United States

Universities use instructors with varying levels of physics expertise for undergraduate physics instruction, including faculty members, graduate teaching assistants, and undergraduate learning assistants. This study examines the effects of instructor type on students’ ratings of explanation quality. We collected written explanations to common introductory physics questions from highly recommended instructors of each type. Students enrolled in an introductory physics course made pairwise comparisons of the written explanations until a rank order could be generated for each participant. We determined if instructor type could determine placement in a student’s rank order using ordinal regression. Using a relative placement algorithm, we extracted a general rank order for the explanations that reflects consensus; opinion; on the relative quality of the explanations. We present the results as a commentary on the relative effectiveness of different instructor types on providing explanations that students perceive as good explanations.

AAPT WM 22

Comparing perceived explanation quality between different instructor types

undergraduate physics edcuation

instructional explanations

graduate teaching assistants

faculty

learning assistants

AAPT meetings are a great way to reflect on your teaching, recommit to best practices and re-energize your career with new research, products, and techniques. Listen to internationally known plenary speakers, attend sessions, workshops, and special activities. This meeting is an excellent opportunity to share your expertise and learn from and network with leaders in the field.



AAPT SM 22

AAPT meetings are a great way to reflect on your teaching, recommit to best practices and re-energize your career with new research, products, and techniques. Listen to internationally known plenary speakers, attend sessions, workshops, and special activities. This meeting is an excellent opportunity to share your expertise and learn from and network with leaders in the field.

technical paper

This meeting is a great opportunity to explore sessions and workshops designed with your professional development in mind. Present your research and exchange ideas on the latest in teaching and pedagogy. Participate in a wide range of events, activities, plenaries, and so much more, connecting you with peers and colleagues who share your commitment to excellence in physics education.

Since 2014, I have worked with students at Siena College to develop and maintain a website, Particle Physics Playground, that shares simplified datasets from real experiments with teachers and students alike. Python is the preferred way of accessing these data and Jupyter notebooks, hosted on Google's Colab platorm, allow users to get up and running seconds. These exercises have been used at the high-school and college level, both for classroom education and training of new research students, both at Siena and elsewhere. Students can learn about relativistic kinematics through hands-on activities, while developing their python programming skills. This poster will give an overview of the website content as well as future plans.

Particle Physics Playground: engage with real data online using python

The Learning Assistant (LA) Model leverages undergraduate students (LAs) as facilitators of learning. LAs work with instructors and are often in positions where they collaborate with instructors on instructional material development and implementation. LAs often have complementary expertise on the types of technology that their peers use to engage in social and academic settings. This semester, eight Catalyst Emerging Leaders, who are experienced LAs, are advising CSU faculty on how we can better support students in our classes. This work leverages what we have learned since Spring 20, what we are learning in Fall 21, with a vision toward future instructional innovations. Funded by The Partnership for College Completion, the Department of Education, and the National Science Foundation DUE# 1524829, 1911341.

Leveraging a community of learners to envision engaging instructional spaces.

Modified Module Analysis using partial correlations (MMA-P) has proven to be a productive method for studying conceptual inventories. MMA-P can be used to analyze large datasets by forming networks of responses then using community detection algorithms to identify sets of responses that are consistently selected together. MMA-P can be extended by using multilayer network analysis. A multilayer network was constructed with pretest and post-test Force Concept Inventory (FCI) responses from five different institutions using samples ranging from N=10,000 to N=200. Each layer of the multiplex network was represented by a network made from the application of MMA-P to data from each institution. Within each layer, MMA-P finds communities of popular responses. Network comparison methods were then used to understand the similarities and differences between the sets of nodes and communities in the networks. This provides insight into the generality of previously identified properties of the FCI between institutions.

Mulitlayer Network Analysis of the Force Concept Inventory

Research on self-efficacy -- or the confidence in one’s capability to perform a task -- has been shown to predict achievement and persistence in the sciences. Over time, students’ experiences in curricular and/or co-curricular activities may threaten their self-efficacy. To investigate the threats or supports to students’ self-efficacy, we are using a mixed methods approach to collect in-the-moment information about lived experiences. This novel design creates a conversation between the Experience Sampling Method, a quantitative technique using surveys of domain-specific self-efficacy, and daily reflections, a qualitative technique investigating threats and supports toward students’ self-efficacy. Thus, we can build a holistic narrative of which curricular and/or co-curricular activities are affecting a student’s self-efficacy as well as how and why these activities may be affecting their self-efficacy. Through the lens of one student, we will show how the research design is investigating self-efficacy through the conversation between the ESM and daily reflections.

