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Integrated Science Education Journal

an Open Access Journal

Problem-Based Learning Enhances Mathematics Engagement: A Multivariate Examination of Motivation and Interest

Nurina Happy ORCID
Universitas PGRI Semarang ROR
Indonesia
nurinahappy@upgris.ac.id
Zuhri Zuhri
STIM Sukma Medan
Indonesia
Hery Saputra
Universitas Jabal Ghafur ROR
Indonesia
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  • Purpose of the study: Mathematics learning requires instructional approaches that improve not only cognitive achievement but also affective aspects, particularly students' motivation and interest. This study aimed to examine the effects of PBL on mathematics learning motivation, learning interest, and both variables simultaneously.

    Methodology: A quantitative quasi-experimental study employing a nonequivalent control group pretest-posttest design was conducted with 71 tenth-grade students selected through cluster random sampling. The experimental group received PBL, while the control group received conventional instruction. Data were collected using the Mathematics Motivation Questionnaire (16 items) and the Interest in Mathematics Questionnaire (20 items) and analyzed using descriptive statistics and Multivariate Analysis of Variance (MANOVA).

    Main Findings: The results showed that PBL significantly improved mathematics learning motivation (Partial Eta Squared = 0.761) and learning interest (Partial Eta Squared = 0.581). MANOVA further confirmed a significant simultaneous effect of PBL on both affective variables (Wilks’ Lambda = 0.216, p < 0.001). These findings indicate that authentic problem solving, collaboration, and active learning in PBL foster multiple affective outcomes simultaneously.

    Novelty/Originality of this study: The novelty of this study lies in the simultaneous examination of mathematics learning motivation and interest using MANOVA while positioning student engagement as the conceptual mechanism underlying PBL effectiveness. The findings provide empirical support for implementing PBL as a student-centered approach to strengthen affective outcomes in mathematics education and offer a foundation for future studies using Structural Equation Modeling (SEM) to examine the underlying mechanisms.

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    [1]
    “Problem-Based Learning Enhances Mathematics Engagement: A Multivariate Examination of Motivation and Interest”, In. Sci. Ed. J, vol. 7, no. 4, pp. 620–628, Jul. 2026, doi: 10.37251/isej.v7i4.3583.

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