20 citations · 32 across the 27 of their papers we have counts for
28 papers
Integrative Thinking in Computational Physics Design Essays
Sibatmika Babu, Ravishankar Chatta Subramaniam, Carina M. Rebello +2
This study investigates integrative thinking in undergraduate computational physics design essays (CPDEs) within an engineering design-based introductory physics laboratory. Integr…
Probing AI-generated physics solutions and preparing students to critique them
Nikhil Sanjay Borse, Amir Bralin, Sean Savage +1
This study examines Artificial Intelligence (AI)-generated physics solutions from two connected perspectives: how prompt design shapes these solutions and how students can be prepa…
Exploring Students' Perceptions of Using Generative AI-Assisted Problem Posing
Lindsay Dawson, N. Sanjay Rebello
Problem posing, a pedagogical practice that asks students to generate novel problems or meaningful variations to problems encountered, supports transfer of learning and strengthens…
A bottom-up taxonomy of student discourse with a Socratic AI physics tutor
Syed Furqan Abbas Hashmi, N. Sanjay Rebello
Large language model (LLM) tutors are being deployed in introductory physics courses at a scale that produces transcript corpora far larger than traditional qualitative coding can…
Using LLMs to Detect Growth in Computational Thinking in Introductory Physics
Sean Savage, Anand Shanker, Grace Michlitsch +1
As computation becomes more central to physics education, creating scalable methods to assess authentic computational thinking (CT) in students remains a critical challenge. While…
Assessing AI in Introductory Physics Problem Solving
Amir Bralin, N. Sanjay Rebello
Reasoning or inference-scaling models are the new generation of Large Language Models (LLMs) capable of complex problem solving. To investigate their problem-solving capability in…
Using Large Language Models to Analyze Engagement in Computational Thinking via Computational Physics Essays
Sean Savage, Amir Bralin, Paul Hur +1
As computational thinking (CT) becomes increasingly important to physics education, the need for authentic, project-based assessments has grown. While open-ended multimodal assignm…
Towards Just-in-Time Adaptive Feedback: Enhancing Student Learning via Knowledge-Grounded LLM
Younghun Lee, Amir Bralin, Nobel Sanjay Rebello +1
Educational interventions are effective tools for enhancing student learning. While Large Language Models (LLMs) allow for generating adaptive feedback at scale, current studies la…
Cognitive Load and Situational Interest in Physics Laboratories: A Comparative Study Across Three Instructional Modalities
Razan Hamed, N. Sanjay Rebello
Understanding how an instructional approach shapes student's cognitive resources and engagement is central to improving undergraduate physics education especially for novice learne…
Making Evidence Actionable in Adaptive Learning Closing the Diagnostic Pedagogical Loop
Amirreza Mehrabi, Jason Wade Morphew, Breejha Quezada +1
Adaptive learning often diagnoses precisely yet intervenes weakly, producing help that is mistimed or misaligned. This study presents evidence supporting an instructor-governed fee…
Making Evidence Actionable in Adaptive Learning
Amirreza Mehrabi, Jason W. Morphew, Breejha Quezada +1
Adaptive learning often diagnoses precisely yet intervenes weakly, yielding help that is mistimed or misaligned. This study presents evidence supporting an instructor-governed feed…
Examining Student and AI Generated Personalized Analogies in Introductory Physics
Amogh Sirnoorkar, Winter Allen, Syed Furqan Abbas Hashmi +1
Comparing abstract concepts (such as electric circuits) with familiar ideas (plumbing systems) through analogies is central to practice and communication of physics. Contemporary r…
Help or Hype? Students' Engagement and Perception of Using AI to Solve Physics Problems
Qurat-ul-Ann Mirza, N. Sanjay Rebello
With the rise of large language models such as ChatGPT, interest has grown in understanding how these tools influence learning in STEM education, including physics. This study expl…
Feedback That Clicks: Introductory Physics Students' Valued Features in AI Feedback Generated From Self-Crafted and Engineered Prompts
Amogh Sirnoorkar, N. Sanjay Rebello
Since the advent of GPT-3.5 in 2022, Generative Artificial Intelligence (AI) has shown tremendous potential in STEM education, particularly in providing real-time, customized feedb…
Investigation of the Inter-Rater Reliability between Large Language Models and Human Raters in Qualitative Analysis
Nikhil Sanjay Borse, Ravishankar Chatta Subramaniam, N. Sanjay Rebello
Qualitative analysis is typically limited to small datasets because it is time-intensive. Moreover, a second human rater is required to ensure reliable findings. Artificial intelli…
Sense of Belonging and Intent to Persist: Mediating Role of Motivation and Moderating Role of Gender in Physics and Astronomy Graduate Students
Swagata Sarkar, N. Sanjay Rebello
This study investigates how graduate students' sense of belonging (SB) influences their intent to persist (IP) in physics and astronomy programs, and how this relationship is shape…
AI Reasoning Models for Problem Solving in Physics
Amir Bralin, N. Sanjay Rebello
Reasoning models are the new generation of Large Language Models (LLMs) capable of complex problem solving. Their reliability in solving introductory physics problems was tested by…
Using an LLM to Investigate Students' Explanations on Conceptual Physics Questions
Sean Savage, N. Sanjay Rebello
Analyzing students' written solutions to physics questions is a major area in PER. However, gauging student understanding in college courses is bottlenecked by large class sizes, w…
Analyzing Undergraduate Problem-Solving in Physics Through Interaction With an AI Chatbot
Syed Furqan Abbas Hashmi, N. Sanjay Rebello
Providing individualized scaffolding for physics problem solving at scale remains an instructional challenge. We investigate (1) students' perceptions of a Socratic Artificial Inte…
Dual-Role Dynamics in Prompting: Elementary Pre-service Teachers' AI Prompting Strategies for Representational Choices
Razan Hamed, Amogh Sirnoorkar, N. Sanjay Rebello
Pre-service teachers play a unique dual role as they straddle between the roles of students and future teachers. This dual role requires them to adopt both the learner's and the in…
Students' Perceptions to a Large Language Model's Generated Feedback and Scores of Argumentation Essays
Winter Allen, Anand Shanker, N. Sanjay Rebello
Students in introductory physics courses often rely on ineffective strategies, focusing on final answers rather than understanding underlying principles. Integrating scientific arg…
From Self-Crafted to Engineered Prompts: Student Evaluations of AI-Generated Feedback in Introductory Physics
Amogh Sirnoorkar, N. Sanjay Rebello
The abilities of Generative-Artificial Intelligence (AI) to produce real-time, sophisticated responses across diverse contexts has promised a huge potential in physics education, p…
Exploring the Feasibility of Employing a Hybrid Machine Learning Method to Unpack Student Reasoning Patterns in Physics Essays
Winter Allen, N. Sanjay Rebello
We propose a novel clustering pipeline that combines two classic clustering algorithms to better understand student problem-solving strategies. This unsupervised machine learning m…
Assessing Physics Students' Scientific Argumentation using Natural Language Processing
Winter Allen, Carina M. Rebello, N. Sanjay Rebello
Scientific argumentation is a core science and engineering practice and a necessary 21st Century workforce skill. Due to the nature of large enrollment classes, it is difficult to…