Academic Honesty in the Age of Artificial Intelligence: A Theory of Planned Behavior Study among Psychology Students in Indonesia

Authors

  • B.M.A.S. Anaconda Bangkara President University
  • Adita Pritasari Institut Teknologi Bandung

DOI:

https://doi.org/10.55324/ijoms.v5i12.1329

Keywords:

academic honesty, academic integrity, artificial intelligence in education, psychology students, theory of planned behavior

Abstract

The rapid adoption of artificial intelligence in higher education provides various learning benefits while also creating new challenges for academic integrity, particularly when AI tools replace students’ independent reasoning and intellectual efforts. This study aimed to examine academic honesty among Indonesian psychology students by testing the explanatory power of the Theory of Planned Behavior within AI-mediated learning environments. A quantitative cross-sectional survey was conducted among 410 psychology students selected through purposive sampling from public and private universities across Indonesia. Data were collected using a 35-item questionnaire and analyzed using Confirmatory Factor Analysis and Structural Equation Modeling with AMOS. The measurement and structural models demonstrated satisfactory fit, reliability, and validity. Attitudes toward honest behavior, subjective norms, and perceived behavioral control significantly predicted behavioral intention, jointly explaining 63% of its variance. Perceived behavioral control was the strongest predictor of behavioral intention. Furthermore, behavioral intention and perceived behavioral control significantly influenced actual honest behavior and explained 58% of its variance. The findings indicate that academic honesty in AI-rich learning environments is supported by ethical evaluations, positive social expectations, and students’ confidence in managing academic demands responsibly. Therefore, universities should combine clear AI-use policies with ethics education, responsible AI literacy, and initiatives that strengthen self-regulation and academic self-efficacy.

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Published

2026-09-29