Learning in Doing: A Model of Design and Assessment for Using New Interaction in Educational Game

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Abstract

To put into practice what has been learned is considered as one of the most important education objectives. In the traditional class, it is difficult for learners to engage in practices since teachers usually convey knowledge and experience by speaking or simple demonstrations, like using slides and videos. This brings obstacles for learners to apply what they have learned to solve real problems. Educational game with the novel input and out technologies is one of the solutions for learners to engage in the learning activities. It can not only effectively encourage learners to learn positively and vividly, promote learning interests and motivation, and enhance the engagement, but also improve their imagination, learning performance and other learning behaviors. This paper first discusses the learning theories related to educational game. Then a literature review is conducted by collecting data on the topics of assessment of educational game with new interaction. Next, we propose a model to guide the design and the evaluation of educational game due to the missing studies. This model underlies an educational game to foster the garbage classification learning with virtual 3D output and natural gesture input using Leap Motion, which is a tracking device of hands and objects. To analyze users’ learning behaviors and evaluate their performance and experience, we conduct an evaluation with 22 college learners. Results showed that the use of the natural interaction not only made the learning interesting and fostered the engagement, but also improved the absorption of knowledge in practices. Finally, a discussion of the challenges and future directions is presented.

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APA

Zhou, Y., Xu, T., Zhu, Z., & Wang, Z. (2018). Learning in Doing: A Model of Design and Assessment for Using New Interaction in Educational Game. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 10925 LNCS, pp. 225–236). Springer Verlag. https://doi.org/10.1007/978-3-319-91152-6_18

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