For learners, with learners: Identifying indicators for an academic advising dashboard for students

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Abstract

Learning Analytics (LA) dashboards aggregate indicators about student performance and demographics to support academic advising. The majority of existing dashboards are targeted at advisors and professors, but not much attention has been put into students’ need for information for their own academic decision-making. In this study, we identify relevant indicators from a student perspective using a mixed methods approach. Qualitative data was obtained from an open-ended online questionnaire answered by 31 student representatives, and quantitative data was collected from a closed-ended online questionnaire answered by 652 students from different cohorts. Findings point out relevant indicators to help students choose what courses to take in an upcoming academic period. Since this study is part of a large research project that has motivated the adoption of academic advising dashboards in different Latin American universities, these findings were also contrasted with indicators of these advising dashboards, informing future developments targeting students.

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Hilliger, I., De Laet, T., Henríquez, V., Guerra, J., Ortiz-Rojas, M., Zuñiga, M. Á., … Pérez-Sanagustín, M. (2020). For learners, with learners: Identifying indicators for an academic advising dashboard for students. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 12315 LNCS, pp. 117–130). Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-030-57717-9_9

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