The psychological mechanism of self-regulated learning in a technology-enhanced environment

被引:0
|
作者
Revishvili, Mariam [1 ]
Tsereteli, Mzia [1 ]
机构
[1] Ivane Javakhishvili Tbilisi State Univ, Dept Educ Psychol, Tbilisi, Georgia
来源
COGENT EDUCATION | 2024年 / 11卷 / 01期
基金
美国国家科学基金会;
关键词
Self-regulated learning; technology-enhanced learning; higher education; confirmatory factor analysis; Hengtao Tang; University of South Carolina; Columbia; South Carolina; USA; Educational Psychology; Higher Education; Research Methods in Education; MOTIVATION; MODELS; FIT;
D O I
10.1080/2331186X.2024.2372153
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
The purpose of this study was to explore the psychological mechanism of self-regulated learning in a technology-enhanced learning environment and to develop a comprehensive model of its function. As a theoretical approach, we used Pintrich's model of Self-regulated learning. The mixed research methods were used in this study. First, we conducted focus-group discussions with students from higher education. Based on the results of the focus group, a questionnaire has been developed. A total of 307 BA students participated in the study, out of whom 213 (69.4%) were female students and 94 (30.6%) were male students. To explore the underlying factor structure of the questionnaire, items were subjected to principal component analysis (PCA). The principal component analysis revealed the presence of 14 components exploring the 61,77% variance respectively. After checking the factors similarity, the following scales were identified: Motivational scale, Cognitive strategies scale, and Deficit of SRL scale. Each scale reflects the area of positive and negative factors of technology use on the students' self-regulated learning. To examine the factorial properties of the questionnaire, all scales were tested using structural equation modeling (SEM). Results show that the model fit of the empirical and theoretical models is satisfactory for all three scales. The reliability of the questionnaire was measured using Cronbach's alpha. Coefficients ranged from .637 to .894. As for gender differences, male and female respondents showed statistically significant differences in the following factors: Self-efficacy in the task domain; Note-taking; Nonacceptance beliefs toward technology; and Blockages to technology integration.
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页数:14
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