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    Appraising higher education assessment validity: Development of the PANDORA GenAI Susceptibility Rubric

    Autor: 
    Bannister, Peter
    ;
    Santamaría Urbieta, Alexandra
    ;
    Brufau Alvira, Nuria
    Fecha: 
    2025
    Palabra clave: 
    academic integrity; assessment design; Generative AI; higher education; susceptibility rubric
    Revista / editorial: 
    Journal of Applied Learning & Teaching
    Citación: 
    Bannister, P., Santamaría Urbieta, A., & Brufau Alvira, N. (2025). Appraising higher education assessment validity: Development of the PANDORA GenAI Susceptibility Rubric. Journal of Applied Learning & Teaching, 8(1), 41-55. https://doi.org/10.37074/jalt.2025.8.1.20
    Tipo de Ítem: 
    article
    URI: 
    https://reunir.unir.net/handle/123456789/18177
    DOI: 
    https://doi.org/10.37074/jalt.2025.8.1.20
    Dirección web: 
    https://journals.sfu.ca/jalt/index.php/jalt/article/view/2429
    Open Access
    Resumen:
    This paper presents the development and application of the PANDORA GenAI Susceptibility Rubric, a novel tool designed to assess the susceptibility of higher education assessments to the undeclared use of generative artificial intelligence (GenAI) tools. In response to growing concerns about academic integrity and the rising sophistication of GenAI technologies, the rubric provides educators with a structured framework to critically evaluate the validity of their assessments across key criteria, including collaborative authorship, intellectual task complexity, and the opportunity for creativity. Through a mixed-methods design, the rubric was refined to include expert-informed modifications and validated through end-user application across various arts and humanities courses. Results highlight how assessment design can either mitigate or exacerbate GenAI susceptibility, revealing that tasks requiring genuine collaboration, creative thinking, and process-oriented evaluation offer greater resistance to AI manipulation. The rubric also emphasises balancing detailed guidance with student autonomy to avoid facilitating GenAI prompt formulation. This study contributes to the field by offering a practical instrument that promotes more robust, ethically sound, and future-proofed assessment practices. It serves as a critical response to the pressing challenges posed by GenAI in higher education and informs ongoing discourse on academic integrity.
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