Publications

ITiCSE 2025 poster

Enhancing Self-Explanation in Student Learning through Large Language Models

Jessica Wen, Angela Zavaleta Bernuy, Naaz Sibia, Andrew Petersen, Michael Liut

Self-explanation deepens understanding by giving learners an opportunity to reflect on what they are learning in a structured way. However, many students struggle to engage in it effectively. We investigate whether large language models (LLMs) can scaffold self-explanations in a flipped computer organization course. In an A/B test, one group used a fixed prompt to compare their explanations with an expert's, while another engaged in an interactive dialogue with an LLM to identify gaps. Although the overall quality of the explanation did not differ significantly between conditions, some students (non-native English speakers and women) reported greater comfort and perceived value when using the LLM.

ITiCSE 2025 poster

Self-Explanations: Does Timing Matter?

Jessica Wen, Bianca Arteaga Alvarez, Jorge Moreno Velasco, Naaz Sibia, Angela Zavaleta Bernuy, Carlos Aníbal Suárez, Andrew Petersen, Michael Liut

Self-explanation promotes active learning by having students articulate their conceptual understanding in their own words. This study investigates whether the timing of self-explanations (before vs. after solving an exercise) relates to performance in a flipped, second-year computer organization course. Although students who self-explained before the exercises achieved higher course marks, the difference was not significant. Still, these findings suggest that early self-explanation may better prepare students for problem-solving when learning new concepts.

NYGH Teaching and Learning Week 2024 poster

Implementation of an Artificial Intelligence Chatbot for Training in Geriatric Medicine Core Competencies

Angela Zavaleta Bernuy, Hammad Sheikh, Marko Choi, Harsh Kumar, Ashton Anderson, Nihal Haque, Michael Liut