Mining LMS data to develop an "early warning system" for educators: A proof of concept
Computers & Education
Proceedings of the 16th ACM international conference on Supporting group work
Issues, challenges, and lessons learned when scaling up a learning analytics intervention
Proceedings of the Third International Conference on Learning Analytics and Knowledge
Proceedings of the Fourth International Conference on Learning Analytics And Knowledge
Building institutional capacities and competencies for systemic learning analytics initiatives
Proceedings of the Fourth International Conference on Learning Analytics And Knowledge
Data wranglers: human interpreters to help close the feedback loop
Proceedings of the Fourth International Conference on Learning Analytics And Knowledge
Perceptions and use of an early warning system during a higher education transition program
Proceedings of the Fourth International Conference on Learning Analytics And Knowledge
Student explorer: a tool for supporting academic advising at scale
Proceedings of the first ACM conference on Learning @ scale conference
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This paper presents current findings from an ongoing design-based research project aimed at developing an early warning system (EWS) for academic mentors in an undergraduate engineering mentoring program. This paper details our progress in mining Learning Management System data and translating these data into an EWS for academic mentors. We focus on the role of mentors and advisors, and elaborate on their importance in learning analytics-based interventions developed for higher education.