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<p>This study introduces the rubric-based progress score (P-score), a model emphasizing individual student growth, as a complement to conventional assessment. By integrating progress tracking into grading, the P-score offers students a clearer understanding of their academic development over time. Designed to work alongside existing systems, the P-score highlights learners’ efforts and improvements while maintaining fairness and transparency in evaluation. The study addresses three key aspects: (1) the development of the P-score model, (2) its implementation in university-level English courses, and (3) an examination of student perceptions through two surveys (N ≈ 120) to assess its feasibility. Conducted over one academic year, students completed timed writing tests assessed using the P-score rubric. To support feedback and consistency in implementation, generative AI was used for rubric-based writing assessments and feedback generation. Survey results indicate strong student support for the P-score as an intuitive and motivational assessment tool. The findings highlight both its classroom feasibility and areas for further refinement, reflecting the iterative nature of assessment innovation. This study offers empirical insights into progress-based assessment and demonstrates the potential of AI-supported testing as a form of formative feedback in promoting self-directed learning in EFL contexts.</p>

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Tracking progress to foster motivation: implementing a rubric-based P-score model in Japanese university EFL courses

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  • 发表日期：

    2025年8月28日

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  • Terumi Miyazoe

摘要

This study introduces the rubric-based progress score (P-score), a model emphasizing individual student growth, as a complement to conventional assessment. By integrating progress tracking into grading, the P-score offers students a clearer understanding of their academic development over time. Designed to work alongside existing systems, the P-score highlights learners’ efforts and improvements while maintaining fairness and transparency in evaluation. The study addresses three key aspects: (1) the development of the P-score model, (2) its implementation in university-level English courses, and (3) an examination of student perceptions through two surveys (N ≈ 120) to assess its feasibility. Conducted over one academic year, students completed timed writing tests assessed using the P-score rubric. To support feedback and consistency in implementation, generative AI was used for rubric-based writing assessments and feedback generation. Survey results indicate strong student support for the P-score as an intuitive and motivational assessment tool. The findings highlight both its classroom feasibility and areas for further refinement, reflecting the iterative nature of assessment innovation. This study offers empirical insights into progress-based assessment and demonstrates the potential of AI-supported testing as a form of formative feedback in promoting self-directed learning in EFL contexts.