Abstract
Creative thinking is the ability to generate new ideas in various ways due to the adaptability of existing thinking as well as the performance of problem solving. This can foster student’s creative thinking. This study was aimed to synthesize the designing framework of constructivist digital learning environment model to enhance creative thinking for undergraduate students. Research target groups were (1) 90 undergraduate students registered in the faculty of Education and (2) 3 experts for this designing framework. Model Research phase 1 Model Development was employed. Qualitative data was collected by Document Analysis and Survey method, and the data was then analyzed by interpreting and concluding. Research results revealed that the designing framework comprised 5 stages as (1) Activating cognitive structure and creative thinking (2) Supporting cognitive equilibrium (3) Enhancing cognitive structure accommodation (4) Enhancing creative thinking and (5) Supporting and fostering knowledge construction. Besides, the model components consisted of 7 parts as (1) Problem based (2) Learning resources (3) Collaboration center (4) Cognitive tools center (5) Creative thinking center (6) Scaffolding center (7) Coaching center. The evaluation results were hence shown that the designing framework had theoretical validity and consistent with claimed theories.
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Acknowledgements
This research was supported by Ph.D. Program in Educational Technology, Faculty of Education, Research Group for Innovation and Cognitive Technology, Khon Kaen, University, and Research and Technology Transfer Affairs Division, Khon Kaen University, and Graduate School, Khon Kaen University which hereby giving the thankfulness all through this.
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Wonganu, P., Chaijaroen, S., Vongtathum, P. (2019). Designing Framework of Constructivist Digital Learning Environment Model to Enhance Creative Thinking for Undergraduate Students. In: Rønningsbakk, L., Wu, TT., Sandnes, F., Huang, YM. (eds) Innovative Technologies and Learning. ICITL 2019. Lecture Notes in Computer Science(), vol 11937. Springer, Cham. https://doi.org/10.1007/978-3-030-35343-8_26
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