This study examines the feasibility and potential advantages of using large language models, in particular GPT-4o, to perform partial credit grading of large numbers of student written responses to introductory level physics problems. Students were instructed to write down verbal explanations of their reasoning process when solving one conceptual…

Artificial intelligence (AI) technologies have been consistently influencing the progress of education for an extended period, with its impact becoming more significant especially after the launch of ChatGPT-3.5 at the end of November 2022. In the field of physics education, recent research regarding the performance of ChatGPT-3.5 in solving…

This study investigates the performance of GPT-4, an advanced AI model developed by OpenAI, on the force concept inventory (FCI) to evaluate its accuracy, reasoning patterns, and the occurrence of false positives and false negatives. GPT-4 was tasked with answering the FCI questions across multiple sessions. Key findings include GPT-4's…

As artificial intelligence (AI) technology rapidly advances, it becomes imperative to equip students with tools to navigate through the many intricate ethical considerations surrounding its development and use. Despite growing recognition of this necessity, the integration of AI ethics into higher education curricula remains limited. This paucity…

[This paper is part of the Focused Collection in Investigating and Improving Quantum Education through Research.] One of the greatest weaknesses of physics education research is the paucity of research on graduate education. While there are a growing number of investigations of graduate student degree progress and admissions, there are very few…

This study investigates the utilisation and perceptions of artificial intelligence (AI) applications among mathematics and science teachers in enhancing students' learning experience in mathematics classrooms. One prominent AI application this research seeks to explore, given its recent rise in popularity and usage, is ChatGPT. The study aims to…

The rapid development of large language models (LLMs) presented opportunities for the transformation of science and STEM education. Research on LLMs was in the exploratory phase, characterized by discussions and observations rather than empirical investigations. This study presented a framework for incorporating LLMs into Science and Engineering…

Human expert problem-solving in science is defined and used to account for scientific discovery. These ideas are used to describe BACON.5, a machine expert problem solver that discovers scientific laws using data-driver heuristics and "expectations" such as symmetry. Implications of BACON.5 type research for traditional science education…

Based on the premise that the quality of domain-specific knowledge is the main determinant of expertise in that domain, an examination was made of the shift from considering general, domain-independent skills and procedures, in both cognitive psychology and artificial intelligence, to the study of the knowledge base. Empirical findings and…

Annotates reference material on artificial intelligence, mostly at an introductory level, with applications to education and learning. Topics include: (1) programing languages; (2) expert systems; (3) language instruction; (4) tutoring systems; and (5) problem solving and reasoning. (JM)

Metacognitive skills may be defined in a variety of ways. Generally, these ways all apply to people's thinking about their own personal thinking. This research study analyzed students' interactions to computer programs to assess their metacognitive skills. The metacognitive skills assessed were: (1) planning a course of action; (2) monitoring the…

Several models for problem solving are discussed, and the idea of a heuristic frame is developed. This concept provides a description of the evolution of problem-solving skills in terms of the growth of the number of algorithms available and increased sophistication in their use. The heuristic frame model is applied to two sets of physical…

Describes an artificial intelligence system known as SOAR that approximates a theory of human cognition. Discusses cognition as problem solving, working memory, long term memory, autonomy and adaptability, and learning from experience as they relate to artificial intelligence generally and to SOAR specifically. Highlights the status of the…

Suggests a method for solving verbal problems in chemistry using a linguistic algorithm that is partly adapted from two artificial intelligence languages. Provides examples of problems solved using the mental concepts of translation, rotation, mirror image symmetry, superpositioning, disjoininng, and conjoining. (TW)

Expert reasoning in the natural sciences appears to make extensive use of a relatively small number of general principles and reasoning strategies, each associated with a larger number of more specific inference patterns. Using a dual declarative hierarchy to represent strategic and factual knowledge, a framework for a robust scientific reasoning…