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Postponing work impacts virtually everyone at some point, especially students. We found academic procrastination is easily observed among students by studying the student’s online submission times. We characterized physics student assignment completion times (ie. procrastintation) behaviors for online homework assignments into 4 completion time classes that clearly distinguish between week-to-week patterns, mean course grades, assignment completion rates, and proportion of women. Consistent with many studies, we find that procrastinating students tend to have lower course grades. Closer examination of exam and non-exam grade components reveals that exam and non-exam components are separately predicted by the two “orthogonal” measures, ACT score and completion time, and we propose that these are measuring so-called cognitive and non-cognitive factors, respectively. Identification of procrastinating students (using completion time) could be important in measuring non-cognitive factors that lead to early identification of at-risk students in physics courses.

AAPT SM 21

Procrastination patterns impact on assignment submission times and grade components

submission times

online assignments

procrastination

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technical paper

The Get the Facts Out project, which is entering its fourth year of funding, has an aggressive research arm that studies the effectiveness of every resource produced by the project as well as perceptions of students and perceptions of faculty at over 50 U.S. institutions. In this presentation we will share several exciting results from the project this year including a blog article that went viral, the impact on students as a result of simply sharing the facts with colleagues, and some critical differences between the challenges within mathematics, chemistry and physics departments. Finally, we will share a couple of new resources including professional STEM teacher recruitment videos and A Teacher’s Life by the Numbers. This project is supported by NSF DUE-1821710 & 1821462

The Latest and Greatest from Get the Facts Out

A few years ago, the IUPUI Physics Department decided to introduce computational methods in its undergraduate curriculum to enhance student learning outcomes and engagement. The overall goal is for our graduates to consider computations as a complement to traditional analytic methods, and to develop the judgment and intuition to use a judicious mix of computational and analytic methods to investigate a problem. Since the project is in its infancy, the onset of the pandemic required some adjustments to the implementation plans. In this talk, I will describe our efforts to get buy-in from every faculty member in the department, training faculty members who were not facile with computations, implementing computations in every course, and developing an assessment instrument. I will also discuss some on-going and future work that is supported by an NSF-IUSE grant to advance the goals of the project and how the pandemic provided some unexpected silver linings.

Normalizing Computations across the Physics Curriculum

Computational modeling can provide a hands-on interactive component in a course that is otherwise entirely Zoom-based. In the introductory, calculus-based course, students can build and explore principle-based models of both hypothetical and real-world systems. They can explore the effect of varying parameters, and can construct models to help determine whether videos of physical phenomena are real or faked. However, the challenges of teaching basic computational ideas to students with no previous computational experience are also magnified in this environment. Creating pre-lab activities to teach basic concepts; ensuring that computational activities are adequately scaffolded, and convincing students to interact with each other in breakout rooms have proven central to success.

Integrating computation in a remote introductory course

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Computational tools and humane instincts: computation in a pandemic

This study investigates what college-level and high-school-level variables significantly predict FMCE (Force and Motion Conceptual Evaluation) pretest scores and whether differences in these variables explain gender differences observed in FMCE pretest scores. The sample consists of students attending a large eastern land-grant university in the US who are enrolled in the introductory calculus-based mechanics class (N=1060). Variables examined include college performance, high school preparation, and non-academic variables such as sense of belonging, self-efficacy, and personality. Correlation analysis and linear regression were used to understand relations between these variables. 



What does the Force and Motion Conceptual Evaluation pretest measure?

Practice exams with immediate feedback and video solutions are among the highest rated learning resources by students taking introductory physics at the University of Illinois. These ratings align with a research showing the positive impact of formative assessment and the testing effect. Despite this alignment, data on our student use of practice exams suggests a majority of students are missing the most important benefits. In particular, the large fraction of students choosing to complete their first practice exam less than 24 hours before the exam, suggests they are primarily being used for cramming. During the Spring 2021 semester we introduced a “mock” proctored exam one week prior to the actual exam. We look at how performance on the mock exam impacted student predictions, preparation and performance on the actual midterm exam. Our results show that despite the valuable formative assessment available from the mock exam, students were resilient in their dependence on cramming. 


Practice exams impact on student exam preparation and performance

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Computational Assessment in Introductory Physics: Codes From Qualitative Interview Analysis

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Using Ranking Question to Assess Students Assistants' PCK-Q

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Development of an Instrument for Analysis of Student Assistants’ PCK-Q

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Procrastination patterns impact on assignment submission times and grade components

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