大数据分析与教育可持续性——马来西亚的情况

S. Jayashree, Mohammad Nurul Hassan Reza, C. Malarvizhi, Mazni Binti Alias
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引用次数: 0

摘要

尽管人们对高等教育机构(hli)的兴趣日益浓厚,但关注教育部门可持续性的大数据分析(BDA)研究仍处于起步阶段。因此,本研究提出了一个以bda为中心的框架,通过整合技术、组织和环境(TOE)理论和创新扩散(DOI)模型,强调高等教育的可持续性。将对该框架进行检验,以审查各种因素对采用BDA和可持续教育的影响。它还旨在确定BDA如何帮助高级别机构实现可持续性。此外,BDA是否在各因素与可持续教育之间起到中介作用也将被检验。本研究将采用基于问卷的调查来验证模型。数据将从位于马来西亚各州的公立和私立大学收集。结构方程模型(SEM)将被用来检验模型和提出的假设。该研究结果为在hli中成功采用BDA提供了重要的见解。本研究可为教育工作者、政策制定者和大数据供应商在高等教育机构中成功采用大数据以确保教育系统的可持续性提供参考。
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Big Data Analytics and Educational Sustainability-A Malaysian Scenario
Despite the increased interest in higher learning institutions (HLIs), research on big data analytics (BDA) focusing on sustainability in the education sector is still in its infancy. Therefore, this study proposes a BDA-centric framework, emphasizing sustainability in higher education by integrating the Technology, Organization, and Environment (TOE) theory and the Diffusion of Innovation (DOI) model. The framework will be tested to examine the impact of the factors on BDA adoption and sustainable education. It also aims to determine how BDA assists HLIs in attaining sustainability. Moreover, whether BDA mediates the relationship between the factors and sustainable education will also be tested. The study will employ a questionnaire-based survey to validate the model. Data will be collected from public and private universities located in various states in Malaysia. Structural Equation Modeling (SEM) will be employed to examine the model and proposed hypotheses. The study's findings offer essential insights for adopting BDA successfully in HLIs. This study may be helpful for educators, policymakers, and big data vendors in adopting big data successfully among HLIs to ensure sustainability in educational systems.
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