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JE01 (10:20 to 10:30 AM) | Contributed | Perspectives on Evaluation Strategies
Presenting Author: Abolaji Akinyemi, University of Minnesota, Duluth
Additional Author | Michael E Loverude, California State University, Fullerton
Additional Author | John R Thompson, University of Maine
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One expected outcome of physics instruction is that students develop quantitative reasoning skills, including strategies for evaluating solutions to problems. Examples of evaluation strategies include special case analysis, unit analysis, and checking for reasonable numbers. To investigate students’ use of evaluation strategies, we developed and administered tasks prompting students to evaluate symbolic expressions, including the electric field due to three point charges, the velocity of a block at the bottom of an incline with friction, and the final velocities of two masses involved in an elastic collision. Written and interview data were collected at the introductory, sophomore, and junior levels. We classified students’ evaluation strategies into three broad categories: consulting external sources, checking through computation, and comparing to the physical world. We compare our categories to prior work in PER and examine the categories through theoretical lenses of epistemic frames, mathematical modelling, proofs and justifications, and metacognition.
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JE02 (10:30 to 10:40 AM) | Contributed | Observations of Student Resources in Introductory Programming Tutorials
Presenting Author: Austin Anderson, Department of Physics, University of North Florida
Presenting Author | Paige Pressler, Department of Physics, University of North Florida
Additional Author | W. Brian Lane, Department of Physics, University of North Florida
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The use of computation in undergraduate physics education is on the rise, but this implementation faces the challenge of attending to students’ varied degrees of experience with programming. To explore how students approach learning a new programming language, we employ the resources framework, which posits that students approach new learning situations by making use of information or skills (resources) they have already developed. We designed a series of introductory Python tutorials and conducted think-aloud interviews to identify the resources that students activated while completing the tutorials. We present a preliminary analysis of two extreme cases: a student with a rich mathematical background and no programming experience, and a student with a moderate mathematical background and a rich programming experience in multiple programming languages outside of Python. These observations will help inform the further development of these tutorials to explicitly activate helpful resources.
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JE03 (10:40 to 10:50 AM) | Contributed | Relating Computational Thinking Practices and Problem Design Features
Presenting Author: Theodore Bott, Michigan State University
Additional Author | Tyler Stump, Michigan State University
Additional Author | Paul W Irving, Michigan State University
Additional Author | Daryl R McPadden, Michigan State University
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With the growing ubiquity of computation in STEM fields, understanding how to teach computational thinking (CT) practices has become an active research area in the last two decades, with particular emphasis on developing CT frameworks. In this paper, we apply one of these CT frameworks and correlate the results with a task analysis to examine how CT practices relate to specific design features of an in-class problem. We have analyzed video data from two separate groups working on one computational class period, which utilizes a minimally working program to model magnetic field vectors. While still in the initial stages of the study, our preliminary results indicate that what is left out of the minimally working program will impact the CT practices students use, particularly around building computational models. Ultimately, we hope this work will help instructors to design activities that can target & build specific CT practices.
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JE04 (10:50 to 11:00 AM) | Contributed | Leveraging dual-process theories to improve student reasoning about air resistance
Presenting Author: Drew Rosen, University of Maine
Additional Author | MacKenzie R. Stetzer, University of Maine
Additional Author | Beth A. Lindsey, Penn State Greater Allegheny
Additional Author | Andrew Boudreaux, Western Washington University
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On qualitative physics questions, students often reason on the basis of context-specific heuristics rather than systematically applying broader principles. In ongoing work, we have used dual-process theories of reasoning (DPToR) to account for student reasoning patterns on such questions. In this talk, we describe an intervention designed to improve student reasoning about the terminal speed behavior of falling objects. In the intervention condition, students were prompted to reconcile highly available ideas about the drag force with a Newton’s second law analysis. This intervention was intended to simulate a sustained, productive engagement of the analytic process. In the control condition, students received additional practice applying the normative Newton’s second law reasoning in slightly different contexts. After the intervention, the treatment group’s performance was statistically significantly stronger than that of the control group. We are currently working to adapt this intervention to other contexts to promote more productive and flexible physics reasoning.
This material is based upon work supported by the National Science Foundation under Grant Nos. DUE-1821390, DUE-1821123, DUE-1821400, DUE-1821511, and DUE-1821561.
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JE05 (11:00 to 11:10 AM) | Contributed | Adapting a dual-process informed intervention strategy across content domains
Presenting Author: Andrew Boudreaux, Western Washington University
Additional Author | Beth A. Lindsey, Penn State University - Greater Allegheny
Additional Author | Drew J. Rosen, University of Maine
Additional Author | MacKenzie R. Stetzer, University of Maine
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In an ongoing project, we have been using dual-process theories of reasoning to make sense of student difficulties and guide the design of instruction. A focus has been on qualitative tasks in which students give a quick answer, based on an intuitively appealing model, that contradicts physics principles emphasized in their course. We have recently found some success with a HW-based intervention to address a persistent difficulty with air resistance (see Rosen et al., this meeting), and are trying to adapt the intervention to a different content domain. An overarching goal is to identify domain-general curriculum development strategies based on dual process theories. Our target domain involves the balancing of extended objects – and the documented belief that the center of mass divides an object into two pieces of equal mass. In this talk, we describe the intervention strategy, as implemented in the balancing context, and share assessment data.
This material is based upon work supported by the National Science Foundation under Grant Nos. DUE-1821390, DUE-1821123, DUE-1821400, DUE-1821511, and DUE-1821561.
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JE06 (11:10 to 11:20 AM) | Contributed | How often can students co-construct knowledge in quantum mechanics?
Presenting Author: Mary Brundage, University of Pittsburgh - Pittsburgh, PA
Additional Author | Alysa Malespina, University of Pittsburgh - Pittsburgh, PA
Additional Author | Chandralekha Singh, University of Pittsburgh - Pittsburgh, PA
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Collaborative learning can lead to students learning from each other and solving a physics problem correctly not only in situations in which one student knows how to solve the problem, but also when none of the students can solve the problem alone. In the latter situation, students are co-constructing knowledge that helps them solve the problem. In this study, we investigate student learning and frequency of co-construction in quantum mechanics when students work with peers during class but do not receive any feedback from the course instructor.
We thank the National Science Foundation for support.