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Title: Focused Self-Explanations Lead to the BestLearning Outcomes in a Digital Learning Game
Authors: McLaren, Bruce M.
Richey, J. Elizabeth
Nguyen, Huy Anh
Mogessie, Michael
Keywords: Learning Sciences
Issue Date: 2022
Publisher: International Society of the Learning Sciences
Citation: McLaren, B. M., Richey, J. E., Nguyen, H. A., & Mogessie, M. (2022). Focused self-explanations lead to the BestLearning outcomes in a digital learning game. In Chinn, C., Tan, E., Chan, C., & Kali, Y. (Eds.), Proceedings of the 16th International Conference of the Learning Sciences - ICLS 2022 (pp. 1229-1232). International Society of the Learning Sciences.
Abstract: Prompted self-explanation, in which learners are induced to explain how they have solved problems, is a powerful instructional technique. Self-explanation can be prompted within learning technology by asking learners to construct their own self-explanations or select explanations from a menu. The menu-based approach has led to the best learning outcomes in the relatively few cases it has been studied in the context of digital learning games, contrary to some self-explanation theory. In a classroom study of 214 5th and 6th graders, in which the students played a digital learning game, we compared three forms of prompted self-explanation: menu-based, scaffolded, and focused (i.e., open-ended text entry, but with a focused prompt). Students in the focused condition learned more than students in the menu-based condition at delayed posttest, with no other learning differences between the conditions. This suggests that focused self-explanations may be especially beneficial for retention and deeper knowledge.
Description: Short Paper
Appears in Collections:ISLS Annual Meeting 2022

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