Classification of Upper Secondary School Students Based on Motivation in Mathematics Learning: Factor Analysis and Latent Profile Analysis
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Abstract
This study aimed to analyze the factor structure of mathematics learning motivation among upper secondary school students and to classify students based on their mathematics learning motivation profiles using Latent Profile Analysis. The sample was divided into two phases: Phase 1 consisted of 367 students for Exploratory Factor Analysis (EFA), and Phase 2 consisted of 1,085 students for Latent Profile Analysis (LPA), both obtained through multi-stage random sampling from Grade 10 – 12 students in schools under the Secondary Educational Service Area Office during the first semester of the 2025 academic year. The research instrument was a 26-item mathematics learning motivation scale with a 5-point rating scale, which was validated with IOC values ranging from 0.60 to 1.00 and a reliability coefficient () of 0.933. The findings revealed that (1) The factor structure of mathematics learning motivation comprised three factors: Self-Confidence, Engagement, and Mathematics Anxiety, which together accounted for 59.75% of the total variance, and (2) the Latent Profile Analysis indicated that the five-profile model provided the best fit to the data (Ek = 0.822, AIC = 7155.65, BIC = 7280.39), consisting of the Passive Learners group (2.49%), the Diligent Learners group (58.71%), the Anxious Learners group (17.42%), the Confident and Positive Learners group (16.96%), and the Anxiety-Driven Learners group (4.42%). Furthermore, gender, grade level, and academic track were found to be significantly associated with motivation profiles (p < .001).
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หากผู้เสนอบทความมีความจำเป็นเร่งด่วนในการตีพิมพ์โปรดส่งลงตีพิมพ์ในวารสารฉบับอื่นแทน โดยกองบรรณาธิการจะไม่รับบทความหากผู้เสนอบทความไม่ปฏิบัติตามเงื่อนไขและขั้นตอนที่กำหนดอย่างเคร่งครัด ข้อมูลของเนื้อหาในบทความถือเป็นลิขสิทธิ์ของ Journal of Inclusive and Innovative Education คณะศึกษาศาสตร์ มหาวิทยาลัยเชียงใหม่
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