This article re-examines the role of assessment within the rapidly evolving landscape of artificial intelligence (AI), focusing specifically on differentiated instruction, and highlights the potential of AI to not only streamline the assessment process but also cultivate a more equitable and student-centered learning environment.
Abstract
This article re-examines the role of assessment within the rapidly evolving landscape of artificial intelligence (AI), focusing specifically on differentiated instruction. As AI tools become more integrated into education, traditional, one-size-fits-all assessment methods are proving to be inadequate for capturing the full scope of student learning. This paper argues for a paradigm shift, urging educators to rethink assessment by embracing a differentiated approach where students can demonstrate their mastery through diverse and creative products. We explore how AI can serve as a powerful ally in this process, offering new ways to automate feedback, analyze complex student outputs, and provide personalized support that goes beyond conventional grading. However, this shift also presents significant challenges, including concerns about academic integrity and the ethical use of AI. By reviewing current literature and proposing a forward-looking framework, this paper highlights the potential of AI to not only streamline the assessment process but also cultivate a more equitable and student-centered learning environment.
The research outcomes demonstrate that AIAS functions effectively as a learning architecture, aligning academic integrity with instructional design, and offers a replicable model for fashion programs and other disciplines seeking responsible AI integration.
D. Shen· PUPIL International Journal...· 0 citations
This paper argues that the core problem extends beyond academic dishonesty to a deeper misalignment between assessment practices and the learning outcomes they are intended to measure, and highlights the need for alternative assessment models that emphasize process over product.
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The idea of AI-resilient assignments maintaining academic integrity with product- and process-based evaluation approach is proposed, similar to the open-book system, where they require human intelligence, independent thinking, and personal understanding to solve them correctly.
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A narrative and strategic framework for student engagement that emphasises enjoyment, active participation, and personal development is developed by fostering environments where students experience intrinsic motivation and recognise the value of their own skills development.
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