...Fernando Curbani; Andreia Zanella; André Wüst Zibetti Purpose This study aims to develop and evaluate machine learning models to predict dropout across three key stages of the undergraduate journey: pre-enrollment, the end of the first semester, and the end of the third semester. Design...

... integration. Design/methodology/approach This study applies natural language processing (NLP) and machine learning to analyze graduate-level course descriptions from business and non-business analytics programs. BERTopic identifies latent topical structures, while a neural network-based classifier Neural...

... were analyzed using machine learning classification models, specifically decision trees, to identify patterns in levels of environmental concern. Design/methodology/approach The study aimed to explore how interactions with AI-based narratives influence university students’ understanding...

... Emerald Publishing Limited 2025 Emerald Publishing Limited Licensed re-use rights only ICT Digital competence Artificial intelligence Machine learning Behavioural bias India For the last two decades, the world has witnessed the rapid evolution of information technology...

... to drop school before Semester 1. Based on the provided knowledge in these systems, UNIs can have enough time for planning assistance strategies and issuing preventive policies to intervene timely (Schmitt et al., 2021). Machine learning (ML), a technique of artificial intelligence...