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Computer simulations have been used to support student learning in physics, not only to boost conceptual understanding but to make labs more widely accessible to different populations. However, their impact on student learning has shown mixed results. To better understand this impact, HTML5-based computer simulations for topics in mechanics were investigated in a large, algebra-based, studio physics course for life science students at a private, research-intensive institution. Over a period of three years, we compared learning outcomes of students using traditional hands-on equipment only, a simulation only, or a hybrid combination of both for activities on energy, momentum, simple harmonic motion, and rotational dynamics. We will present our findings of this study through an equity lens, both from the experience of online learning due to the global pandemic and from consideration of the limited access to lab equipment for many students.

AAPT SM 21

Use of physics simulations in supporting equity and student learning

equity

physics

simulations

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poster

An instructor may often wonder what their students understand from their lessons or may want to know what students already understand before coming to class. While formative assessments can help, they can also be stressful and time consuming. During the fall and spring semesters from 2018 to 2021 in Physics I and Physics II, students reported their level of understanding of the material before and after each class. This information helped to inform the instructor on how to teach the class as well as how well the class went and what material might need to be reviewed. We graphed the average level of understanding for each class session to compare the students’ understanding before and after class, between semesters, and between years. Each semester is analyzed for trends, and we plan to share the interesting results that were found.

Measuring students’ level of understanding in introductory physics courses

This poster analyzes two examples of whiteboard meetings from a college calculus-based introductory physics course taught using University Modeling Instruction. In this pedagogy, students work in small groups to create a solution to the same problem on 2′ × 3′ whiteboards. They then sit in a large circle with their whiteboards held facing in and conduct a student-led whole-class discussion (“board” meeting) to reach a consensus. One example is given of a conversation where students overcame sharp disagreements to eventually reach whole-class consensus and another example is given where they did not. We examine how social positioning contributed to students either successfully examining and resolving different ideas or failing to do so. Our analysis suggests that the way students position themselves in discussions may open or close the collaborative space to productive sense-making.

Social-positioning correlates with consensus building in two contentious large-group meetings

Among the many significant challenges raised by the Covid-19 pandemic, many educators had to face the most significant challenge to convert well-designed in-person instruction methods to online teaching methods. To improve educators' online teaching methods to increase comprehension in classrooms, we collected data from STEM introductory level courses in the form of student feedback surveys, and personal interviews conducted online. We used persona methodology and ethnography to document the diverse learning group in a STEM classroom. Personas are "life-like models, whose characteristics are driven by the various goals and motivations of real or potential users." We used these personas to learn how an individual's learning experience affects their participation, goals, motivations, and expectations during online learning. These personas can support the design of online courses with student- centered approaches that better engage undergraduate students across multiple disciplines.

Personas of Student completing Online Instructions During the COVID-19 Pandemic

Calls to reform to science teaching have elicited numerous responses over the past decade. One avenue of reform, 3 Dimensional Learning (3DL), focuses on what students learn, instead of how students learn. 3DL achieves this by organizing science learning around the same 3 dimensions that experts organize their knowledge: Scientific Practices, Disciplinary Core Ideas, and Crosscutting Concepts. To aid transformations toward 3DL, the 3DL4US group has created protocols to help characterize when 3DL may occur on assessments and in instruction. In this talk, we present initial results that extend this effort to student engagement with the Scientific Practice of Developing and Using Models. We will look at results from student problem solving interviews to see how the practice manifested in their work. These results will help inform us about the effectiveness of instructional efforts to engage students with the Practice of Using Models as we attempt to create 3DL environments.

Student Engagement in the Practice of Developing and Using Models

The term 'Representations' refers to sketches, diagrams, pictures, graphs, tables, and mathematical equations are representations we commonly use in undergraduate physics courses and STEM more broadly. Even though expert instructors are familiar with these representations, the studies show that novice students are often struggling to understand and use these representations. Studies on the use of social semiotics in physics classrooms suggest that the instructors explain representations at a basic level and then, more in-depth, all physics representations. We collect student-generated problem-solving videos (Pencasts) from calculus- based physics courses at UGA. In this study, we analyze we look for patterns of students internalizing and combining representations to solve physics problems. In this poster, we present our initial findings. We find that students commonly use tables and visual representations with individualization to maximize learned skills and incorporate their understanding in the class. We expect to extend our work to other STEM branches.

Students' Problem-Solving Processes Associated with Representations in Pencasts.

Reasoning across different contexts consistently is a challenge when learning physics. Despite demonstrating correct conceptual understanding and reasoning on one task, students often fail to use the same knowledge and skills on similar tasks. Dual-process theories can explain these inconsistencies, asserting that cognition involves two thinking processes: the heuristic, which is fast and automatic, and the analytic, which is slow and deliberate. Inconsistent responses arise when the heuristic process produces an intuitively appealing (but incorrect) response that the analytic process fails to reject. We hypothesize making the dual nature of human cognition explicit and more visible to the students could help them recognize and evaluate intuitive responses more productively. Results of a study designed to probe the impact of such instruction on student learning in introductory calculus-based mechanics courses are presented here.

The effect of dual process theory instruction on student learning*

During the mid-part of the spring 2021 semester, the COVID-19 pandemic forced the conversion of well-designed in-person instruction methods to online teaching methods. During the Fall 2020 semester, Introductory Physics students at the University of Georgia were asked about their experiences with their online instructions during the COVID-19 pandemic, with an idea to use this feedback to improve further instruction in the following semesters. We gathered our research by collecting student feedback surveys from students in SCALE-UP classrooms where group-based learning is prevalent. The survey included multiple choice and open response questions about camera and privacy, preferred methods of group activities, and their tendency to participate. Data was collected across multiple STEM disciplines. Students found the instruction to be presented more clearly when attending in-person, and many requested the use of more real-life examples during class time.

Student Feedback: Transition to Online Instructions During the COVID-19 Pandemic

In Summer 2020, an accelerated, 9-week version of the full-year introductory physics laboratory sequence was offered in the emergency remote teaching (ERT) environment. The three term sequence covers mechanics in the first course, electromagnetism in the second, and finally wave, optics and thermodynamics in the last course. Students had to complete three labs each week. We discuss the process for transitioning the traditional laboratory curriculum of the courses to ERT. We also describe changes to the third course in the sequence that were informed by preliminary results from a study of students’ attitudes conducted during the rapid remote implementation of the Spring 2020 instance of the course. Finally, we show changes in students’ attitudes over the three course sequence.

Students’ Self-Efficacy in an Accelerated Remote Introductory Lab Sequence

Advisors and graduate students are sometimes stuck and not moving their research forward. We use Deliberate Innovation(DI) techniques to understand the specific situations centered around research that graduate students and their advisors find themselves in that may be problematic. A critical element of this is determining whether advisors and advisees show indifference in particular situations. We understand indifference by noticing what people are and are not drawn to in the research setting, and will be focusing on ways in which we have seen it show up. Finding this indifference allows us to know where to focus our attention, with the ultimate goal of finding situations in which we can help graduate students and advisors get unstuck and move their research forward.

Using Deliberate Innovation to Understand Indifference in Graduate Advisor/Advisee Relationships

Motion is used in a variety of ways in introductory mechanics contexts. Given the foundational importance of related ideas such as force and acceleration, it might behoove instructors to understand how their students are interpreting this all-encompassing word. In this study, we explored how beliefs and conceptions about motion are refined or used by undergraduate, upper-division physics students in a series of think-aloud interviews with coupled-multiple response (CMR) items developed from free-response data and with two adapted example questions from the Force and Motion Conceptual Evaluation (FMCE).

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