SocratiQ: A Generative AI-Powered Learning Companion for Personalized Education and Broader Accessibility

Discussion Leader: Vijay Janapa Reddi, PhD - John L. Loeb Associate Professor of Engineering and Applied Sciences; LInc Faculty Fellow 


Overview:  The focus will be on SocratiQLinks to an external site., 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:

• How AI tools like SocratiQ might enhance learning in different disciplines.
• The challenges and concerns around AI-driven education.
• Ways faculty might experiment with AI in their own courses.

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!

To Do: 

Biblio Reference:
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. https://arxiv.org/pdf/2502.00341Links to an external site..

Learning Goals
 

Examine AI’s Role in STEM Pedagogy

• Critically examine the pedagogical assumptions underlying AI-powered learning tools like SocratiQ and assess their alignment with evidence-based teaching practices.
• Analyze how generative AI shifts the cognitive load in learning—where it enhances student engagement and where it risks passive dependency.
• Debate the implications of AI-driven assessments for STEM students with varying levels of prior knowledge, identifying risks and opportunities for deeper learning.
• Distinguish between AI’s potential as a scaffolding tool for student autonomy and its risks in reinforcing superficial learning.

Applying AI to Course Redesign with Intentionality

• Evaluate how SocratiQ’s adaptive assessment strategies could be leveraged—or reconfigured—for courses in engineering and applied sciences, considering discipline-specific constraints.
• Design an AI-integrated learning experience that actively mitigates expert blind spots, ensuring accessibility to students at different competency levels.
• Reframe traditional approaches to feedback and assessment by integrating AI-generated formative assessment while maintaining instructor agency in evaluation.
• Generate course design modifications that incorporate AI-assisted inquiry-based learning, ensuring alignment with research-backed active learning strategies.

Navigating the Faculty Role in AI-Enhanced Learning

• Articulate the evolving role of the instructor when AI mediates student engagement—what should remain faculty-driven versus AI-assisted?
• Formulate a strategy to integrate AI-driven personalized learning while maintaining student accountability, critical thinking, and problem-solving agency.
• 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?
• Develop a guiding framework for evaluating new AI tools in STEM education, ensuring alignment with learning goals, cognitive development, and student agency.

Reflecting on AI’s Broader Pedagogical Implications

• Assess how AI-enhanced learning systems intersect with issues of equity, accessibility, and disciplinary expectations in STEM courses.
• Construct a set of guiding principles for AI integration in engineering education, addressing ethical concerns, faculty oversight, and student autonomy.
• Synthesize insights from SocratiQ and course design discussions into an action plan for iterative pedagogical innovation within SEAS courses.

Take Aways 
 

1. AI’s Role in Pedagogy: Strengths and Limitations

• 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.
• 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.
• 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.
  
   

2. AI in Course Design: Strategies for Effective Integration

• Align AI use with clear learning goals—AI should support, not dictate, the pedagogical framework of a course.
• Faculty control is essential—AI-generated assessments should complement human-designed evaluation, ensuring that AI does not override faculty-driven curriculum priorities.
• 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.
• Backward design remains critical—AI should not drive content selection or assessment; rather, AI tools should be selected based on pre-defined learning outcomes.
  
   

3. The Evolving Role of Faculty in AI-Enhanced Learning

• Faculty must guide the ethical and responsible use of AI, ensuring that students remain active learners rather than passive consumers of AI-generated explanations.
• AI’s presence in the classroom changes how instructors provide feedback—faculty should explore ways to balance automated feedback with meaningful instructor intervention.
• 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.
  
   

4. Moving Forward: Faculty Action Items

• Reflect on your own course(s)—where could AI enhance student engagement, assessment, or support, and where might it introduce challenges?
• Develop an AI integration plan—identify one area where AI could be tested in your course, ensuring it aligns with clear pedagogical goals.
• 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?
• Continue faculty discussions on AI—what principles should guide the responsible integration of AI into STEM education at SEAS?