Digital Learning Challenges in Tertiary Education in Sri Lanka: A Social Capital Perspective

IF 4.5 2区 计算机科学 Q1 COMPUTER SCIENCE, CYBERNETICS
Jayoda Weerapperuma;Dasuni Nawinna;Narmada Gamage
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Abstract

This study investigates the underlying factors that contribute to the success of digital learning in higher education using a social capital perspective. It is important to address the issues faced in tertiary education as these students will soon be a part of the workforce. Although digital learning has advanced in developed countries, many developing nations, including Sri Lanka, are still in the early stages of adopting it. Previous research has not adequately explored the relationship between social capital and the challenges of digital learning in the Sri Lankan context. Thus, this study focuses on examining the structural, relational, and cognitive aspects of social capital in relation to the difficulties in digital education in tertiary institutions. The research uses a quantitative approach, and the data were collected through an online survey of students in nonstate universities in Sri Lanka. Structural equation modeling was used to analyze the data, and the results showed that the three dimensions of poor social capital have a negative impact on digital education in tertiary institutions. This study also used multigroup moderation analysis to examine the effect of gender and location. This article will provide new insights into the role of social capital in digital education and will help policy makers to improve the quality and accessibility of digital education for all.
斯里兰卡高等教育中的数字化学习挑战:社会资本视角
本研究从社会资本的角度出发,探讨了促使高等教育数字化学习取得成功的潜在因素。解决高等教育中面临的问题非常重要,因为这些学生很快就会成为劳动力的一部分。虽然数字化学习在发达国家取得了进展,但包括斯里兰卡在内的许多发展中国家仍处于采用数字化学习的初期阶段。以往的研究没有充分探讨斯里兰卡社会资本与数字化学习挑战之间的关系。因此,本研究侧重于探讨社会资本的结构、关系和认知方面与高等院校数字化教育困难之间的关系。研究采用定量方法,通过对斯里兰卡非国立大学学生的在线调查收集数据。研究采用结构方程模型对数据进行分析,结果表明,不良社会资本的三个维度对高等院校的数字化教育产生了负面影响。本研究还采用了多组调节分析法来考察性别和地点的影响。本文将为社会资本在数字教育中的作用提供新的见解,并将帮助政策制定者提高全民数字教育的质量和可及性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Transactions on Computational Social Systems
IEEE Transactions on Computational Social Systems Social Sciences-Social Sciences (miscellaneous)
CiteScore
10.00
自引率
20.00%
发文量
316
期刊介绍: IEEE Transactions on Computational Social Systems focuses on such topics as modeling, simulation, analysis and understanding of social systems from the quantitative and/or computational perspective. "Systems" include man-man, man-machine and machine-machine organizations and adversarial situations as well as social media structures and their dynamics. More specifically, the proposed transactions publishes articles on modeling the dynamics of social systems, methodologies for incorporating and representing socio-cultural and behavioral aspects in computational modeling, analysis of social system behavior and structure, and paradigms for social systems modeling and simulation. The journal also features articles on social network dynamics, social intelligence and cognition, social systems design and architectures, socio-cultural modeling and representation, and computational behavior modeling, and their applications.
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