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The Influence of GenAI on the Evaluation of Computer Programming Students in Higher Education

Authors Teresa Terroso , Mário Pinto

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Document Identifiers

Subject Classification

ACM Subject Classification
  • Computing methodologies
  • Applied computing → Computer-managed instruction
Keywords
  • Generative Artificial Intelligence
  • Computer Programming Education
  • Student Assessment
  • Teaching and Learning
  • Higher Education

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Abstract

Artificial Intelligence (AI) has assumed an increasingly prominent role in education, transforming the dynamics of teaching and learning while introducing new pedagogical opportunities and challenges. In computer programming education, generative AI tools have had a particularly profound impact. Historically, computer programming education has emphasized problem-solving skills, syntax accuracy, and code efficiency. However, the emergence of generative AI models capable of supporting automatic code generation, producing high-quality code snippets and entire programs, personalized explanations and tutoring, and real-time debugging, has triggered a paradigm shift. These tools make learning processes and assessment less effective and less clear about students' true knowledge. In this context, the paper explores three key dimensions: the broader impact of AI in education, the new challenges that AI presents in teaching and learning computer programming in higher education, and the implications for student assessment, an essential element of the educational process. To investigate these topics, we conducted an online survey targeting Portuguese higher education instructors teaching programming-related courses. Our primary objective was to understand the changes introduced in evaluation methods and criteria due to the growing use of generative AI tools, particularly those focused on code generation.

Cite As Get BibTex

Teresa Terroso and Mário Pinto. The Influence of GenAI on the Evaluation of Computer Programming Students in Higher Education. In 6th International Computer Programming Education Conference (ICPEC 2025). Open Access Series in Informatics (OASIcs), Volume 133, pp. 18:1-18:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/OASIcs.ICPEC.2025.18

Author Details

Teresa Terroso
  • ID+, ESMAD, Polytechnic Institute of Porto, Portugal
Mário Pinto
  • ID+, ESMAD, Polytechnic Institute of Porto, Portugal

References

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