Implementing and assessing computational modeling in introductory mechanics

Abstract

Students taking introductory physics are rarely exposed to computational modeling. In a one-semester large lecture introductory calculus-based mechanics course at Georgia Tech, students learned to solve physics problems using the VPython programming environment. During the term, 1357 students in this course solved a suite of 14 computational modeling homework questions delivered using an online commercial course management system. Their proficiency with computational modeling was evaluated with a proctored assignment involving a novel central force problem. The majority of students (60.4%) successfully completed the evaluation. Analysis of erroneous student-submitted programs indicated that a small set of student errors explained why most programs failed. We discuss the design and implementation of the computational modeling homework and evaluation, the results from the evaluation, and the implications for computational instruction in introductory science, technology, engineering, and mathematics (STEM) courses.

Epistemology and expectations survey about experimental physics: Development and initial results

“…Some laboratories have introduced new educational technologies (e.g., microcomputer-based labs [7] and VPython [8,9]), others have added an emphasis on particular scientific practices (e.g., measurement and uncertainty [10,11], developing testable questions and designing experiments [12,13], and scientific argumentation [14]), while others have pushed the lab course closer to cuttingedge research by introducing modern physics concepts and apparatus (e.g., single photon quantum optics experiments [15,16]), and others have demonstrated improved conceptual learning gains through research-based lab activities [17]. The diversity of responses reflects both the diversity of goals for the laboratory and the flexibility and adaptability of the laboratory environment to meet many different goals.…”

P 3 : a practice focused learning environment

“…The P 3 appraoch to computational instruction makes use of a non-traditional perspective, which will be outlined in the section on "minimally working programs". [15][16][17][18] It is important to em-phasize that it is not our intention that students become fluent in a computational language (in the case of P 3 : python). Instead, P 3 is an opportunity to introduce students to the utility of computational modeling and some basic programming structures such as iterative loops.…”

Examining Thematic Variation in a Phenomenographical Study on Computational Physics

“…Helping students of physics learn computational methods, tools, and ways of thinking is likely to become a large part of future educational efforts [1]. However, the undergraduate environments in which students use computing are understudied [2,3]. This expanding field of research is open to many unanswered questions such as: "How do students learn computational tools and methods?…”