Academic Integrity in Teacher Education in the GenAI Era: Academic Coordinators’ Perspectives in Spain

Authors

  • Maria Vallespir-Adillon
  • Rubén Comas-Forgas
  • Carmen Touza Garma
  • Eva María Espiñeira Bellón

Keywords:

teacher training; academic misconduct; generative artificial intelligence; higher education ethics; educational leadership

Abstract

This study explores academic dishonesty in pre-service teacher training programmes from the perspective of academic managers in Spanish universities. Using a quantitative design, based on an online questionnaire and a sample of 198 academic coordinators, it examines perceptions of the prevalence, evolution, and severity of 28 dishonest behaviours, including those involving generative artificial intelligence (GenAI). Results reveal that GenAI-related misconduct is perceived as particularly severe and rapidly increasing, though traditional forms such as plagiarism and contract cheating remain common. Significant differences in perception were found across variables such as age, institutional type, and years of management experience. A composite index (DB-PES) was developed to categorise behaviours by perceived urgency. Findings suggest that academic dishonesty is a dynamic phenomenon requiring systemic and pedagogically grounded responses. Institutions must prioritise ethical training, develop clear policies on AI use, and adopt flexible, responsive mechanisms to address evolving examples of misconduct. This study offers new insights to guide integrity strategies in teacher education.

https://doi.org/10.26803/ijlter.24.10.8

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2025-10-30

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Vol. 24 No. 10 (2025): October 2025

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Copyright (c) 2025 Maria Vallespir-Adillon, Rubén Comas-Forgas, Carmen Touza Garma, Eva María Espiñeira Bellón

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