42. https://doi.org/10.3102/0013189X018001032
Caeli, E. N., & Yadav, A. (2020). Unplugged approaches to computational thinking: A historical perspective. TechTrends, 64(1), 29–36.
Caspersen, M. E., Iversen, O. S., Nielsen, M., Hjorth, H. A., & Musaeus, L. H. (2018). Computational thinking–hvorfor, hvad og hvordan?: Efter opdrag fra Villum Fondens bestyrelse.
Clarke, D., & Chan, M. C. E. (2018). The use of video in classroom research: Window, lens, or mirror. In G. A. Lihua Xu, W. Widjaja, & D. Clarke (Eds.), Video-based research in education (pp. 5–18). London, UK: Routledge.
Cobb, P., Confrey, J., DiSessa, A., Lehrer, R., & Schauble, L. (2003). Design experiments in educational research. Educational Researcher, 32(1), 9–13.
Creswell, J. W., Hanson, W. E., Clark Plano, V. L., & Morales, A. (2007). Qualitative research designs: Selection and implementation. The Counseling Psychologist, 35(2), 236–264.
Curran, J. R., Schulz, K. A., & Hogan, A. (2019). Coding and computational thinking – What is the evidence? Retrieved from https://education.nsw.gov.au/content/dam/main-education/teaching-and-learning/education-for-a-changing-world/media/documents/Coding-and-Computational-Report_A.pdf
de Jong, I., & Jeuring, J. (2020). Computational thinking interventions in higher education: A scoping literature review of interventions used to teach computational thinking. Koli Calling’20: Proceedings of the 20th Koli Calling International Conference on Computing Education Research.
Dede, C. (2004). If design-based research is the answer, what is the question? A commentary on Collins, Joseph, and Bielaczyc; diSessa and Cobb; and Fishman, Marx, Blumenthal, Krajcik, and Soloway in the JLS special issue on design-based research. The Journal of the Learning Sciences, 13(1), 105–114.
Denning, P. J., & Tedre, M. (2021). Computational thinking: A disciplinary perspective. Informatics in Education, 20(3), 361–390. https://doi.org/10.15388/infedu.2021.21
Dohn, N. B. (2021). Kapitel 1. Computational thinking – indplacering i et landskab af it-begreber. In N. B. Dohn, R. Mitchell, & R. Chongtay (Eds.), Computational thinking – teoretiske, empiriske og didaktiske perspektiver. Frederiksberg, DenmarK: Samfundslitteratur.
Dohn, N. B., & Hansen, J. J. (2018). Design in educational research – Clarifying conceptions and presuppositions. In N. B. Dohn (Ed.), Designing for learning in a networked world. London, UK: Routledge.
Dohn, N. B., Hansen, J. J., & Goodyear, P. (2020). Basic design principles for learning designs to support knowledge transformation. In N. B. Dohn, S. B. Hansen & J. J. Hansen (eds), Designing for situated knowledge transformation. London, UK: Routledge.
Dohn, N. B., Kafai, Y., Mørch, A., & Ragni, M. (2022). Survey: Artificial intelligence, computational thinking and learning. KI – Künstliche Intelligenz. https://doi.org/10.1007/s13218-021-00751-5
Dohn, N. B., Mitchell, R., & Chongtay, R. (2021). Introduction. In N. B. Dohn, R. Mitchell, & R. Chongtay (Eds.), Computational thinking – teoretiske, empiriske og didaktiske perspektiver. Samfundslitteratur.
Flyvbjerg, B. (2010). Fem misforståelser om casestudiet (Five misunderstandings about case-study research) (pp. 463–487). Kvalitative metoder, København: Hans Reitzels Forlag.
Goodyear, P. (2005). Educational design and networked learning: Patterns, pattern languages and design practice. Australasian Journal of Educational Technology, 21(1).
Grover, S., & Pea, R. (2018). Computational thinking: A competency whose time has come. In Computer science education: Perspectives on teaching and learning in school (p. 19).
Jensen, P. M. (2018). Mediesystemer. In P. S. Lauridsen & E. Svendsen (Eds.), Medieteori (pp. 175–190). Samfundslitteratur.
Lave, J. (1988). Cognition in practice: Mind, mathematics and culture in everyday life. Cambridge, MA: Cambridge University Press.
Lave, J., & Wenger, E. (1991). Situated learning: Legitimate peripheral participation. Cambridge, MA: Cambridge University Press.
Lippert-Rasmussen, K., Midtgaard, S. F., Nielsen, L., & Olsen, T. V. (2020). Politisk teori og filosofi. Kobenhavn, DenmarK: Djøf Forlag.
Lyon, J. A., & Magana, A. J. (2020). Computational thinking in higher education: A review of the literature. In Computer applications in engineering education, 28(5), 1174–1189.
