Learning Based on Art and the Digital Paradox: Rethinking English Education in the 21st Century.

IF 1.2 4区 综合性期刊 Q3 MULTIDISCIPLINARY SCIENCES
Shengqin Bi
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引用次数: 0

Abstract

This study investigates the digital paradox in 21st-century English education, aiming to determine how integrating digital art pedagogies influences academic performance. The primary objective was to test a model positing that digital art integration, perceived art value, and technology self-efficacy drive academic success, with student engagement as a mediator and digital literacy as a moderator. A quantitative methodology was employed, collecting data from n = 265 Chinese undergraduates and analyzing them via Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings confirm that student engagement fully mediates the relationship between the three independent variables and academic performance. A key and novel discovery is the significant negative moderating effect of digital literacy, indicating that the engagement-performance link is weaker for highly digitally literate students. This provides a nuanced empirical understanding of the digital paradox, suggesting that high digital skills may inadvertently dilute academic focus. The study's novelty lies in its integrated model and in this counterintuitive finding, which challenges the assumption that digital literacy is an unequivocal benefit. Theoretical implications include a refined model of technology acceptance in creative disciplines. In contrast, practical implications advise educators to design digital art pedagogies that strategically manage cognitive load for all learners, not just the less proficient.

基于艺术的学习与数字悖论:21世纪英语教育的再思考
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来源期刊
Jove-Journal of Visualized Experiments
Jove-Journal of Visualized Experiments MULTIDISCIPLINARY SCIENCES-
CiteScore
2.10
自引率
0.00%
发文量
992
期刊介绍: JoVE, the Journal of Visualized Experiments, is the world''s first peer reviewed scientific video journal. Established in 2006, JoVE is devoted to publishing scientific research in a visual format to help researchers overcome two of the biggest challenges facing the scientific research community today; poor reproducibility and the time and labor intensive nature of learning new experimental techniques.
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