Assessing Efficiency in Student Mathematics Performance Using Slack-Based DEA: Integrating Prior Performance, Engagement, and Chapter-Level Results

Assessing student performance in mathematics is often limited to raw scores or averages, which overlook differences in how effectively students use their learning opportunities and fail to identify hidden weaknesses across topics. To address this issue, this study applies the Slack-Based Measure (SBM) model of Data Envelopment Analysis (DEA) to evaluate the efficiency of students’ mathematics performance in a higher education setting. Academic efficiency was assessed based on test scores across three chapters of a standardized assessment. Each student was treated as a Decision-Making Unit (DMU), with pre-assessment, class attendance and pre-university mathematics results as inputs, and chapter-specific scores as outputs. An output-oriented SBM approach was employed to examine how effectively students converted instructional inputs into academic outcomes while also identifying chapter-level slacks that reveal hidden inefficiencies. The results highlight that while some students achieve high efficiency, many demonstrate inefficiencies driven by underperformance in specific chapters despite relatively strong input profiles. The SBM model’s ability to capture slack allows for the precise identification of these gaps, making it possible to diagnose individual weaknesses that traditional measures may overlook. Chapter-level analysis further revealed variability in content mastery, emphasizing the importance of topic-specific interventions. Additionally, efficiency patterns varied across student groups, with attendance and GPA emerging as critical factors influencing learning efficiency. These findings provide actionable insights for educators, including the development of personalized tutoring, targeted revisions, and more effective feedback mechanisms tailored to students’ unique needs. By diagnosing individual strengths and weaknesses, the SBM framework supports evidence-based teaching strategies that enhance overall academic achievement. This study contributes to the growing field of educational analytics by demonstrating how operations research methods can be integrated into classroom evaluation, offering a practical framework for improving instructional quality, supporting student success, and guiding institutional benchmarking.