Mikkonen, J., & Fyhn, C. (2021). Kapitel 12: Læring af computational thinking ved udvikling af computational things gennem Storycoding. In N. B. Dohn, R. Mitchell, & R. Chongtay (Eds.), Computational thinking – teoretiske, empiriske og didaktiske perspektiver. Samfundslitteratur.
Pande, P. (2021). Learning and expertise with scientific external representations: An embodied and extended cognition model. Phenomenology and the Cognitive Sciences, 20(3), 463–482.
Papert, S. (1980). Mindstorms – Children, computers and powerful ideas. New York, NY: Basic Books.
Polanyi, M. (1957). Problem solving. The British Journal for the Philosophy of Science, 8(30), 89–103.
Pollock, L., Mouza, C., Guidry, K. R., & Pusecker, K. (2019). Infusing computational thinking across disciplines: Reflections & lessons learned. Paper presented at the Proceedings of the 50th ACM Technical Symposium on Computer Science Education.
Reeves, T. (2006). Design research from a technology perspective. In Educational Design Research (pp. 64–78). London, UK: Routledge.
Reimann, P. (2011). Design-based research. In L. Markauskaite, P. Freebody, & J. Irwin (Eds.), Methodological choice and design: Scholarship, policy and practice in social and educational research (pp. 37–50). Dordrecht, Netherlands: Springer.
Rienecker, L., & Jørgensen, P. S. (2017). Den gode opgave – håndbog i opgaveskrivning på videregående uddannelser: Samfundslitteratur.
Sales, T. (1997). Llull as computer scientist or why Llull was one of us. Paper presented at the International AMAST workshop on aspects of real-time systems and concurrent and distributed software.
Schoenfeld, A. H. (1987). Pólya, problem solving, and education. Math Mag, 60(5), 283–291. https://doi.org/10.1080/0025570X.1987.11977325
Shute, V. J., Sun, C., & Asbell-Clarke, J. (2017). Demystifying computational thinking. Educational Research Review, 22, 142–158.
Skiena, S. S. (2020). The algorithm design manual. Cham, Switzerland: Springer.
Snelson, C., Yang, D., & Temple, T. (2021). Addressing the challenges of online video analysis in qualitative studies: A worked example from computational thinking research. The Qualitative Report, 26(6), 1974–1988. https://doi.org/10.46743/2160-3715/2021.4734
Tang, K.-Y., Chou, T.-L., & Tsai, C.-C. (2020). A content analysis of computational thinking research: An international publication trends and research typology. The Asia-Pacific Education Researcher, 29(1), 9–19.
Uckelman, S. L. (2010). Computing with concepts, computing with numbers: Llull, Leibniz, and Boole. Berlin/Heidelberg.
Valente, A., & Marchetti, E. (2020). Playful learning and shared computational thinking: The PaCoMa case study. Paper presented at the Proceedings of the 28th International Conference on Computers in Education, ICCE 2020.
van den Akker, J. (1999). Principles and methods of development research. In Design approaches and tools in education and training (pp. 1–14). Dordrecht, Netherlands: Springer.
Vestergaard, J. (2007). Hvad er et mediesystem, og hvordan analyserer man det? In K. Frandsen & H. Bruun (eds), Tv-produktion-nye vilkår (pp. 55–82). København, Denmark: Samfundslitteratur.
Wang, F., & Hannafin, M. J. (2005). Design-based research and technology-enhanced learning environments. Educational Technology Research and Development, 53(4), 5–23.
Wing, J. M. (2006). Computational thinking. Communications of the ACM, 49(3), 33–35.
Wing, J. M. (2010). Computational thinking: What and why? Retrieved from https://www.cs.cmu.edu/~CompThink/resources/TheLinkWing.pdf
Xu, W., & Zammit, K. (2020). Applying thematic analysis to education: A hybrid approach to interpreting data in practitioner research. International Journal of Qualitative Methods, 19, 1609406920918810.
Yin, R. K. (2003). Case study research: Design and methods (Vol. 5, 3rd ed.). Thousand Oaks, CA: Sage.
Acknowledgments
This work is part of the overall project Designing for situated computational thinking with computational things which is funded by the Independent Research Fund Denmark. All opinions are the author’s and do not necessarily represent those of the funding agency.
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Christensen, IM.F. (2023). Integrating Computational Thinking in Humanistic Subjects in Higher Education. In: Spector, M.J., Lockee, B.B., Childress, M.D. (eds) Learning, Design, and Technology. Springer, Cham. https://doi.org/10.1007/978-3-319-17727-4_180-2
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Integrating Computational Thinking in Humanistic Subjects in Higher Education- Published:
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DOI: https://doi.org/10.1007/978-3-319-17727-4_180-2
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DOI: https://doi.org/10.1007/978-3-319-17727-4_180-1