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AAPT SM 20

Diagnosing Middle-School Students’ Cognition in Argumentation Practices Using Machine Learning-based Assessments

cognitive diagnostics model; argumentation; automatic scoring; machine learning

The 2020 AAPT Virtual Summer Meeting brought together physics educators from around the globe to learn about the latest in physics theory, research methodology and education from leaders in their field. The program featured plenary speakers, sessions, workshops and many special activities.

For more information please visit the 2020 AAPT Virtual Summer Meeting page at: https://www.aapt.org/Conferences/SM2020/index.cfm.


The 2020 AAPT Virtual Summer Meeting brought together physics educators from around the globe to learn about the latest in physics theory, research methodology and education from leaders in their field. 

poster

We present the design and initial implementation of two data-driven Astronomy courses at Ohio State. Both courses teach fundamental astrophysical and statistical concepts using the Python coding language. Astronomy 1221 is a general-education course for first-year students, about half of whom are majors in Astronomy and Astrophysics. Astronomy 3350 is a majors course for 3rd-year students. We review the main features of these courses and how they prepare students for sophomore- and senior-level astrophysics classes and for starting research in data-intensive projects. Especially in the first-year course, the design is intended to improve retention of female students, who leave the major more often than do male students despite having higher grades in their physics and math courses. Finally, we discuss how Astronomy 1221 will fit into a new general-education scheme at OSU, which will roll out starting in the 2021-2022 academic year.

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Introductory Physics for the Life Sciences (IPLS) courses are gaining momentum in the physics education community, with the creation of multiple curricula for a variety of implementation strategies. At Michigan State University, we have designed an integrated lab-lecture (studio style) introductory physics course that meets the needs of life science students. Our design of this course focuses on incorporating computational simulations that model complex biological phenomenon and complement empirical lab investigations. We will present on updates to a unit on diffusion in which we incorporated a series of computational tasks designed to build up students’ understanding of collisions and random motion. In this presentation we will describe changes that we have made to the unit and how those changes supported student understanding and engagement.

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