Autors: Antonova, E. V., Minkovska, D. V.
Title: Beyond Correct & Incorrect: Identifying Error Types to Personalise Learning Paths in Computer Science Education
Keywords: adjustment, assessment, error, learning, personalisation

Abstract: In computer science, student assessment scores are usually reduced to 'right' and 'wrong', without considering the errors made. This article proposes a detailed approach to error categorisation - syntax, logical, and theoretical - to analyse the learning process more deeply. Identifying the type of error allows for the creation of personalised learning paths tailored to each student's strengths and weaknesses, enabling educators to focus their efforts and students to receive targeted support effectively. The results demonstrate that this would enhance understanding of the material.

References

    Issue

    2025 34th International Scientific Conference Electronics, ET 2025 - Proceedings, 2025, Albania, https://doi.org/10.1109/ET66806.2025.11204153

    Вид: публикация в международен форум, публикация в реферирано издание, индексирана в Scopus