Trends in Higher Education

Artificial intelligence (AI) has become central to the evolution of learning analytics (LA), transforming how higher-education institutions capture and interpret student engagement data. This narrative review synthesises research published between 2015 and 2025 to examine how AI-driven analytics link learner engagement to measurable academic outcomes, with emphasis on the South-African higher-education context. Drawing on global reviews of AI in education and emerging governance frameworks, the study highlights the shift from traditional dashboards toward deep-learning and transformer-based systems that integrate behavioural, cognitive, and affective indicators. Ethical and policy challenges, particularly around data privacy, transparency, and institutional capacity, remain significant. Grounded in UNESCO and OECD guidance and South Africa’s Protection of Personal Information Act, the review outlines a governance-driven approach for equitable and transparent adoption of AI-enhanced learning analytics. It identifies key challenges, data fragmentation, algorithmic opacity, and limited contextual adaptation, and translates them into practical recommendations for policy, capacity building, and future research. The findings underscore that sustainable AI adoption requires human-centred ethics, robust data governance, and context-sensitive innovation to achieve inclusive and data-driven higher education.

Examinations are central to higher education, yet students consistently describe them as detrimental to well-being. Drawing on self-determination theory (SDT), we conducted three studies to examine whether multiple-choice examinations could be redesigned to satisfy students’ basic psychological needs (BPNs) and support well-being. In Study 1 (n = 400), we developed and validated the Basic Psychological Need Satisfaction and Frustration Scale for Classroom Assessment (BPNSF-CA). Using bifactor exploratory structural equation modeling (bifactor ESEM), results supported a well-defined single global need fulfillment factor (G-factor) alongside six specific factors (autonomy support/frustration, competence support/frustration, relatedness support/frustration) as well as evidence of validity. In Study 2 (n = 387), we conducted a randomized experiment with three versions of a multiple-choice exam serving as the independent variable (flawed items, high-quality items, and high-quality + need-supportive features). Results showed that high-quality items improved performance, while only the addition of need-supportive features satisfied BPNs with differential patterns for the single G-factor and S-factors. In Study 3 (n = 101), we applied the intervention in a real classroom and tested the mediational role of BPN satisfaction. Results showed that redesigned exams (high-quality + need-supportive features) significantly enhanced perceptions of fairness and success via BPNs. We conclude with a discussion of all three studies, including implications and limitations.

Post-COVID-19, it is widely reported that the attendance rates of higher education students have not recovered to pre-COVID-19 numbers. Initial internal investigations in the Department of Mathematics and Statistics at Maynooth University suggested that factors relating to the cost of living, commuting, and working were impacting students’ ability to attend university. In order to establish the degree to which these issues were influencing student attendance at lectures, tutorials, and with the academic support of mathematics at Maynooth University, we conducted an in-depth survey of first-year service mathematics students. This paper focuses on the qualitative experiences and perspectives of the 415 students who participated in this study. Using reflective thematic analysis, we identified two dominant themes across the survey responses: the weight of the ‘financial burdens’ that students were experiencing, and frustration with the ‘poor infrastructure’ that they encountered. As a result, a further three themes of students being ‘time poor’, feeling forced to make difficult ‘decisions’, and ‘missing out’ on academic and social life were also prevalent. These findings reveal the complex and systemic challenges facing students in their day-to-day efforts to attend university, and they emphasise the urgent need for both institutional specific measures and coordinated government policies to tackle these issues.