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Technological barriers and incentives to learning analytics adoption in higher education: insights from users

Abstract

Learning analytics (LA) tools promise to improve student learning and retention. However, adoption and use of LA tools in higher education is often uneven. In this case study, part of a larger exploratory research project, we interviewed and observed 32 faculty and advisors at a public research university to understand the technological incentives and barriers related to LA tool adoption and use. Findings indicate that lack of a trustworthy technological infrastructure, misalignment between LA tool capabilities and user needs, and the existence of ethical concerns about the data, visualizations, and algorithms that underlie LA tools created barriers to adoption. Improving tool integration, clarity, and accuracy, soliciting the technological needs and perspectives of LA tool users, and providing data context may encourage inclusion of these tools into teaching and advising practice.

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Acknowledgements

This research was supported in part by a grant from the National Science Foundation under Grant IIS-1447489.

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Correspondence to Carrie Klein.

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Klein, C., Lester, J., Rangwala, H. et al. Technological barriers and incentives to learning analytics adoption in higher education: insights from users. J Comput High Educ 31, 604–625 (2019). https://doi.org/10.1007/s12528-019-09210-5

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  • DOI: https://doi.org/10.1007/s12528-019-09210-5

Keywords

  • Learning analytics
  • Predictive analytics
  • Technology adoption
  • Technological barriers
  • Technological incentives
  • Higher education