Predictive power of peer assessment: Correlations between evaluators’ scores and academic success in a mathematics preparatory program
Yaniv Biton 1 2 *
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1 Shannan Academic College of Education, Haifa, ISRAEL2 Center for Educational Technology, Tel Aviv, ISRAEL* Corresponding Author

Abstract

This study examines the extent to which students’ performance in peer assessment tasks predicts academic achievement in a mathematics preparatory program. Conducted at the Technion’s Center for Pre-University Education, the study involved approximately 60 students participating in two intensive mathematics classes. A key innovation of this research lies in the structure of the peer assessment process: unlike conventional designs that provide expert-defined rubrics, this study empowered students to independently formulate their own evaluation criteria. Each peer group generated its own set of assessment standards based on internal consensus, without instructor intervention. Despite the variability in rubrics, the peer-generated scores showed statistically significant correlations with both interim and final examination results, as well as with teacher-assigned grades. These findings provide compelling evidence that peer assessment can yield reliable evaluative outcomes even when criteria are student-constructed. Moreover, stronger correlations were observed when tasks were aligned with the formal curriculum and administered later in the program, suggesting development in students’ evaluative proficiency. The study contributes to the discourse on the reliability of peer assessment, challenges assumptions regarding the necessity of expert-driven rubrics and highlights the potential of student-authored frameworks to foster authentic engagement and reflective judgment in mathematical learning contexts.

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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Article Type: Research Article

EURASIA J Math Sci Tech Ed, Volume 21, Issue 9, September 2025, Article No: em2694

https://doi.org/10.29333/ejmste/16774

Publication date: 01 Sep 2025

Online publication date: 18 Aug 2025

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