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Digital Game-Based Assessment on Student Evaluation: A Systematic Review

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Blended Learning: Engaging Students in the New Normal Era (ICBL 2022)

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Abstract

Digital Game-Based Assessment (DGBA) has emerged as a valid alternative to traditional assessment. This study conducted a systematic review of empirical studies on DGBA in the field of student evaluation from six aspects: country of research, education level of participant, game genre, content of assessment, method of assessment, and method of data analysis. It was found that DGBA has attracted extensive attention from researchers all over the world and it is applicable to students at almost all educational levels. The gener of game used for DGBA are mainly educational games. The main contents of assessment of DGBA are discipline knowledge, contemporary competence and cognitive ability. The main assessment methods of DGBA are formative assessment modeling with process data and summative assessment using final scores. Given these findings, this study made several recommendations for future studies on DGBA.

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Acknowledgments

The work was supported by a grant from the National Natural Science Foundation of China (No. 62107019).

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Authors and Affiliations

  1. Central China Normal University, Wuhan, 430079, China

    Sha Zhu, Qing Guo & Harrison Hao Yang

  2. State University of New York at Oswego, Oswego, 13126, USA

    Harrison Hao Yang

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  1. Sha Zhu
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  2. Qing Guo
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Correspondence to Harrison Hao Yang .

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Editors and Affiliations

  1. The Hong Kong Polytechnic University, Hong Kong, China

    Richard Chen Li

  2. Hong Kong Metropolitan University, Hong Kong, China

    Simon K. S. Cheung

  3. The Hong Kong Polytechnic University, Hong Kong, China

    Peter H. F. Ng

  4. Tung Wah College, Hong Kong, China

    Leung-Pun Wong

  5. Hong Kong Metropolitan University, Hong Kong, China

    Fu Lee Wang

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Zhu, S., Guo, Q., Yang, H.H. (2022). Digital Game-Based Assessment on Student Evaluation: A Systematic Review. In: Li, R.C., Cheung, S.K.S., Ng, P.H.F., Wong, LP., Wang, F.L. (eds) Blended Learning: Engaging Students in the New Normal Era. ICBL 2022. Lecture Notes in Computer Science, vol 13357. Springer, Cham. https://doi.org/10.1007/978-3-031-08939-8_8

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  • DOI: https://doi.org/10.1007/978-3-031-08939-8_8

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