Depression and academic stress undermine students' attendance, performance, and retention, yet educational institutions lack reliable early-alert tools. Because about three-quarters of lifetime psychiatric conditions emerge before age 25, timely automated screening is critical for early intervention. This paper proposes a multi-source ensemble learning framework for distinguishing {\it depression} (DP) from {\it non-depression} (ND) using 1,547 harmonized samples drawn from six real-world sources: occupational surveys, student academic stress records, Twitter sentiment data, Reddit depression posts, fine-grained emotion corpora, and behavioural monitoring signals. Academic stress and behavio... More >

With the rapid advancement of artificial intelligence and smart education, academic performance prediction has emerged as a critical research direction within educational data mining. This paper provides a systematic review of recent progress in this field, focusing on technological evolution, application scenarios, model adaptation, emerging trends, and persistent challenges. The development of prediction technologies has progressed through three stages: statistical methods, machine learning, and deep learning. These approaches have been widely applied to grade prediction, academic risk and dropout prediction, knowledge tracing, and personalized learning recommendation. Different models var... More >

Educational Data Mining (EDM) has achieved substantial gains in predictive performance, yet many existing approaches remain centered on single-objective optimization, most often accuracy. This does not adequately reflect the multi-dimensional nature of real-world educational decision-making, which requires balancing interpretability, fairness, robustness, efficiency, and timeliness. This perspective advocates a shift toward multi-objective, interpretable, and trustworthy EDM frameworks. We highlight the role of multi-objective optimization in modeling trade-offs through Pareto-optimal solutions and address the challenge of actionable decision-making through bargaining-based mechanisms, such... More >