Cluster analysis of student satisfaction in a criteria-based assessment course with a project-based learning approach

The quality of courses plays a significant role in shaping effective future educators, particularly in mathematics education, where innovative assessment and teaching methods are crucial. This study investigates the experiences and satisfaction of future mathematics teachers enrolled in a course on criteria-based assessment (CBA) techniques, delivered using a project-based learning (PjBL) approach. A total of 98 participants from a university in Kazakhstan provided survey data that were analyzed using cluster analyses. The k-means algorithm identified three distinct clusters of participants: “less engaged or satisfied,” “moderately satisfied,” and “highly engaged and satisfied.” The optimal number of clusters was determined using the elbow method, and 3D scatter plots provided a visual representation of the data patterns. Additional analyses examined gender, prior experience with assessment techniques, and prior experience with in PjBL, highlighting significant variations in satisfaction and engagement levels across these factors. Results showed that students with intermediate knowledge of assessment techniques and prior PjBL experience were more likely to belong to the highly satisfied cluster. Gender distribution indicated a slight tendency for female students to benefit more from the CBA course. Key challenges included complex tasks such as reliability calculations, which impacted the less engaged group more significantly. Findings highlight the importance of aligning course design with learner needs, offering structured support, and integrating foundational training in CBA and PjBL methodologies. This study provides actionable recommendations for enhancing teacher education programs and improving the implementation of innovative teaching and assessment strategies.