Abstract
The rise of generative AI use in higher education calls for a critical reexamination of academic integrity, revealing its culturally-constructed and context-dependent nature. While institutions scramble to create generative AI policies, many rely on Western-centric definitions of integrity that overlook the diverse cultural and linguistic students’ backgrounds. Traditional frameworks often misunderstand behaviors like patchwork writing or collaborative learning, viewing them as misconduct rather than culturally influenced practices. This paper argues that academic integrity standards differ across cultures and institutions rather than follow universal principles. As generative AI further complicates ideas of authorship and originality, institutions must move beyond punitive responses toward inclusive, pedagogically grounded policies that is both discipline and assignment specific. By explicitly teaching academic integrity practices and ethical generative AI use, every course can contribute to an environment grounded in rigor and equity. Academic integrity, therefore, must be reframed as a developmental and inclusive practice that evolves with context and technology, rather than maintaining a static moral code.
Biography
A composition and rhetoric specialist at West Chester University, Ilknur Sancak-Marusa also teaches professional and technical writing courses and serves as Writing Center Director. Over the past fifteen years, her scholarly agenda has focused on writing studies and developmental education, specifically examining pedagogical approaches that support student writers across diverse academic backgrounds.
Recommended Citation
Sancak-Marusa, I. (2025). Rethinking Academic Integrity: Deconstructing Academic Norms in a Technologically and Culturally Shifting Lanscape. Journal of Access, Retention, and Inclusion in Higher Education, 8(1). Retrieved from https://digitalcommons.wcupa.edu/jarihe/vol8/iss1/3