Designing University Assessment for a World with Artificial Intelligence

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Bol Artificial intelligence presents unprecedented challenges for assessment in higher education, disrupting traditional approaches to evaluating student learning. This has insights for teaching and learning scholars, academic developers, assessment designers, and anyone seeking pedagogically sound approaches to assessment design in the AI era. Artificial intelligence (AI) presents unprecedented challenges for assessment in higher education, disrupting traditional approaches to evaluating student learning. In this collection, the editors address these challenges head-on, grounding responses in long-standing assessment principles that have guided educational practice for decades. Rather than panic-driven responses or technological quick fixes, chapter authors offer frameworks for genuine transformation. AI exposes the vital importance of principles such as validity, authenticity, and meaningful learning. From program-wide reforms to innovative oral assessments, this book presents real examples of assessment evolution happening now. The collection explores both theoretical frameworks and practical realities, examining what's changing in classrooms and what these changes mean for the future of education. By reconnecting with assessment fundamentals while embracing technological possibilities, this essential read provides important insights for teaching and learning scholars, academic developers, assessment designers, institutional leaders and policymakers, and anyone seeking pedagogically sound approaches to assessment design in the AI era.

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Artificial intelligence presents unprecedented challenges for assessment in higher education, disrupting traditional approaches to evaluating student learning. This has insights for teaching and learning scholars, academic developers, assessment designers, and anyone seeking pedagogically sound approaches to assessment design in the AI era. Artificial intelligence (AI) presents unprecedented challenges for assessment in higher education, disrupting traditional approaches to evaluating student learning. In this collection, the editors address these challenges head-on, grounding responses in long-standing assessment principles that have guided educational practice for decades. Rather than panic-driven responses or technological quick fixes, chapter authors offer frameworks for genuine transformation. AI exposes the vital importance of principles such as validity, authenticity, and meaningful learning. From program-wide reforms to innovative oral assessments, this book presents real examples of assessment evolution happening now. The collection explores both theoretical frameworks and practical realities, examining what's changing in classrooms and what these changes mean for the future of education. By reconnecting with assessment fundamentals while embracing technological possibilities, this essential read provides important insights for teaching and learning scholars, academic developers, assessment designers, institutional leaders and policymakers, and anyone seeking pedagogically sound approaches to assessment design in the AI era.


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