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Computational Thinking (CT) has recently become an important practice to study due to its inclusion in the NGSS framework. In response to calls for further investigation into CT, we developed a framework of CT practices specific to the context of computationally integrated introductory physics classrooms. The development of the framework was guided by a comprehensive literature review of existing research around CT and an emergent coding of in-class data. This blending of literature and observations resulted in a robust six-category, fourteen-practice framework of CT practices. The application of previous literature to our specific context highlighted the substantial influence that context can have on how CT practices manifest. The framework was applied to two different classrooms to examine differences between the CT practices that occurred between groups and activities within a classroom. We also demonstrate the ability for this framework to answer multiple questions around curriculum design that involves computational integration. This work was support by the National Science Foundation (DRL-1741575).

AAPT SM 21

Developing and Applying a Computational Thinking Framework in Introductory Physics

computational-thinking

computation

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AAPT SM 22

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How do student perceptions about introductory physics correlate, if at all, with student performance, in both remote and in-person learning environments? Previous studies offer an interesting link between students’ perception of the value of the course and their performance: students with lower perceived value at the start of the semester perform better in in-person learning environments, as compared to those offered remotely. Furthermore, no discernible difference in performance between remote and in-person learning environments was detected for students having higher perceived value of a course. These observations suggest that individual student perceptions are more indicative of performance than modality of instruction. We address the interplay between student perceptions and performance outcomes, in introductory physics at West Point.

Remote vs. In-Person Learning: Perceptions vs. Outcomes in Introductory Physics

In the past few years, we have been developing Interactive video-enhanced tutorials (IVETs) which include web-based activities that lead students through a solution using effective problem-solving strategies. The IVETs, which are designed by incorporating multimedia learning principles, are adaptive and provide different levels of feedback and guidance for different students. They also adapt to students’ affect by providing additional guidance to students who indicate they are confused, frustrated, or bored while completing the IVETs. This presentation will showcase our IVET on Thermal Equilibrium and present results from implementing it in a calculus-based course taught online in the past year.

Improving student understanding of Thermal Equilibrium with an interactive tutorial

This session explains how the Institute of Physics moved all its physics teacher CPD online after over a decade of working directly in schools in the UK and Ireland. Our team of over 50 teacher coaches and IOP colleagues worked in much closer collaboration to support teachers remotely and respond to the new pressures that they were facing. We moved from live support sessions to a blended approach with pre-recorded videos accessed on IOPSpark. There were many deep conversations and a lot of new thinking about what physics pedagogy is vital and lends itself to a short video structure. This session will showcase the greatest hits of the 11-19 videos, including the underpinning education research and technology used. We’ll discuss how these ideas have now been taken back into the physics classroom and what works better on camera than in real life.

Lights, camera, action! From IOP physics coach to Youtuber

Jupyter Notebooks gaining popularity in Universities for scientific computation and programming. Jupyter Notebooks utilize Python programming and are primarily used to handle large data sets. They are also used in scientific computational projects, such as machine learning. Advantages for the educational setting include: it is free to use (with a google account), its enabled to be highly collaborative (like google docs), and has the ability to allow advanced code markup including writing equations, inserting hyperlinks, youtube videos and other media. I developed six Jupyter Notebook lessons introducing high school physics students to computational physics, aimed at teaching them to graph data and solve problems. The large data sets used included the open data repository from the CMS experiment at CERN, where students can access real data to discover a particle.

Integrating Computational Jupyter Notebook Lessons into High School Physics

Large amplitude pendulums are often ignored by introductory physics classes even though students notice deviations from the small angle approximation during physics labs. Using Blockly coding built into PASCO software, students can create models of the motion of a large amplitude pendulum from basic physics principles. The new PASCO scientific Meter Stick Torque Set coupled with rotary sensors and photogates allows for accurate measurement of angular position, angular velocity, and period. This enables students to compare their models to direct measurements to test and refine them. Methods to predict and measure the period of a meter stick oscillating about its end will be demonstrated. Code to predict the motion of the pendulum as a function of time will be shown and the results compared to measurements. A procedure for the experimental derivation of the parallel axis theorem using this equipment also will be shared.


Modeling and Measuring Characteristics of a Large Amplitude Physical Pendulum

STEPP (Scaffolded Training Environment for Physics Programming) is a no-cost interactive instructional tool designed to support the teaching of kinematics and Newton’s Laws of Motion in high school physics. Developed through NSF’s STEM+C program, STEPP focuses on the overlap between physics and computational thinking. STEPP allows users to model and visualize the motion described in physics problems already in their curriculum without any formal programming experience expected or required. Carefully designed with scaffolded levels and dynamic display of motion and graphing, STEPP will be available for use in classrooms this fall at stepp.utdallas.edu. Join us to learn about STEPP and how to access resources including a video workshop introduction.

Introducing STEPP: A Resource for Physics Classrooms Utilizing Computational Thinking

Scaffolded Training Environment for Physics Programming (STEPP) project team has developed a synergistic learning environment for high school physics students to acquire physics concepts and computational thinking (CT) through formative experiences modeling and simulating kinematics using modeling tools based on state diagrams called Finite State Machines (FSMs). Scaffolding and dynamic modeling with FSMs allow students to focus on the aspects of CT that support physics learning, e.g., problem decomposition, abstraction, and algorithms, instead of the aspects that are mainly about programming. Three STEPP learning modules have been developed on 1D/2D kinematics and the Newton’s Laws of Motion using Unity game engine that is free for academic use and widely used in K-16 education and educational research. Each level of each module is designed for students to model a kinematic problem as an FSM and see the simulation result as an animation, graphs, numbers and equations which are all synchronically displayed.

Introducing Finite State Machine based modeling into high school physics

High school physics classrooms across the United States are making efforts to integrate computation into their approach to teaching physics. There is wide agreement on the importance of teaching computational thinking (CT) practices in these types of settings, but little research has focused on the dispositions that students can develop that support the development of CT practices. This presentation examines the case of one high school physics class where students do computation-integrated physics in a group work format. Drawing from a newly theorized framework on CT dispositions and the well-established theory of mindset, we investigate how students take up dispositions and mindset during class, and we examine connections between these theories and how they manifest in our data. We intend to help researchers and practitioners identify students' dispositions so that they can provide opportunities for their students to better develop dispositions and more productively engage with computationally integrated physics.

Dispositions and Mindset in Computation-integrated Physics

Integration of computation and modeling into the physics curriculum has been a defining trend at college level, and increasingly so at high school level. Computation not only enhances active learning and student engagement, it also prepares students with valuable computational thinking and skill sets to be successful in the STEM workforce. Unlike introductory physics where there is broad consensus in the subject matter and level of preparation, there is little such consensus on computation and modeling. In this presentation we will discuss integration of computation into the physics curriculum at UMass Dartmouth (see some examples at https://jwang.sites.umassd.edu/). We hope to stimulate conversations on shared experiences and common ground in computation including goals and preparations between high school and college levels.


Vertical integration of computation into the physics curriculum

(Please upload this from my earlier submission)

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