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Using networked learning to improve learning analytics implementation

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Abstract

As learning analytics use grows across U.S. colleges and universities, so does the need to discuss the plans, purposes, and paths for the data collected via learning analytics. More specifically, students, faculty, and others who are impacted by learning analytics use should have more information about their campus’ learning analytics practices than many colleges and universities currently provide. Therefore, in the current text, the authors leverage networked learning to create a networked learning analytics logic model that supports colleges and universities in develo** more transparent, ethical, inclusive learning analytics plans. The authors build on their previous learning analytics framework as well as extant learning analytics literature to develop the networked learning analytics logic model. The model offers flexibility that allows for adaptive implementation by institutions that are both new to or already engaging in learning analytics initiatives. We encourage those considering learning analytics to implement the model and disseminate their findings so that the model can evolve to align with the dynamic nature of learning analytics implementations.

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Authors and Affiliations

  1. William & Mary, Williamsburg, USA

    Stephanie J. Blackmon

  2. School of Teaching and Learning, College of Education, University of Florida, Gainesville, USA

    Robert L. Moore

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  1. Stephanie J. Blackmon
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Appendix 1

Appendix 1

See Table 5

Table 5 Networked Learning Logic Model (adapted from Keller & Bauerle, 2009)
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Blackmon, S.J., Moore, R.L. Using networked learning to improve learning analytics implementation. J Comput High Educ 36, 183–201 (2024). https://doi.org/10.1007/s12528-023-09362-5

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