Related papers: Using reflections to explore student learning duri…

Tool-augmented large language models (LLMs) are usually trained with supervised imitation or coarse-grained reinforcement learning that optimizes single tool calls. Current self-reflection practices rely on heuristic prompts or one-way…

Physics education researchers have argued that authentic physics education includes computation as part of a physics student's training, and many parties have made efforts towards this goal. However, most research on this teaching modality…

The Learning Assistant (LA) model supports instructors in implementing research-based teaching practices in their own courses. In the LA model, undergraduate students are hired to help facilitate research-based collaborative-learning…

The growing integration of generative AI in higher education is transforming how students write, learn, and engage with knowledge. As AI tools become more integrated into classrooms, there is an urgent need for pedagogical approaches that…

Reflection is an often addressed design goal in Human-Computer Interaction (HCI) research. An increasing number of artefacts for reflection have been developed in recent years. However, evaluating if and how an interactive technology helps…

Feedback has a powerful influence on learning, but it is also expensive to provide. In large classes, it may even be impossible for instructors to provide individualized feedback. Peer assessment has received attention lately as a way of…

Education is a goal-oriented field. But if we want to treat education scientifically so we can accumulate, evaluate, and refine what we learn, then we must develop a theoretical framework that is strongly rooted in objective observations…

Many institutions are changing the focus of their introductory physics labs from verifying physics content towards teaching students about the skills and nature of science. As instruction shifts, so too will the ways students approach and…

We have analyzed the impact of taking an associated lab course on the scores on final exam questions in two large introductory physics courses. Approximately a third of the students who completed each course also took an accompanying…

Reward functions are central in reinforcement learning (RL), guiding agents towards optimal decision-making. The complexity of RL tasks requires meticulously designed reward functions that effectively drive learning while avoiding…

We ran a study on engagement and achievement for a first year undergraduate programming module which used an online learning environment containing tasks which generate automated feedback. Students could also access human feedback from…

Traditional high-stakes summative assessments--timed, in-class exams accounting for a large percentage of the term's overall grade--have often received criticism from the educational community. Such assessments tend to prize a particular…

In this paper we put forth a model for physics course reform that uniquely uses proven, research-based active learning strategies to help students improve their physics knowledge and problem-solving skills. In this study, we compared the…

Student learning in instructional physics labs is a growing area of research that includes studies exploring students' beliefs and expectations about experimental physics. To directly probe students' epistemologies about experimental…

We discuss two proof evaluation activities meant to promote the acquisition of learning behaviors of professional mathematics within an introductory undergraduate proof-writing course. These learning behaviors include the ability to read…

Instructional physics labs are critical junctures for many STEM majors to develop an understanding of experimentation in the sciences. Students can acquire useful experimental skills and grow their identities as scientists. However, many…

We present the impact on student self-efficacy of an introductory physics for life-science students course taught using a Team-Based Learning pedagogy. We measured self-efficacy using the validated quantitative Sources of Self-Efficacy in…

We examine whether data generated by explanation techniques, which promote a process of self-reflection, can improve classifier performance. Our work is based on the idea that humans have the ability to make quick, intuitive decisions as…

A variety of activities are commonly used in college physics courses including lab, tutorials, and studio curricula. Instructors must choose among using research-based activities, designing their own activities or modifying existing…

Code generation plays a crucial role in various tasks, such as code auto-completion and mathematical reasoning. Previous work has proposed numerous methods to enhance code generation performance, including integrating feedback from the…