Problem-solving categorization tasks have been well studied and used as an effective tool for assessment of student knowledge structure. In this study, a traditional free-response categorization test has been modified into a multiple-choice format, and the effectiveness of this new assessment is evaluated. Through randomized testing with Chinese college students, the multiple-choice categorization test has been shown to provide equivalent measurement compared to the open-ended test. In addition, the influence of including diagrams in problems on students’ categorization performances has also been studied, which suggests that the inclusion of diagrams in problems can improve students’ performances in identifying the relevant concepts. The results also show that the knowledge structures of the Chinese college students are in the early transitional stage between novices and experts.

Physics is a subject requiring strong logical thinking, and writing a problem-solving path according to logical thinking can enhance students’ knowledge and problem-solving ability. The purpose of the study was to explore the effects of problem presentation of different scaffolds (MAPS or dynamic figures) on students’ physical problem solving. MAPS scaffold is a modeling applied to problem-solving pedagogy. The study adopts a quasi-experimental design, as participants were divided into four groups tested under different scaffolds. These groups are Traditional group (problems with static figures), MAPS group (MAPS combined with static figures), Dynamic Figure group (problems with dynamic figures), and MAPS + Dynamic Figure group (MAPS combined with dynamic figures). The results indicated that the students assisted by MAPS could more effectively describe and interpret key concepts and knowledge in questions, and they selected formulas appropriately according to the physics conditions. However, the findings did not reveal any significant difference between the dynamic figure. Thus, we will explore dynamic figures in different types of physics questions in future research, so that dynamic figures can be more effectively used by students for physics problem-solving.

As the development and application of large language models (LLMs) in physics education progress, the well-known AI-based chatbot ChatGPT4 has presented numerous opportunities for educational assessment. Investigating the potential of AI tools in practical educational assessment carries profound significance. This study explored the comparative performance of ChatGPT4 and human graders in scoring upper-secondary physics essay questions. Eighty upper-secondary students’ responses to two essay questions were evaluated by 30 pre-service teachers and ChatGPT4. The analysis highlighted their scoring consistency and accuracy, including intra-human comparisons, GPT grading at different times, human-GPT comparisons, and grading variations across cognitive categories. The intraclass correlation coefficient (ICC) was used to assess consistency, while accuracy was illustrated through Pearson correlation coefficient analysis with expert scores. The findings reveal that while ChatGPT4 demonstrated higher consistency in scoring, human scorers showed superior accuracy in most instances. These results underscore the strengths and limitations of using LLMs in educational assessments. The high consistency of LLMs can be valuable in standardizing assessments across diverse educational contexts, while the nuanced understanding and flexibility of human graders are irreplaceable in handling complex subjective evaluations. Keywords: Physics essay question assessment, AI grader, Human graders.

A new round of the reform of college entrance examination is in progress in China, which would inevitably influence high school curriculum, especially physics. According to our statistics, the proportion of students choosing physics as a selective subject decreased significantly after the reform of college entrance examination was carried out. We conducted a study in Shanghai, one of the pilot areas of the reform, to investigate the impact of the new reform policy of college entrance examination on high school physics curriculum with interviews and FCI tests, thus to provide references for the future reform. We found that compared with the conditions before the reform, the high school students from Shanghai learned less about physics and physics teachers has less time to teach and communicate with students. What is more, college freshmen from Shanghai fell behind those who came from other areas in FCI performance before and even after a term of formal instruction.