arXiv subjects

Carina M. Rebello

Publications and source records attributed to Carina M. Rebello.

4 recordsLinked to original sources

arXiv2025

Assessing Physics Students' Scientific Argumentation using Natural Language Processing

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 individually assess students and provide feedback on their scientific argumentation. The recent developments in Natural Language Processing (NLP) and Machine Learning (ML) provide new opportunities to analyze large collections of student writing efficiently. In this study, we investigate how undergraduate students' scientific argumentation evolves across four semesters of an introductory calculus-based physics course as increasingly structured argumentation scaffolds were introduced. We investigate the use of NLP and ML, specifically topic modeling, to analyze student scientific argumentation across those semesters. We report on the emergent themes present in each semester. Our findings show a clear shift in the thematic focus of student arguments corresponding to the level of scaffolding provided. In semesters with minimal scaffolding, students' arguments emphasized procedural and surface-level features, while semesters with explicit scaffolds exhibited greater concentration around physics-principle-based themes. These results suggest that structured scaffolding supports students in constructing more conceptually grounded scientific arguments and highlights the potential of NLP and ML as scalable approaches for evaluate broad trends in students' scientific argumentation.

physics.ed-ph↗

arXiv2025

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

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.

physics.ed-ph↗

arXiv2025

Presenting a STEM Ways of Thinking Framework for Engineering Design-based Physics Problems

Investigating students' thinking in classroom tasks, particularly in science and engineering, is essential for improving educational practices and advancing student learning. In this context, the notion of Ways of Thinking (WoT) has gained traction in STEM education, offering a framework to explore how students approach and solve interdisciplinary problems. Building on our earlier studies and contributing to ongoing discussions on WoT frameworks, this paper introduces a new WoT framework: Ways of Thinking in Engineering Design based Physics (WoT4EDP). WoT4EDP integrates five key elements: design, science, mathematics, metacognitive reflection, and computational thinking within an undergraduate introductory physics laboratory. This framework offers a novel perspective by emphasizing how these interconnected elements work together to foster deeper learning and holistic problem-solving in Engineering Design based projects. A key takeaway is that this framework serves as a practical tool for educators and researchers to design, implement, and analyze interdisciplinary STEM activities in physics classrooms. We describe the development of WoT4EDP, situate it within the broader landscape of undergraduate STEM education, and provide detailed characterizations of its components. Additionally, we compare WoT4EDP with two contemporary frameworks: Dalal et al. (2021) and English (2023), to glean insights that enhance its application and promote interdisciplinary thinking. This paper is the first of a two-part series. In the upcoming second part, we will demonstrate the application of the WoT4EDP framework, showcasing how it can be used to analyze student thinking in real-world, ED-based physics projects.

physics.ed-ph↗

arXiv2024

Investigating the Design-Science Connection in a multi-week Engineering Design (ED)-based introductory physics laboratory task

Reform documents advocate for innovative pedagogical strategies to enhance student learning. A key innovation is the integration of science and engineering practices through Engineering Design (ED)-based physics laboratory tasks, where students tackle engineering design problems by applying physics principles. While this approach has its benefits, research shows that students do not always effectively apply scientific concepts, but instead rely on trial-and-error approaches, and end up 'gadgeteering' their way to a solution. This leads to what is commonly referred to as the "design-science gap" -- that students do not always consciously apply science concepts while solving a design problem. However, as obvious as the notion of a `gap' may appear, there seems to exist no consensus on the definitions of `design' and `science', further complicating the understanding of this `gap'. This qualitative study addresses the notion of the design-science gap by examining student-groups' discussions and written lab reports from a multi-week ED-based undergraduate introductory physics laboratory task. Building on our earlier studies, we developed and employed a nuanced, multi-layered coding scheme inspired by the Gioia Framework to characterize `design thinking' and `science thinking'. We discuss how student-groups engage in various aspects of design and how they apply concepts physics principles to solve the problem. In the process, we demonstrate the interconnectedness of students' design thinking and science thinking. We advocate for the usage of the term "design-science connection" as opposed to "design-science gap" to deepen both design and scientific thinking. Our findings offer valuable insights for educators in design-based science education.

physics.ed-ph↗