Abstract
AbstractUnderstanding the reasoning in the design process is essential to comprehend design practice and promote students’ learning. Followingly, to effectively support students through the design process, it is crucial to pay attention to their reasoning. Therefore, in this study, we have built a model for students’ reasoning in the design process in technology education to be used as a utility in further research. Here, reasoning is viewed as the process of using premises to reach a conclusion. Drawing from philosophy of technology and philosophy of technology education, the model introduces relevant concepts that are particularly useful in technology education. The model incorporates two types of reasoning: means-end reasoning and cause-effect reasoning. Means-end reasoning involves identifying actions to achieve a desired end. While cause-effect reasoning leads to conclusions in the form of beliefs about causes, effects, consequences, and side-effects, which is important when predicting and evaluating in the design process. The model highlights the interplay between these two types of reasoning, where students would constantly move between them in the design process. The model involves a holistic view of the reasoning and the design process, rather than taking a purely instrumental approach. That the model fuse two types of reasoning, makes it applicable at any point in the design process and across different contexts in technology education. Overall, the model provides a comprehensive view of reasoning in the design process in technology education.
Funder
Royal Institute of Technology
Publisher
Springer Science and Business Media LLC
Reference50 articles.
1. Alamäki, A. (2000). Technological reasoning as a human side of technological innovation. In Innovation and Diffusion in Technology Education: Proceedings of PATT-10 Conference (pp. 9–15). PATT.
2. Ankiewicz, P. J. (2019). Andrew Feenberg: Implications of critical theory for technology education. In J. R. Dakers, J. Hallström, & M. J. de Vries (Eds.), Reflections on Technology for Educational Practitioners (pp. 115–130). Brill Sense.
3. Autio, O., & Soobik, M. (2017). Technological knowledge and reasoning in Finnish and Estonian technology education. International Journal of Research in Education and Science, 3(1), 193–202.
4. Buckley, J., Seery, N., Canty, D., & Gumaelius, L. (2018). Visualization, inductive reasoning, and memory span as components of fluid intelligence: Implications for technology education. International Journal of Educational Research, 90, 64–77.
5. Citrohn, B., Stolpe, K., Svensson, M., & Bernard, J. (2022). Affordances of models and modelling: A study of four technology design projects in the Swedish secondary school. Design and Technology Education: An International Journal, 27(3), 58–75.
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