Using an integrative meta-analyzis to examine the effects of smart classroom-based instruction on academic achievement
A technological change perspective
Bibliographic Data
| ID | 21631726 |
|---|---|
| Authors | Shu-Hsuan Chang (0000-0002-2625-8347, National Changhua University of Education), Po-Jen Kuo (0000-0001-9864-6384, National Changhua University of Education, corresponding author), Jia Xin Kao (0000-0002-9194-6576, China Medical University), Lee-Jen Yang (0000-0003-0470-7495, National Changhua University of Education) |
| Year | 2022 |
| Pages | 1-28 |
| Publication date | 2022-12-15 |
| Open Access | No |
| Type | ARTICLE |
| Venue | Interactive Learning Environments (JOURNAL) |
| Journal identifiers | ISSN: 1049-4820 • E-ISSN: 1744-5191 |
| Publisher | Informa UK Limited (PUBLISHER • GB) |
| DOI | 10.1080/10494820.2022.2146138 |
| OpenAlex | W4311741078 |
| Language | EN |
| References cited | 65 |
With the development of education technology, Smart classroom has evolved to version 2.0. Currently, the meta-analysis literature on the effects of smart classroom-based instruction on academic achievement ignores the impact of technological changes and time on the effect sizes. This study incorporated the impact of technological changes and time, and proposed an integrative algorithm suitable for meta-analysis of students' academic achievement in applying education technology. The research results indicate that the overall average weighted effect size is 0.8, revealing that smart classroom-based instruction has a larger positive effect on students' academic achievement than non-smart classroom-based instruction. In addition, the average effect size is affected by moderator variables such as smart classroom type and year, learning management system and year, teaching strategy, sample size (experimental group), and school location, but is not affected by educational stage, learning domain, and experiment duration. The advantages of the proposed algorithm include: (1) using this algorithm, we can understand the changes in the effect size with the different types of education technology and the passage of time; and (2) this algorithm provides a quantitative analysis process, which can be used as a reference for the related research
Academic achievement · Educational technology · Machine learning · Mathematics education · Moderation · Sample size determination · Statistics · Computer Science · Education and Learning Interventions · Education and Technology Integration · Mathematics · Psychology · Technology-Enhanced Education Studies · Artificial Intelligence
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| Highly cited | No |
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