The effects of online learning self-efficacy and attitude toward online learning in predicting academic performance: The case of online prospective mathematics teachers

IF 0.9 Q3 EDUCATION & EDUCATIONAL RESEARCH Tuning Journal for Higher Education Pub Date : 2023-11-30 DOI:10.18543/tjhe.2214
S. Bütüner, Serdal Baltaci
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Abstract

This study aims to discover if Online Learning Self-Efficacy (OLSE) and attitude toward online learning (AOL) significantly predict the academic performance (AP) among Turkish prospective mathematics teachers. Unlike the studies conducted in the literature, online learning self-efficacy and attitude towards online learning as predictor variables were included in the study and both quantitative and qualitative data were collected. The study included 1075 prospective mathematics teachers’ responses in the analysis. The Pearson correlation was employed to determine how strongly OLSE, AOL, and AP are related. Results indicated that OLSE and AOL influenced the level of AP. Also, the multiple regression aimed to predict AP based on OLSE and AOL, and this model explained 44.6% of the variance in AP. The beta weights demonstrated that OLSE and AOL (OLSE β = .36, t(1072) = 9.705, p < .001, and AOL β = .34, t(1072) = 9.176, p < .001) significantly contributed to the model. The results showed that the level of academic performance can be predicted by online learning self-efficacy and attitude toward online learning. In addition, this study revealed the factors that have favorable and adverse effects on the academic performance of prospective mathematics teachers to gain more extensive information. Under the theme of negative factors, there were 7 codes. The results obtained from the study can be a guide for practitioners, policy makers and teachers to take the necessary precautions for the effective execution of the distance education process. Received: 4 October 2021Accepted: 27 June 2023
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在线学习自我效能感和在线学习态度对预测学习成绩的影响:在线准数学教师的案例
本研究旨在发现在线学习自我效能感(OLSE)和在线学习态度(AOL)是否能显著预测土耳其未来数学教师的学业成绩(AP)。与文献研究不同的是,本研究将在线学习自我效能感和在线学习态度作为预测变量,并收集了定量和定性数据。研究分析了 1075 名未来数学教师的回答。研究采用了皮尔逊相关法来确定 OLSE、AOL 和 AP 的相关程度。结果表明,OLSE 和 AOL 对 AP 水平有影响。此外,多元回归旨在根据 OLSE 和 AOL 预测 AP,该模型解释了 AP 变异的 44.6%。贝塔权重表明,OLSE 和 AOL(OLSE β = .36,t(1072) = 9.705,p < .001;AOL β = .34,t(1072) = 9.176,p < .001)对模型有显著贡献。结果表明,在线学习自我效能感和在线学习态度可以预测学习成绩水平。此外,本研究还揭示了对准数学教师学业成绩产生有利和不利影响的因素,以获得更广泛的信息。在负面因素这一主题下,共有 7 个代码。本研究获得的结果可为从业人员、政策制定者和教师提供指导,为有效实施远程教育过程采取必要的预防措施。 收稿日期:2021 年 10 月 4 日接受日期:2023 年 6 月 27 日
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来源期刊
Tuning Journal for Higher Education
Tuning Journal for Higher Education EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
1.20
自引率
11.10%
发文量
15
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