Perceived benefits and barriers of a prototype early alert system to detect engagement and support 'at-risk' students: The teacher perspective. (October 2020)

• Record Type: Journal Article
• Authors: Atif, Amara; Richards, Deborah; Liu, Danny; Bilgin, Ayse Aysin
• Is Part Of: Computers & education. Volume 156(2020)
• Publication Date: 2020-10
• Subjects: Student early alert system -- Teacher perspective -- At-risk student -- Student performance -- Learning management system; Education -- Data processing -- Periodicals; Education -- Periodicals; Computers -- Periodicals; Computer-Assisted Instruction -- Periodicals; Éducation -- Informatique -- Périodiques; Electronic journals; 370.285
• DOI: 10.1016/j.compedu.2020.103954
• Languages: English
• ISSNs: 0360-1315

Abstract

Abstract: Given the focus on boosting retention rates and the potential benefits of proactive and early identification of students who may require support, higher education institutions are looking at the data already captured in university systems. Student early alert systems are part of formal, proactive, early intervention communication initiatives that institutions have put into place to help with the timely identification and intervention (alert) of at-risk students. The significance of student early alert systems is that support could be offered to high-risk students while they are still enrolled in the unit and able to influence their success/failure before the unit completes. Delivering timely interventions to students via a student early alert system typically requires teaching staff to identify at-risk students, and act upon that information in a way that would encourage students to change their behaviours. However, little is understood regarding teachers' needs and attitudes towards the use of such a system. In the context of a prototype early alert system, this article reports the practices and opinions of a range of teaching staff across all faculties within an institution. The article sheds light on how teachers measure student performance and engagement in their units, and the perceived benefits and barriers of using the early alert system to identify and manage at-risk students. Highlights: Teachers want learning analytics tools that combine reliable data with action. Exploratory sequential mixed methods effectively captured teachers' perceptions. Assessment-related data from LMS preferred by teachers as engagement triggers. Main challenges for teachers were tool usability, data trustworthiness, interpretability. At-scale early interventions focused on withdrawal or face-to-face meetings.