The Development and Preliminary Evaluation of Learner’s Flow State of an Online Decision-making Detective Game

60959 Information integration and decisions-making competence have gained much attention not only many fields. Assisting learners to have efficient logical reasoning and to make accurate decisions, and further form their decision-making patterns is a great issue. Therefore, exploring learners’ status…

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60959

Information integration and decisions-making competence have gained much attention not only many fields. Assisting learners to have efficient logical reasoning and to make accurate decisions, and further form their decision-making patterns is a great issue. Therefore, exploring learners’ status and process in the decision-making game is the foundation for future learning and teaching. The study developed an online detective game to explore learners’ flow state as a pilot study. The scenario of this game is to provide the exact position of the missing girl with limited time. The learning goal of this game is to analyze the clues in the game, applying any online tools and information to locate the missing girl’s position precisely. There are 35 participants above 20 years old from E-recruitment and participate in the study online. Preliminary results suggested that participants’ flow state revealed their high engagement in the game. According to one sample t-test, all nine dimensions of flow are higher than median 3. The learners revealed that they perceived well flow antecedents, especially challenge–skill balance, goals of an activity, control are high above 3.5. Even action–awareness merging which is relatively difficult to achieve high in similar game-based learning was high as well. As for flow experience, concentration, the transformation of time, and autotelic experience were high above 4. The designs and mechanism of this game based on cognitive theory are clear to guide learner joining and engage learners in the game. Future study can explore the effects of provided scaffoldings and learning behavior patterns.

Huei-Tse Hou, National Taiwan University of Science and Technology, Taiwan
Chih-Chen Kuo, National Taiwan University of Science and Technology, Taiwan
Tzu Hsuan Wang, National Taiwan University of Science and Technology, Taiwan

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