Ethical imperatives in AI-driven educational assessment: Framework and implications

• Main Author: LIM, Ming Soon Tristan
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Artificial Intelligence; AI Ethics; Educational Assessments; Framework; Implications; Artificial Intelligence and Robotics
• Online Access: https://ink.library.smu.edu.sg/etd_coll/556; https://ink.library.smu.edu.sg/context/etd_coll/article/1554/viewcontent/GPEN_AY2021_EngD_Lim_Ming_Soon_Tristan.pdf
• Institution: Singapore Management University

This dissertation embarks on an extensive exploration of the ethical challenges emerging from the integration of AI in educational assessments. It uncovers the complex interplay between AI and the ethical imperatives these technologies pose within educational assessments. Amidst the rapid development of AI-enabled educational technologies, such as Ubiquitous, Adaptive, and Immersive technologies, this research identifies a notable gap in literature specifically concerning the ethical imperatives and implications of AI in educational assessments. Addressing this gap, the dissertation has three primary objectives: to comprehend and analyze the underpinning educational technologies driving assessments, to elucidate the intricate relationship between AI, ethics, and educational assessments, and to develop a comprehensive theoretical framework addressing the ethical challenges inherent in AI implementations in assessments. The dissertation contributes to the research field by offering a nuanced examination of AI’s role in educational assessments and its ethical ramifications. It introduces a robust framework to guide educators, policymakers, and researchers through the ethical complexities of AI implementation. This study not only bridges the literature gap but also provides actionable insights for the practical application of AI in educational settings, emphasizing the need for ethical consideration at every stage of the assessment pipeline. The dissertation highlights the dynamic trajectories of educational technologies, stressing the rising importance of adaptive technologies and the transformative role of immersive and ubiquitous technologies in assessments. It underscores the necessity of ethical vigilance in AI applications and validates a generalizable framework for ethically grounded AI-enabled assessments. The dissertation opens pathways for future exploration, suggesting the need for interdisciplinary methodologies, longitudinal studies, deeper analysis of learners' AI understanding, and practical applications of the study’s insights. It calls for a collaborative, informed approach among various stakeholders in education to responsibly harness AI's potential, ensuring its integration not only advances educational practices but does so with ethical integrity and pedagogical effectiveness.