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Title:	Enhancing Learning Performance with Interactive Test Dashboard and Diagnostic Feedback Mechanisms
Authors:	陳志銘 Chen, Chih-Ming;Liu, Ting-Yu;Li, Ming-Chaun;Hsu, Wei-Tung
Contributors:	圖檔所
Keywords:	Digital dashboard for learning (DDL);Test dashboard with diagnosis and feedback;Computer-adaptive science assessment;Physics self-efficacy;Technology acceptance
Date:	2023-07
Issue Date:	2024-04-29 14:51:43 (UTC+8)
Abstract:	In the present research, an interactive test dashboard with diagnostic and feedback mechanisms (ITD-DFM) was designed and implemented to provide students with a comprehensive feedback system for their learning reflection and review. This system effectively synthesizes test response time and correctness to generate visualized and high-quality feedback, thus supporting students’ academic progress. To evaluate the effectiveness of ITD-DFM, a quasi-experimental study was conducted on a sample of 50 eighth-grade students from two classes in a public junior high school in Taiwan. One class with 26 students was assigned as the experimental group using ITD-DFM to support their learning, and the other class with 24 students was assigned as the control group using the traditional testing system without diagnosis and feedback mechanisms (TTS-NDFM). The results of the experiment showed a significant difference between the experimental and control groups in terms of learning performance, physics self-efficacy, and technology acceptance. Specifically, the experimental group showed significantly higher levels of learning performance, physics self-efficacy, and technology acceptance than the control group. The ITD-DFM was found to be effective in improving learning performance, as indicated by the significant improvements observed in the experimental group. In addition, the experimental group showed notable improvements in physics self-efficacy, a finding that was not evident in the control group. Moreover, the technology acceptance in the experimental group was also found to be significantly higher than that of the control group, further supporting the potential of ITD-DFM to facilitate learning in a physics course.
Relation:	2023 14th IIAI International Congress on Advanced Applied Informatics (IIAI-AAI), International Institute of Applied Informatics
Data Type:	conference
DOI link:	https://doi.org/10.1109/IIAI-AAI59060.2023.00040
DOI:	10.1109/IIAI-AAI59060.2023.00040
Appears in Collections:	[Graduate Institute of Library, Information and Archival Studies] Proceedings

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