STEM Education (Dec 2023)

PAIGE: A generative AI-based framework for promoting assignment integrity in higher education

  • Shakib Sadat Shanto,
  • Zishan Ahmed ,
  • Akinul Islam Jony

DOI
https://doi.org/10.3934/steme.2023018
Journal volume & issue
Vol. 3, no. 4
pp. 288 – 305

Abstract

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The integration of Generative Artificial Intelligence (GAI) tools like ChatGPT, Google Bard, and Bing Chat in higher education shows excellent potential for transformation. However, this integration also raises issues in maintaining academic integrity and preventing plagiarism. In this study, we investigate and analyze practical approaches for efficiently harnessing the potential of GAI while simultaneously ensuring the preservation of assignment integrity. Despite the potential to expedite the learning process and improve accessibility, concerns regarding academic misconduct highlight the necessity for the implementation of novel GAI frameworks for higher education. To effectively tackle these challenges, we propose a conceptual framework, PAIGE (Promoting Assignment Integrity using Generative AI in Education). This framework emphasizes the ethical integration of GAI, promotes active student interaction, and cultivates opportunities for peer learning experiences. Higher education institutions can effectively utilize the PAIGE framework to leverage the promise of GAI while ensuring the preservation of assignment integrity. This approach paves the way for a responsible and thriving future in Generative AI-driven education.

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