Predictive Learning Analytics and the Creation of Emotionally Adaptive Learning Environments in Higher Education Institutions: A Study of Students’ Affect Responses

Research output: Contribution to journalArticlepeer-review


The aims of this study are to examine affective responses of university students when viewing their own Predictive Learning Analytics (PLA) dashboards, and to analyse how are those responses perceived to affect their self-regulated learning behaviour?

42 Northern Irish students were shown their own predictive scores on a dashboard. A list of emotions along with definitions were provided which respondents were instructed to verbalise during the experience. Post-hoc walkthrough conversations with participants further clarified their responses. Content analysis methods were used to categorise response patterns.

There is a significant variation in ways students respond to the predictions: they were Curious and motivated, Comforted and sceptical, Confused and fearful and with some students being not interested and doubting the accuracy of predictions. We show that not all PLA-triggered affective states motivate students to act in desirable and productive ways.

Research limitations/implications
This small-scale exploratory study was conducted in one higher education institution with a relatively small sample of students in one discipline. In addition to the many different categories of students included in the study, specific efforts were made to include 'at-risk' students. However, none responded. A larger sample from a multi-disciplinary background that include those who are categorised as 'at-risk' could further enhance our understanding.

Practical implications
We provide mixed evidence for students’ openness to learn from predictive learning analytics scores. The implications of our study are not straightforward, except to proceed with caution, valuing benefits while ensuring that students’ emotional wellbeing is protected through a mindful implementation of PLA systems.

Social implications
Understanding students’ affect responses contribute to the quality of student support in higher education institutions. In the current era on online learning and increasing adaptation to living and learning online, our findings allow for the development of appropriate strategies for implementing affect-aware PLA systems.

The current study is unique in its research context, and its examination of immediate affective states experienced by students who viewed their predicted scores, based on their own dynamic learning data, in their home institution. It brings out the complexities pertinent to implementing student-facing PLA dashboards in higher education institutions.
Original languageEnglish
JournalInternational Journal of Information and Learning Technology
Publication statusAccepted/In press - 16 Feb 2021

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