6 papers
Constructing Evaluation Datasets for Procedural Reasoning: Balancing Naturalness, Grounding, and Multi-Hop Coverage
Sarah Elshabrawy, Rahul K. Dass, Ashok K. Goel
Evaluating procedural reasoning in AI-supported learning systems requires question-answer datasets that are both learner-like and grounded in the instructional knowledge the system…
From Explanation to Diagnosis: Next Generation Interactive Video Coach with Misstep Awareness
Xiao Jin, Rahul K. Dass, Ashok K. Goel
Intelligent tutoring systems excel at generating explanations but rarely provide principled diagnosis of where and why a learner is wrong. We introduce a misstep-aware coaching cap…
Guidelines for Designing AI Technologies to Support Adult Learning
Jennifer M. Reddig, Glen R. Smith, Sanaz Ahmadzadeh Siyahrood +16
AI-powered educational technologies have demonstrated measurable benefits for learners, but their design and evaluation have largely centered on K-12 contexts. As a result, many AI…
Developing Models of Procedural Skills using an AI-assisted Text-to-Model Approach
Rahul K. Dass, Shubham Puri, Arpit Khandelwal +2
Scalable AI tutoring for procedural skill learning requires structured knowledge representations, yet constructing these representations remains a labor-intensive bottleneck. This…
Improving Procedural Skill Explanations via Constrained Generation: A Symbolic-LLM Hybrid Architecture
Rahul Dass, Thomas Bowlin, Zebing Li +2
In procedural skill learning, instructional explanations must convey not just steps, but the causal, goal-directed, and compositional logic behind them. Large language models (LLMs…
Enhanced Question-Answering for Skill-based learning using Knowledge-based AI and Generative AI
Rahul K. Dass, Rochan H. Madhusudhana, Erin C. Deye +4
Supporting learners' understanding of taught skills in online settings is a longstanding challenge. While exercises and chat-based agents can evaluate understanding in limited cont…