近十年来scopus数据库中基于计算机的数学学习的元分析:趋势和启示

M. Tamur, S. Ndiung, Robert Weinhandl, T. Wijaya, E. Jehadus, E. Sennen
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引用次数: 1

摘要

在过去的十年中,基于计算机的数学学习(CBML)已经走向全球,并对教育目的产生了重大影响。但事实是,在科学文献中,人们发现旨在检验这些理论假设的研究结果并不一致。在这方面,本荟萃分析是为了确定CBML的影响,并分析分类变量来考虑其影响。数据在2010年至2023年期间使用“发表或消亡”从Scopus数据库中检索。本研究检查了28项符合条件的初级研究的29个独立样本,共1179名受试者。人口估计基于随机效应模型,并使用CMA软件作为计算辅助。该研究的结果提供了1.03的总体效应值(大效应)。这表明运用CBML对学生的数学能力有显著影响。讨论了研究中考虑的四个分类变量,以阐明研究趋势。此外,概述了研究的意义,并有助于未来的CBML实施安排。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
META-ANALYSIS OF COMPUTER-BASED MATHEMATICS LEARNING IN THE LAST DECADE SCOPUS DATABASE: TRENDS AND IMPLICATIONS
Computer-Based Mathematics Learning (CBML) has gone global in the last decade and is making a substantial impact for educational purposes. But the fact is that in the scientific literature, it is found that studies aimed at testing these theoretical assumptions have inconsistent results. In this regard, this meta-analysis was conducted to determine the effect of CBML and to analyze categorical variables to consider the implications. Data were retrieved from the Scopus database using Publish or Perish between 2010 and 2023. This study examined 29 independent samples from 28 eligible primary studies with 1179 subjects. The population estimate was based on a random effects model, and the CMA software was used as a calculation aid. The study's results provide an overall effect size of 1.03 (large effect). This indicates that applying CBML significantly affects students' mathematical abilities. The four categorical variables considered in the study are discussed to clarify research trends. Furthermore, the research implications are outlined and contribute to future CBML implementation arrangements.
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