Student outcomes are of great importance in higher education institutions. Accreditation bodies focus on them as an indicator to measure the performance and effectiveness of the institution. Forecasting students' academic performance is crucial for every educational establishment seeking to enhance performance and perseverance of its students and…

Artificial intelligence (AI) is increasingly exploited to promote student engagement. This study combined topic modelling, keyword analysis, trend test and systematic analysis methodologies to analyse AI-supported student engagement (AIsE) studies regarding research keywords and topics, AI roles, AI systems and algorithms, methods and domains,…

Background and context: Coding and computational thinking are often taught through integrated curricula, despite a paucity of classroom-based research on their effectiveness. Objective: To investigate evidence of learning resulting from cross-curricular coding tasks in middle-school classrooms, and the school environment factors that impact upon…

Educational data mining is widely deployed to extract valuable information and patterns from academic data. This research explores new features that can help predict the future performance of undergraduate students and identify at-risk students early on. It answers some crucial and intuitive questions that are not addressed by previous studies.…

Large language models present new opportunities for teaching and learning. The response accuracy of these models, however, is believed to depend on the prompt quality which can be a challenge for students. In this study, we aimed to explore how undergraduate students use ChatGPT for problem-solving, what prompting strategies they develop, the link…