A new paper proposes a framework for integrating Generative Artificial Intelligence (GenAI) into STEM assessments, balancing the need for academic integrity with preparation for AI-enabled workplaces. The framework, grounded in Evidence-Centered Design, offers decision rules for when to restrict, scaffold, or require GenAI use based on learning objectives and task characteristics. It suggests restricting GenAI for foundational knowledge, scaffolding it to reduce peripheral demands, and requiring it for tasks involving human-AI collaboration and AI literacy, using physics examples to illustrate its application. AI
IMPACT Provides a structured approach for educators to navigate the integration of GenAI in assessments, ensuring learning integrity while preparing students for future AI-collaborative environments.
RANK_REASON Academic paper proposing a framework for GenAI use in STEM assessments. [lever_c_demoted from research: ic=1 ai=1.0]
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