A Using Latent Class Analysis to Enhance Students' Positive Attitudinal Patterns in Mathematics

Abstract

This study aimed to identify latent classes among Grade 8A – 8D students at Statefields School, Incorporated (SSI) during the 2023–2024 school year to enhance teaching-learning and promote positive attitudes toward Mathematics. The respondents completed the Mathematics Self-Efficacy and Anxiety Questionnaire (MSEAQ), developed by May D. (2017) for her Ph.D. dissertation at the University of Michigan, via Google Forms. Results indicated that a five-class model optimally fits the attitudinal patterns of the students. The latent classes, derived through Latent Class Analysis (LCA), were Class 1 (Math Anxiety), Class 2 (Growth Mindset), Class 3 (Competitive Achiever), Class 4 (Self-Efficacy), and Class 5 (Enthusiasm). Among the 143 respondents, most students were categorized in Class 4 (Self-Efficacy), indicating a high prevalence of self-efficient attitudes. Conversely, students in Class 1 (Math Anxiety) require educators who can proactively foster excitement about math and help them develop confidence as successful problem solvers.