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X-WR-CALNAME;VALUE=TEXT:SocratiQ: A Generative AI-Powered Learning Companion for Personalized Education and Broader Accessibility 
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SUMMARY:SocratiQ: A Generative AI-Powered Learning Companion for Personalized Education and Broader Accessibility 
DESCRIPTION:<p><span>Discussion Leader: Vijay Janapa Reddi, PhD - John L. Loeb Associate Professor of Engineering and Applied Sciences; LInc Faculty Fellow&nbsp;</span><br><br><br><strong>Overview</strong>:&nbsp; The focus will be on <a href="https://urldefense.proofpoint.com/v2/url?u=https-3A__arxiv.org_pdf_2502.00341&amp;d=DwMFaQ&amp;c=WO-RGvefibhHBZq3fL85hQ&amp;r=_Z9N2VTg-HstFhiJIwevZk-gx_fkhjXPregEFGZabTk&amp;m=YSXhqov5GkfqWy0bOw2JtOICtnvgjYqgtOUxmF4RhJATjOR0kCL7xUMcp0jDRdg6&amp;s=UaEJY6ITCphoMUBDfw0ksi04cmrTG7TrwkqroM_lBzg&amp;e="><span>SocratiQLinks to an external site.</span></a>, an AI-powered learning companion we’ve been experimenting with in preparation for the Machine Learning Systems course (CS249r). It provides adaptive quizzes, personalized explanations, and interactive learning experiences. Rather than a formal presentation, this will be a brainstorming session to explore:</p><ul><li>How AI tools like SocratiQ might enhance learning in different disciplines.</li><li>The challenges and concerns around AI-driven education.</li><li>Ways faculty might experiment with AI in their own courses.</li></ul><p>This is an open-ended conversation—whether you’re curious, skeptical, or already using AI, I’d love to hear your thoughts. Hope to see you there!</p><hr><p><br><strong>To Do:&nbsp;</strong><br><br><strong>Biblio Reference:</strong><br>Jabbour, Jason, Kai Kleinbard, Olivia Miller, Robert Haussman, and Vijay Janapa Reddi. 2025. "SocratiQ: A Generative AI-Powered Learning Companion for Personalized Education and Broader Accessibility." arXiv. <a href="https://arxiv.org/pdf/2502.00341"><span>https://arxiv.org/pdf/2502.00341Links to an external site.</span></a>.</p><hr><p><br><strong>Learning Goals</strong><br>&nbsp;</p><p><strong>Examine AI’s Role in STEM Pedagogy</strong></p><ul><li>Critically examine the pedagogical assumptions underlying AI-powered learning tools like SocratiQ and assess their alignment with evidence-based teaching practices.</li><li>Analyze how generative AI shifts the cognitive load in learning—where it enhances student engagement and where it risks passive dependency.</li><li>Debate the implications of AI-driven assessments for STEM students with varying levels of prior knowledge, identifying risks and opportunities for deeper learning.</li><li>Distinguish between AI’s potential as a scaffolding tool for student autonomy and its risks in reinforcing superficial learning.</li></ul><p><strong>Applying AI to Course Redesign with Intentionality</strong></p><ul><li>Evaluate how SocratiQ’s adaptive assessment strategies could be leveraged—or reconfigured—for courses in engineering and applied sciences, considering discipline-specific constraints.</li><li>Design an AI-integrated learning experience that actively mitigates expert blind spots, ensuring accessibility to students at different competency levels.</li><li>Reframe traditional approaches to feedback and assessment by integrating AI-generated formative assessment while maintaining instructor agency in evaluation.</li><li>Generate course design modifications that incorporate AI-assisted inquiry-based learning, ensuring alignment with research-backed active learning strategies.</li></ul><p><strong>Navigating the Faculty Role in AI-Enhanced Learning</strong></p><ul><li>Articulate the evolving role of the instructor when AI mediates student engagement—what should remain faculty-driven versus AI-assisted?</li><li>Formulate a strategy to integrate AI-driven personalized learning while maintaining student accountability, critical thinking, and problem-solving agency.</li><li>Interrogate the risks of AI-driven learning companions in engineering and applied sciences—how do we avoid reinforcing formulaic problem-solving at the expense of conceptual understanding?</li><li>Develop a guiding framework for evaluating new AI tools in STEM education, ensuring alignment with learning goals, cognitive development, and student agency.</li></ul><p><strong>Reflecting on AI’s Broader Pedagogical Implications</strong></p><ul><li>Assess how AI-enhanced learning systems intersect with issues of equity, accessibility, and disciplinary expectations in STEM courses.</li><li>Construct a set of guiding principles for AI integration in engineering education, addressing ethical concerns, faculty oversight, and student autonomy.</li><li>Synthesize insights from SocratiQ and course design discussions into an action plan for iterative pedagogical innovation within SEAS courses.</li></ul><hr><p><br><strong>Take Aways&nbsp;</strong><br>&nbsp;</p><ol><li>AI’s Role in Pedagogy: Strengths and Limitations</li></ol><ul><li>AI tools like SocratiQ can enhance student engagement and personalize learning through adaptive assessments and interactive feedback, but they must be intentionally integrated into course design.</li><li>AI-driven explanations and assessments can support students at varying competency levels, yet faculty must ensure they do not unintentionally reinforce surface learning or discourage deep critical thinking.</li><li>AI can scaffold learning, but it should not replace faculty expertise—the instructor’s role in guiding conceptual understanding and inquiry-based learning remains crucial.<br><br>&nbsp;</li></ul><ol start="2"><li>AI in Course Design: Strategies for Effective Integration</li></ol><ul><li>Align AI use with clear learning goals—AI should support, not dictate, the pedagogical framework of a course.</li><li>Faculty control is essential—AI-generated assessments should complement human-designed evaluation, ensuring that AI does not override faculty-driven curriculum priorities.</li><li>AI can be leveraged to mitigate expert blind spots by dynamically responding to students’ knowledge gaps, but it must be paired with intentional instructional strategies to ensure conceptual mastery.</li><li>Backward design remains critical—AI should not drive content selection or assessment; rather, AI tools should be selected based on pre-defined learning outcomes.<br><br>&nbsp;</li></ul><ol start="3"><li>The Evolving Role of Faculty in AI-Enhanced Learning</li></ol><ul><li>Faculty must guide the ethical and responsible use of AI, ensuring that students remain active learners rather than passive consumers of AI-generated explanations.</li><li>AI’s presence in the classroom changes how instructors provide feedback—faculty should explore ways to balance automated feedback with meaningful instructor intervention.</li><li>Teaching students how to critically engage with AI tools (rather than simply using them for convenience) will be an essential skill in modern STEM education.<br><br>&nbsp;</li></ul><ol start="4"><li>Moving Forward: Faculty Action Items</li></ol><ul><li>Reflect on your own course(s)—where could AI enhance student engagement, assessment, or support, and where might it introduce challenges?</li><li>Develop an AI integration plan—identify one area where AI could be tested in your course, ensuring it aligns with clear pedagogical goals.</li><li>Engage students in discussions about AI’s role in learning—how can we help students use AI as a learning tool rather than a substitute for thinking?</li><li>Continue faculty discussions on AI—what principles should guide the responsible integration of AI into STEM education at SEAS?</li></ul>
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DTSTART:20250214T160000Z
DTEND:20250214T173000Z
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