“I Feel Seen”: What Higher Education Students Find Helpful in Learning Analytics-Informed Personalised Messaging from Teachers
DOI:
https://doi.org/10.53761/xz6w5w79Keywords:
learning analytics, personalised learning, assessment feedback, at-risk studentsAbstract
There is a recognised disconnect between the learning analytics that are routinely collected by higher education institutions, and their application in improving learning and teaching. The effectiveness of presenting learning analytics in dashboards, either student-facing or teacher-facing, has been questioned, with student-facing dashboards sometimes leading to negative outcomes, and teachers struggling to convert dashboard indicators into actions that improve learning. Likewise, analytics used in early-warning systems to identify at-risk students can be overly reliant on demographic or past performance data, and not responsive to unit-specific learning conditions, which are likely to be more significant when it comes to improving engagement and performance. An alternative approach to using learning analytics is to afford teachers the ability to use data for tailoring messages to students in a fashion and rhythm that best suits the specific pattern of learning activities and assessments within a particular unit. Following an approach such as this, the Student Relationship Engagement System (SRES) has been in use at the University of Sydney since 2011. We analysed six years of students’ feedback comments on what they found useful about email messages they received via SRES, and found that they most appreciated personalised feedback, which they frequently indicated would help them improve in future assessments. They also signalled that timely reminders and clarifications of unit requirements were helpful, and they valued the encouragement, motivation, and sense of connectedness the messages conveyed. To our knowledge this is the first large-corpus study of student perceptions of this type of learning analytics application.
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Data are not publicly available, in accordance with institutional ethics approval received.
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Copyright (c) 2025 Christopher Bridge, Associate Professor Jay Cohen, Professor Danny Y. T. Liu

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