arXiv subjects

Bilas Paul

Publications and source records attributed to Bilas Paul.

6 recordsLinked to original sources

arXiv2026

P-A.I.R.: A Structured AI-Replication Framework for Active Learning in Introductory Physics

The growing use of generative AI tools among students raises an important pedagogical question: how can AI be structured to promote active learning rather than passive answer-seeking? This study introduces the Physics AI-Replication (P-A.I.R.) framework, in which students identify challenging problems, use AI to explain underlying concepts and solutions, generate similar problems, and practice independently before reviewing answers. Survey data from 39 undergraduate students in algebra-based physics indicate that nearly all participants reported improved conceptual understanding following engagement with P-A.I.R. across the semester, and self-confidence scores were consistently above the scale midpoint (mean = 7.03; range 5-9). A strong association between conceptual clarity and replication helpfulness (Spearman r = 0.582, p < 0.001) supports the framework's design. Qualitative findings highlight conceptual clarification and structured problem-solving. These results suggest that P-A.I.R. offers a practical approach for integrating AI into physics learning.

physics.ed-ph↗

arXiv2026

Who Gets to Do Physics? Occupational Stereotypes in AI-Generated Problem Sets

As AI-generated problem sets gain traction in introductory physics courses, their technical correctness is well established - but the social assumptions embedded in their framing have gone largely unexamined. This study analyzes 600 introductory physics problems generated by four AI systems - Grok~4, GPT-5.2, Claude Sonnet 4.6, and Gemini 3 Flash - across structured prompts involving occupations (CEO, Physicist, High School Teacher, Nurse, Construction Worker, and Migrant Worker). Problems were coded on five dimensions: hazard presence, hazard type, agency role, cognitive role, and object ownership. While the physics content is technically sound across all platforms, our analysis reveals systematic occupational stratification in narrative framing. Hazardous scenarios were concentrated in Migrant Worker and Construction Worker problems, with exposure-related hazards (electrocution, burns, radiation, heat or chemical exposure) especially concentrated in Migrant Worker problems. Passive-accident framing - the persona as the recipient of an injury - appeared in one in eight Migrant Worker problems and never appeared for the Physicist, Teacher, or CEO. Possessive ownership language was reserved almost exclusively for the CEO. These patterns suggest that AI-generated physics problems can introduce surface-level diversity while reproducing occupational hierarchies in who acts, who owns, and who is placed at risk. We discuss implications for physics teaching and offer simple screening strategies for instructors using AI-generated problems.

physics.ed-ph↗

arXiv2026

How Well Do AI Systems Solve AP Physics? A Comparative Evaluation of Large Language Models on Algebra-Based Free Response Questions

The rapid advancement of LLMs has generated growing interest in their potential role in physics education and assessment, yet a focused evaluation of their performance on multi-faceted, free-response physics problems remains underexplored. In this study, we systematically evaluate the performance of four widely accessible AI systems-ChatGPT 4.1 mini, Gemini 2.5 Flash, Claude 4.0 Sonnet, and DeepSeek R1-on AP Physics 1 and 2 free-response questions administered between 2015 and 2025. Model-generated solutions were produced under standardized exam-style prompting and evaluated by three independent physics experts using official College Board scoring guidelines. All models achieved relatively high mean scores (82-92%), indicating strong capability in structured algebraic problem solving. However, substantial year-to-year variability was observed, particularly for AP Physics 1, where statistical testing revealed no consistent performance hierarchy among models. In contrast, AP Physics 2 results showed statistically significant differences, with Gemini and DeepSeek demonstrating more consistent performance than Claude. A qualitative analysis revealed recurring error patterns across all models, including misinterpretation of diagrams and graphs, incorrect graph construction, incorrect reasoning about vector direction, circuit topology errors, partial and misleading qualitative explanations, and difficulties applying three-dimensional concepts such as the right-hand rule. These findings suggest that while contemporary AI systems can effectively support routine physics problem solving, they remain limited in tasks requiring spatial reasoning, visual interpretation, and conceptual integration. The results highlight both the instructional potential and current pedagogical limitations of AI-assisted learning tools in physics education.

physics.ed-ph↗

arXiv2025

Unveiling Gender Dynamics in Introductory Physics Labs

The persistent underrepresentation of women and gender minorities within the physical sciences remains a significant issue. This study investigates gender dynamics in introductory algebra-based physics laboratories, focusing on participation, task preferences, and comfort levels. Statistical analysis revealed no significant gender difference in overall participation rates during lab activities. However, significant gender-based disparities emerged in both task preference [\(\chi^2(\text{df}=3) = 9.548,~ p = 0.023, ~ \alpha = 0.05 \)] and comfort levels [\(\chi^2(\text{df}=3) = 7.906,~ p = 0.048, ~ \alpha = 0.05\)]. Male students significantly preferred and felt more comfortable with hands-on equipment handling and data collection, whereas female students more frequently preferred and reported higher comfort with analytical and documentation tasks like note-taking, calculations, and report writing. Qualitative responses highlighted additional challenges reported by some women, including exclusion from group discussions and reluctance to contribute ideas in male-dominated groups. These findings suggest that while overall participation may appear gender-neutral, gendered patterns in task allocation and comfort persist. The results underscore the need for instructional strategies that promote equitable engagement and foster inclusive laboratory environments in physics education.

physics.ed-ph↗

arXiv2024

Teaching Physics to Life Sciences Students in the SCALE-UP Style

Physics has a reputation among majority of life sciences students for being very complicated and tough. If we leave students with this impression, it is likely that students see physics class as useless and irrelevant to life sciences. Concepts of physics are vital in oder to understand physics based technological tools and biophysical topics essential and relevant for life sciences. This review summarizes approaches for improving teaching and learning in introductory physics courses to life science students in the SCALE- UP style. We also discuss our experiences in adapting IPLS Courses to better meet the needs of life sciences students. to better meet the needs of life sciences students.

physics.ed-ph↗

arXiv2024

Breaking Barriers: Investigating Gender Dynamics in Introductory Physics Lab Classes

The persistent underrepresentation of women and other gender minorities in physical science fields has been an ongoing concern. This study investigates gender dynamics in introductory physics laboratory courses, focusing on whether students of different gender identities exhibit equal inclination and confidence in conducting lab experiments, and whether they face barriers that impact their participation. Conducted across three institutions and involving non-physics STEM students enrolled in algebra-based and calculus-based physics courses, the study found mixed results, with two institutions showing no significant gender-based differences in participation levels during lab activities, while one institution demonstrated significant differences. Chi-square tests revealed no significant association between gender and task preference or comfortability, though the small dataset suggests the need for further investigation. While quantitative analysis provided limited evidence of systematic barriers, qualitative feedback revealed that some female students experienced challenges related to gender dynamics, such as perceived assumptions about competence, being overlooked during discussions, and hesitation to voice opinions in male-dominated groups. These findings highlight the complex influence of gender and institutional factors on laboratory experiences and underscore the need for creating inclusive environments that promote equitable engagement and participation for all gender identities in STEM education.

physics.ed-ph↗