Advising the whole student: eAdvising analytics and the contextual suppression of advisor values

Publication Information

APA Citation

Jones, K. M. L. (2018). Advising the whole student: eAdvising analytics and the contextual suppression of advisor values. Education and Information Technologies, 24(1), 437-458. doi: 10.1007/s10639-018-9781-8

Description

Institutions are applying methods and practices from data analytics under the umbrella term of “learning analytics” to inform instruction, library practices, and institutional research, among other things. This study reports findings from interviews with professional advisors at a public higher education institution. It reports their perspective on their institution’s recent adoption of eAdvising technologies with prescriptive and predictive advising affordances. The findings detail why advisors rejected the tools due to usability concerns, moral discomfort, and a belief that using predictive measures violated a professional ethical principle to develop a comprehensive understanding of their advisees. The discussion of these findings contributes to an emerging branch of educational data mining and learning analytics research focused on social and ethical implications. Specifically, it highlights the consequential effects on higher education professional communities (or “micro contexts”) due to the ascendancy of learning analytics and data-driven ideologies

Access the Publication
SSRN

Share this Publication

Metrics and Citations

Alternative Metrics

Google Scholar Citations: None at this time.

Scholarly Citations

None at this time.

Grey Literature Citations

None at this time.