Related papers: Using machine learning to understand physics gradu…
Physics education research (PER) is a rapidly growing area of PhD specialization. In this article we examine the trajectories that led respondents into a PER graduate program as well as their expected future trajectories. Data were…
Currently, there is a surge of interest in fair Artificial Intelligence (AI) and Machine Learning (ML) research which aims to mitigate discriminatory bias in AI algorithms, e.g. along lines of gender, age, and race. While most research in…
With the number of Computer Science (CS) jobs on the rise, there is a greater need for Computer Science graduates than ever. At the same time, most CS departments across the country are only seeing 25 to 30 percent of female students in…
Students' attitudes and approaches to problem solving in physics can profoundly influence their motivation to learn and development of expertise. We developed and validated an Attitudes and Approaches to Problem Solving survey by expanding…
Most machine learning theory and practice is concerned with learning a single task. In this thesis it is argued that in general there is insufficient information in a single task for a learner to generalise well and that what is required…
In this work we discuss the impact of nuisance parameters on the effectiveness of machine learning in high-energy physics problems, and provide a review of techniques that allow to include their effect and reduce their impact in the search…
Students face diverse pathways as they journey through undergraduate study. The analysis of student course records can untangle common patterns in course progression, and identify group trends in student outcomes. The current work examines…
The recent progresses in Machine Learning opened the door to actual applications of learning algorithms but also to new research directions both in the field of Machine Learning directly and, at the edges with other disciplines. The case…
At large institutions of higher education, students frequently have a choice whether to attend the introductory physics sequence asynchronously online, on-site in a traditional lecture-setting, or in a reformed studio setting. In this…
Machine learning with application to questions in the physical sciences has become a widely used tool, successfully applied to classification, regression and optimization tasks in many areas. Research focus mostly lies in improving the…
We investigate a new structure for machine learning classifiers applied to problems in high-energy physics by expanding the inputs to include not only measured features but also physics parameters. The physics parameters represent a…
We have studied the impact of incoming preparation and demographic variables on student performance on the final exam in physics 1, the standard introductory, calculus-based mechanics course This was done at three different institutions…
Physics is considered as one of the most prevailing and problematic subjects by the students in the realm of science. Students perceived physics as a difficult subject during high school days and become more evasive when they reach college.…
Women, visible minorities, and other socially disadvantaged groups continue to be underrepresented in STEM education. Understanding students' motivations for pursuing a STEM major, and the roles gender, nationality, parental education…
Machine Learning algorithms have had a profound impact on the field of computer science over the past few decades. These algorithms performance is greatly influenced by the representations that are derived from the data in the learning…
We present comparative case study of three physics department culture from different institutions using the experiences undergraduate women. The three studies conducted in the United States include Johnson's 2020 study in a small physics…
We study the problem of selecting the top-k candidates from a pool of applicants, where each candidate is associated with a score indicating his/her aptitude. Depending on the specific scenario, such as job search or college admissions,…
When considering performing an Introductory Physics for Life Sciences course transformation for one's own institution, life science majors' achievement goals are a necessary consideration to ensure the pedagogical transformation will be…
Increasing student retention (successfully finishing a particular course) and persistence (continuing through a sequence of courses or the major area of study) is currently a major challenge for universities. While students' academic and…
Machine learning encompasses a set of tools and algorithms which are now becoming popular in almost all scientific and technological fields. This is true for molecular dynamics as well, where machine learning offers promises of extracting…