Integrating technology in mathematics instruction on grade school academic achievement in Taiwan: A meta-analysis

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题名:	Integrating technology in mathematics instruction on grade school academic achievement in Taiwan: A meta-analysis 我國近30年科技融入數學教學對中小學生學習成效影響之後設分析
作者:	Liao, Yuen-Kuang Cliff Chen, Yung-Hsin
贡献者:	師資培育中心
关键词:	Academic achievement Integrating technology Mathematics Meta-analysis Taiwan students
日期:	2021-06
上传时间:	2023-05-08
摘要:	Jonassen (2000) suggested that learning with information technology (IT) involves three stages: learning from computers, learning about computers, and learning with computers. The development of learning with IT in Taiwan, beginning with computer-assisted instruction, loosely follows these three stages (Chang, 2002). Integrating IT into instruction is the first stage of learning with computers. Previous meta-analyses (Cheung & Slavin, 2013; Demir & Basol, 2014; Hartley, 1977; Li & Ma, 2011; Slavin et al., 2008, 2009; Slavin & Lake, 2008; Rakes et al., 2010; Sokolowski1 et al., 2015; Young, 2017) regarding the effectiveness of integrating IT into mathematics instruction (ITMI) have reported positive effects compared with non-ITMI classes; effect sizes (ESs) were 0.07-0.9. These meta-analyses also concluded that variables such as publication year, publication type, learning stage, research design, intervention duration, technology type, assessment tool, instructional approach, and mathematics topic might influence the overall ES. A total of 19 meta-analyses investigating the effects of integrating IT into student learning in Taiwan have been performed; however, none of these studies were specifically focused on mathematics. In this study, we performed a meta-analysis to synthesize existing research regarding the effects of integrating IT with mathematics instruction on the academic achievement of elementary and secondary school students in Taiwan. We searched the National Digital Library of Theses and Dissertations in Taiwan, Airiti Library, Index to Taiwan Periodical Literature System, Scopus, EBSCOhost, ProQuest, ScienceDirect, and Web of Science databases for relevant studies by using keywords “math, " “technology, " “computer, " and “achievement” and gathered 282 studies (with 20, 190 participants). We then transformed the quantitative data into ESs. After the calculation of the ES for each study, six studies with unusually large ESs were excluded in further analyses (Lipsey & Wilson, 2001). Thus, the total number of studies was 276. We used the meta-analytic approach suggested by Borenstein et al. (2009), Hedge and Olkin (1985), and Lipsey and Wilson (2001). The ES was defined as the mean difference between the treatment and control groups divided by the pooled standard deviations. The criteria for inclusion of studies were as follows: (1) Studies must compare the effects of ITMI and traditional instruction (TI) on student academic achievement in mathematics; (2) participants must be elementary or secondary school students; (3) the research design must include treatment and control groups, and the treatment group must receive treatment that involved integrating IT into instruction; (4) studies must provide adequate quantitative data for both treatment and control groups so that the ES could be estimated; (5) the number of participants for both ITMI and TI groups must be over 15; studies were excluded if the overall participants were less than 30; (6) the study participants must be Taiwanese students; (7) studies must be published between 1993 and 2019. On the basis of previous meta-analyses, the moderating effects of 13 variables were investigated. These variables were classified into three categories: (1) research characteristics, including learning stage, topic in mathematics, type of publication, and year of publication; (2) research methods, including study design, instructor bias, reliability of assessment tools, number of treatment class sessions, and sample size; and (3) research design, including the instructional approach for the treatment group, learning device for the student, method of integration, and timing of integration. Hedges’ g was applied for ES calculation. If studies provided only an F-ratio value or a t value, equivalent formulae were used. In addition, the homogeneity test presented by Borenstein et al. (2009) was used to aggregate and analyze the ESs for all 276 studies. The significance of the mean ES was evaluated by its 95% confidence interval (95% CI). A significantly positive (+) mean ES indicated that the results favored the ITMI group, whereas a significantly negative (-) ES indicated that the results favored the TI group. The results of this meta-analysis revealed that the overall mean ESs were 0.32 (95% CI = 0.30-0.35, z = 24.31, p <. 0001) and 0.35 (95% CI = 0.31-0.39, z = 17.54, p <. 0001) for the fixed-effects model and random-effects model, respectively. An effect is said to be small when ES < 0.2, medium when ES ≈ 0.5, and large when ES > 0.8 (Cohen, 1992). The results indicated that integrating technology into mathematics instruction had a significant small to medium positive effect compared with TI on the academic achievement of Taiwanese students. Moreover, the homogeneity test was significant (QT = 582.37, p [removed]
關聯:	Bulletin of Educational Psychology卷 52, 期 4, 頁 781 - 806 June 2021
显示于类别:	[師資培育中心 ] 期刊論文

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