Enhancing Feedback to Students in Automated Diagram Assessment

Authors Helder Correia, José Paulo Leal, José Carlos Paiva

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Helder Correia
José Paulo Leal
José Carlos Paiva

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Helder Correia, José Paulo Leal, and José Carlos Paiva. Enhancing Feedback to Students in Automated Diagram Assessment. In 6th Symposium on Languages, Applications and Technologies (SLATE 2017). Open Access Series in Informatics (OASIcs), Volume 56, pp. 11:1-11:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2017)


Automated assessment is an essential part of eLearning. Although comparatively easy for multiple choice questions (MCQs), automated assessment is more challenging when exercises involve languages used in computer science. In this particular case, the assessment is more than just grading and must include feedback that leads to the improvement of the students' performance. This paper presents ongoing work to develop Kora, an automated diagram assessment tool with enhanced feedback, targeted to the multiple diagrammatic languages used in computer science. Kora builds on the experience gained with previous research, namely: a diagram assessment tool to compute differences between graphs; an IDE inspired web learning environment for computer science languages; and an extensible web diagram editor. Kora has several features to enhance feedback: it distinguishes syntactic and semantic errors, providing specialized feedback in each case; it provides progressive feedback disclosure, controlling the quality and quantity shown to each student after a submission; when possible, it integrates feedback within the diagram editor showing actual nodes and edges on the editor itself.
  • automated assessment
  • diagram assessment
  • feedback generation,language environments
  • e-learning


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