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Applying a STEM Ways of Thinking Framework for Student-generated Engineering Design-based Physics Problems

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arxiv 2503.05957 v2 pith:CLSILYX6 submitted 2025-03-07 physics.ed-ph

Applying a STEM Ways of Thinking Framework for Student-generated Engineering Design-based Physics Problems

classification physics.ed-ph
keywords physicsanalysisengineeringqualitativethinkingdesigndesign-basededucation
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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This second paper in a multi-part series builds on the first, which introduced the Ways of Thinking for Engineering Design-based Physics (WoT4EDP) framework for STEM education in an introductory undergraduate physics course. Here, we apply the framework to analyze transcripts of group discussions and written reports from 14 student teams as they engaged in a self-generated engineering design (ED) problem in an introductory physics laboratory. We qualitatively examine: (i) the aspects students address in their problem statements; (ii) how they engage in design-based, science-based, and mathematics-based thinking, as well as metacognitive reflection, while developing solutions; and (iii) how they incorporate computational thinking through Python coding. Key findings highlight the need for: (i) increased guidance for iterative problem framing; (ii) structured support for assessing design limitations, engaging in a feasibility study, adopting a systematic approach to applying physics and mathematics in their iterations, and making specific metacognitive reflections; and (iii) integration of Python-based activities into laboratory tasks with appropriate scaffolding. We present our findings through a detailed qualitative analysis, drawing extensively from the qualitative methods literature. We outline our analytical approach, present coding charts, and employ qualitative methods such as thematic analysis and thick description to convey our findings. In doing so, we contribute to ongoing efforts to enhance the rigor of qualitative analysis in physics education research (PER). Based on our analysis, we provide valuable insight for educators and researchers in designing physics-based engineering design tasks and promoting interdisciplinary problem-solving in STEM education.

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  1. Investigation of the Inter-Rater Reliability between Large Language Models and Human Raters in Qualitative Analysis

    physics.ed-ph 2025-08 conditional novelty 4.0

    GPT-4o and GPT-4.5-preview reached moderate to substantial Cohen's kappa with human coders for three of four student thinking themes after per-theme hyperparameter and prompt tuning.