Using Analytics to Select and Track At-Risk Students for Targeted Interventions

Abstract

The provision of academic support is an institution’s responsibility to ensure students’ chance of attaining academic success. Data is used to understand students’ learning and academic performance and helps in making decisions on when and whom to provide timely academic support. This presentation will discuss a pilot project conducted at a Singapore university, whereby a stepped-up approach is used to provide academic support to students who are academically at-risk. The basic intervention that is provided to the majority of at-risk students is an advisory email that provides resources for self-help. The next level of intervention, that is more resource intensive, is the one-on-one academic coaching for a select group of at-risk students. Such targeted interventions will not only ensure a higher chance of being effective in supporting students, it also ensures efficiency in resource utilisation. The presentation will detail the process of using analytics to select and track at-risk students for the targeted interventions. Learning points from this pilot project will also be shared for the benefit of like-minded educational institutions planning to use analytics to support academically at-risk students.



Author Information
Yew Haur Lee, Singapore University of Social Sciences, Singapore
Yan Yin Ho, Singapore University of Social Sciences, Singapore

Paper Information
Conference: ACE2021
Stream: Learning Experiences

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Posted by amp21