Curriculum analytics in higher education institutions: a systematic literature review

IF 4.5 2区 教育学 Q1 EDUCATION & EDUCATIONAL RESEARCH Journal of Computing in Higher Education Pub Date : 2024-08-23 DOI:10.1007/s12528-024-09410-8
Liyanachchi Mahesha Harshani De Silva, María Jesús Rodríguez-Triana, Irene-Angelica Chounta, Gerti Pishtari
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Abstract

With technological advances, institutional stakeholders are considering evidence-based developments such as Curriculum Analytics (CA) to reflect on curriculum and its impact on student learning, dropouts, program quality, and overall educational effectiveness. However, little is known about the CA state of the art in Higher Education Institutions (HEIs), where dropout is a worldwide problem. Through a systematic literature review, this study summarizes 59 manuscripts about CA published until April 2024. The aim of this review is to identify: 1) WHERE CA was used; 2) WHO were the CA target stakeholders; 3) WHY CA was proposed; 4) WHAT types of data and what types of data gathering and analysis methods are employed; 5) HOW CA was designed, implemented and evaluated and what the stakeholders' role was; and 6) WHICH limitations and constraints affect CA and WHICH recommended practices could contribute to the CA success. Results from our review reveal a considerable number of CA solutions available. However, there is a need for more evidence on how CA solutions inform decision-making among various stakeholders. Thus, more longitudinal studies are needed, involving stakeholders not only in the design but also in the implementation and evaluation of CA solutions. At the same time, findings suggest that including multiple data sources can enrich the analysis and enable triangulation. Additionally, the lack of evidence on the role of CA in dropouts and decision-making in higher education institutions requires more future research on this aspect. Finally, researchers, practitioners, and decision-makers can use the findings obtained in this review to inform future research and practices on how to leverage CA to improve student learning, enhance the learning experience, and reduce student dropouts.

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高等教育机构的课程分析:系统文献综述
随着技术的进步,机构利益相关者正在考虑以证据为基础的发展,如课程分析(CA),以反思课程及其对学生学习、辍学、课程质量和整体教育效果的影响。然而,对于辍学这一世界性问题,人们对高等教育机构(HEIs)的课程分析技术现状知之甚少。本研究通过系统的文献综述,总结了截至 2024 年 4 月发表的 59 篇有关 CA 的手稿。本综述旨在确定1)CA 在何处使用;2)谁是 CA 的目标利益相关者;3)为什么提出 CA;4)采用了哪些类型的数据以及哪些类型的数据收集和分析方法;5)如何设计、实施和评估 CA 以及利益相关者的角色是什么;6)哪些限制和制约因素会影响 CA 以及哪些推荐实践有助于 CA 取得成功。我们的审查结果表明,有相当多的 CA 解决方案可供使用。然而,还需要更多证据来证明 CA 解决方案如何为各利益相关方的决策提供依据。因此,需要开展更多的纵向研究,让利益相关者不仅参与 CA 解决方案的设计,还参与其实施和评估。同时,研究结果表明,纳入多种数据来源可以丰富分析内容,实现三角测量。此外,由于缺乏关于 CA 在高等教育机构辍学和决策中的作用的证据,今后需要在这方面开展更多的研究。最后,研究人员、从业人员和决策者可以利用本综述中的发现,为今后的研究和实践提供参考,以了解如何利用 CA 来改善学生的学习,提高学习体验,减少学生辍学。
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来源期刊
Journal of Computing in Higher Education
Journal of Computing in Higher Education EDUCATION & EDUCATIONAL RESEARCH-
CiteScore
15.10
自引率
3.60%
发文量
40
期刊介绍: Journal of Computing in Higher Education (JCHE) contributes to our understanding of the design, development, and implementation of instructional processes and technologies in higher education. JCHE publishes original research, literature reviews, implementation and evaluation studies, and theoretical, conceptual, and policy papers that provide perspectives on instructional technology’s role in improving access, affordability, and outcomes of postsecondary education.  Priority is given to well-documented original papers that demonstrate a strong grounding in learning theory and/or rigorous educational research design.
期刊最新文献
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