Challenges and contexts in establishing adaptive learning in higher education: findings from a Delphi study

Author:

Mirata VictoriaORCID,Hirt Franziska,Bergamin Per,van der Westhuizen Christo

Abstract

AbstractHigher education institutions are increasingly interested in using adaptive learning as an innovative data-driven approach to teaching. The actual use of adaptive learning in courses remains, however, low. This is despite positive attitudes of institutional leaders towards its adoption and promising results of early studies on its effectiveness.This study examines the challenges that prevent higher education institutions from adopting adaptive learning concepts in teaching. We used a four-stage Delphi design to empirically identify, categorise, and prioritise the challenges of adaptive learning raised and rated by experts from two universities with different organisational and socioeconomic contexts, one from Switzerland and one from South Africa. Considering different contexts allowed us to include various perspectives on the research topic and thus broaden the view on the challenges of adaptive learning. Overall, three main dimensions related to technological, teaching and learning, and organisational challenges with eight corresponding categories were identified. Our findings revealed clear differences between the two universities regarding the emerged challenges and their rankings. These differences are linked to different socioeconomic backgrounds (South Africa and Switzerland) and organisational contexts (e.g., type of the university, teaching model, and implementation phase) of the universities. We conclude by proposing practical recommendations for institutional leaders and project implementers on the factors to be considered when implementing adaptive learning in higher education settings. These recommendations relate to the necessary infrastructure, institutional commitment, support and resources.

Publisher

Springer Science and Business Media LLC

Subject

Computer Science Applications,Education

Reference52 articles.

1. Avella, J. R. (2016). Delphi panels: Research design, procedures, advantages, and challenges. International Journal of Doctoral Studies, 11, 305–321.

2. Bailey, A., Vaduganathan, N., Henry, T., Laverdiere, R., & Pugliese, L. (2018). Making digital learning work: Success strategies from six leading universities and community colleges. Retrieved from https://edplus.asu.edu/sites/default/files/BCG-Making-Digital-Learning-Work-Apr-2018.pdf

3. Bate, P., Robert, G., Fulop, N., Øvretveit, J., & Dixon-Woods, M. (2014). Perspectives on context. Retrieved from https://www.health.org.uk/sites/default/files/PerspectivesOnContext_fullversion.pdf

4. Becker, S. A., Brown, M., Dahlstrom, E., Davis, A., DePaul, K., Diaz, V., & Pomerantz, J. (2018). CMN Horizon report: 2018 Higher education edition. Retrieved from https://library.educause.edu/~/media/files/library/2018/8/2018horizonreport.pdf

5. Brady, S. R. (2015). Utilizing and adapting the Delphi method for use in qualitative research. International Journal of Qualitative Methods, 14(5), 1–6 https://doi.org/10.1177/1609406915621381.

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3