Investigating Students' Self-Efficacy Using Mixed Methods Research

Social network analysis (SNA) has gained popularity as a methodology for understanding patterns of student interactions. Such techniques have been applied extensively to face-to-face but not remote physics courses. To bridge this gap, we surveyed students in four remote introductory physics courses, asking them to report peers with whom they meaningfully interact about the course. We then applied SNA methods to determine how various factors relate to the observed network formations. We find differences in what course content students discuss with peers in their lab and discussion sections. Students with higher final course grades were more connected to their peers in interaction networks related to lecture but not lab content. We also discern several trends between students’ gender and their network position, but no strong patterns with regard to students race/ethnicity. Results suggest that group-forming surveys may be useful tools for instructors to create comfortable social environments for students.

Characterizing the interaction networks of physics students during remote teaching

This study examined the relationship between attending secondary school in a rural locale, first-generation college student status, and persistence in engineering majors at West Virginia’s state flagship university. Students who are rural or first-generation depart engineering by changing majors and by leaving the institution without degrees at higher rates than other students, and patterns of attrition for these students are qualitatively different. High school preparation was a significant predictor of leaving college after the freshmen year with rural and first-generation students at higher risk correcting for high school preparation; however, neither rurality nor first-generation status were significant predictors of continuing in engineering to the sophomore year after controlling for students’ high school academic preparation.

Factors Related to Rural and First-Generation Persistence in Engineering

Since Fall 2019, our team has been in the process of reforming our introductory physics courses using the Investigative Science Learning Environment (ISLE) approach. This, alongside the pandemic which required all courses to be held entirely online for one year, has required us to revise our curricular materials multiple times over the past several years. In this talk we will share some of the strategies we have learned both for developing materials which encourage students to actively participate in their own learning and for creating materials which can be used authentically by any member of the teaching team.

Balancing consistency and authenticity: Lessons learned designing reformed curricular materials

The well documented deficit of physics graduates pursuing education as a career has led to a significant number of high school teachers with little to no background in the discipline, which can result in reduced impact in the classroom. The Mitchell Institute Physics Enhancement Program (MIPEP) was founded in 2012 to address such problems through targeting out-of-field high school physics teachers. MIPEP participants work with Texas University faculty and two master teachers over a two week period, focusing on both subject comprehension and pedagogy for implementation. Here we examine the impact of the virtual version of MIPEP on the 2021 cohort. Participant pre- and post-program knowledge and confidence were measured using an assessment compiled of questions from mechanics, electricity and magnetism, optics, and modern physics. Analysis of our data will be shown, which may encourage other institutions to create similar programs.

Improving Out-Of-Field Preparation for High School Physics Teachers

Since Fall 2019 we have been reforming both our algebra and calculus-based introductory physics courses with the Investigative Science Learning Environment (ISLE) approach. As expected, each academic year, students are initially resistant to the approach. In this talk we will discuss specifics of the resistance to ISLE expressed by students in our calculus based introductory physics course and the quantitative effects of "pep talks" and institutional change sessions. We will also explore possible improvements to our implementation of the ISLE approach to mitigate resistance particularly from students who have already encountered non-ISLE physics.

Overcoming student resistance to active learning during an ISLE-based reform

In Fall 2019 we reformed all of our introductory physics courses with the Investigative Science Learning Environment (ISLE) approach. In this approach, students build physics knowledge by doing science. We used ISLE-based materials to write a curriculum and have made structural changes to support it. The curriculum is taught by a team of 10 instructors (full time faculty, part time lecturers, and graduate TAs) with the help of 10 undergraduate Learning Assistants (LAs). All instructors and LAs attend a pre-semester workshop and weekly prep meetings. Three years into our reform, the curriculum and instructional team has become the “new normal.” 450 students enroll in our courses each semester. The big goal driving our reform is to teach students to think like scientists. We present data showing success and areas of improvement.

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Particle Physics Playground: engage with real data online using python

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Student preferences about instructional explanation strategies in introductory physics classes

Stay up to date with the latest Underline news!

PRESENTATIONS

CONFERENCES

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RESOURCES

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