Learning programming has become increasingly popular, with learners from diverse backgrounds and experiences requiring different support. Programming-process analysis helps to identify solver types and needs for assistance. The study examined students' behavior patterns in programming among beginners and non-beginners to identify solver types,…

One expected outcome of physics instruction is that students develop quantitative reasoning skills, including strategies for evaluating solutions to problems. Examples of well-known "canonical" evaluation strategies include special case analysis, unit analysis, and checking for reasonable numbers. We report on responses from three tasks…

We use a validated conceptual multiple-choice survey instrument focusing on thermodynamic processes and the first and second laws of thermodynamics at the level of introductory physics to investigate the problem-property dependence of introductory and advanced student responses to introductory thermodynamics problems after traditional…

[This paper is part of the Focused Collection in Artificial Intelligence Tools in Physics Teaching and Physics Education Research.] We present a study in which a version of a common conservation of mechanical energy introductory physics problem, an object released on an inclined plane, is given to OpenAI's GPT-4 large language model (LLM). We…

Background: Automatically graded programming assignments provide instant feedback to students and significantly reduce manual grading time for instructors. However, creating comprehensive suites of test cases for programming problems within automatic graders can be time-consuming and complex. The effort needed to define test suites may deter some…

Contribution: The proposed operational model offers a detailed framework for understanding the complexities of design thinking. It helps instructors evaluate each stage, promoting the development of high-quality designs. This model emphasizes the link between the various stages and the final design quality, steering students toward achieving…

Background: Conventional reflective learning methodologies in programming education often lack structured guidance and individualised feedback, limiting their pedagogical effectiveness. Whilst computational thinking (CT) offers a systematic problem-solving framework with decomposition, pattern recognition, abstraction, and algorithm design, its…

Dimensional analysis is an algorithm currently in use in almost every chemistry classroom in the United States. Chemistry educators use this procedural tool in the classroom with the intention of providing students with a reliable method to solve many of the relatively simple math problems they encounter. The unintended consequence of using this…

Background: We examine the efficacy of an online collaborative problem-solving (CPS) teaching approach in academic performance and student connections with other peers, among first-year engineering calculus students at a Latin American university. Our research uses communities of practice (CoP) to emphasize the social nature of learning and the…

Reform documents advocate for innovative pedagogical strategies to enhance student learning. A key innovation is the integration of science and engineering practices through engineering design (ED)-based physics laboratory tasks, where students tackle engineering design problems by applying physics principles. While this approach has its benefits,…

DBL is a novel pedagogical approach intended to improve students' conditional knowledge and problem-solving skills by exposing them to a sequence of branching learning decisions. The DBL software provided students with ample opportunities to engage in the expert decision-making processes involved in complex problem-solving and to receive…

The growing use of generative AI (GenAI) has sparked discussions regarding integrating these tools into educational settings to enrich the learning experience of teachers and students. Self-regulated learning (SRL) research is pivotal in addressing this inquiry. One prevalent manifestation of GenAI is the large-language model (LLM) chatbot,…

Understanding particle motion in force fields (PMFF), which encompasses the nature of forces and the relationship between force and motion, is fundamental to mastering mechanics and electromagnetism. Effectively solving PMFF-related problems requires advanced reasoning skills and the ability to apply knowledge across diverse contexts. Despite…