arXiv subjects

Jibeom Seo

Publications and source records attributed to Jibeom Seo.

4 recordsLinked to original sources

arXiv2026

How Does Science Education Research Respond to Sociopolitical Change? A BERTopic Analysis of Korean Research

Research fields do not evolve in isolation: their questions and priorities shift with policy, curriculum reform, and broader social change. Analyzing published literature can reveal not only how a field matures but also how it responds to these conditions. Prior work in science education has focused on identifying research topics and their trends, but paid less attention to the external conditions in which research is produced. We examine Korean science education research from 2008 to 2025, a case in which centralized curriculum revision, government education initiatives, and demographic decline are prominent. Using BERTopic, an embedding-based topic modeling technique, we identify major topics and temporal trends, and analyze their associations with selected sociopolitical factors. We interpret each topic and distinguish three groups: sociopolitical, subject-specific, and student-related topics. Within the first group, science teacher professionalism and curriculum implementation, science education for gifted students, and STEAM education show the strongest associations with sociopolitical conditions, such as government policy initiatives and declining enrollment in science-gifted education, whereas digital-based science education does not. The subject-specific and student-related groups, by contrast, show no comparable movement and are not linked to the external indicators we examine; this pattern is interpreted as reflecting stronger disciplinary grounding. Taken together, these patterns suggest that a topic's anchoring to policy and practice or to academic disciplines shapes how closely it tracks external change. This helps explain why some research agendas move with their national context while others hold steady, and why the same topic may develop differently across countries.

cs.CY↗

arXiv2026

Leveraging learning analytics to enhance immersive teacher simulations: Challenges and opportunities

This chapter examines how data analytics can be leveraged to enhance immersive teacher simulations, situating this inquiry within the broader learning sciences discourse on embodied cognition, data-informed feedback, and teacher professional learning. It explores both conceptual foundations and empirical cases to illustrate how analytics serve as mediational tools that connect immersive experiences with reflective teaching practice. The chapter unfolds in multiple sections: (1) The Innovation Journey: An Overview of Immersive Teacher Simulations outlines the evolution from traditional simulations to XR-based environments, highlighting the need for professional decision-making under realistic constraints. (2) Innovation in Existing Research and Practice situates teacher analytics within the trajectory from descriptive observation to multimodal and predictive modeling. (3) Study Approach and Design details how multimodal data-discourse, behavior, and gaze-from the TeacherGen@i simulation were collected and organized to reveal cognitive distribution of pedagogical discourse and interaction patterns. (4) Findings present the cognitive distribution of preservice teachers' pedagogical discourse and the sequential interaction patterns that emerge in exchange, illustrating how multimodal analytics make pedagogical reasoning processes visible within immersive simulations. (5) Understanding Innovative Practices in Teacher Education examines teaching analytics to enhance immersive teacher simulation based on the findings of the study. (6) Key Takeaways of the Innovation Journey identifies research challenges and design implications for scalable, analytics-enhanced teacher education. Together, these sections position immersive teacher simulations as a pivotal testbed for aligning learning analytics, professional learning, and next-generation immersive learning environment design.

cs.HC↗

arXiv2025

Semantic Network Analysis of Achievement Standards in Physics of 2022 Revised Curriculum

We investigate semantic networks of achievement standards for physics subjects in the 2022 revised curriculum to derive information embedded in the curriculum. We extract each subject's keywords with node strength and random-walk betweenness, detect communities of physics terms by the optimized greedy algorithm, and find the connectivity of physics subjects using bipartite networks. The network analysis reveals three remarkable results: First, keywords are about scientific thinking and practices, evolving to a higher level as the grades increase. Second, there is a lack of connection to learning content in physics. Lastly, achievement standards for 'Integrated Science' are inadequate to fulfill the intended purpose of the curriculum. This is attributed to the reduced learning volume in the 2022 revised curriculum. Our study implies that the curriculum and achievement standards should be improved for the better connectivity of subjects.

physics.ed-ph↗

arXiv2024

Opinion dynamics model of collaborative learning

We propose a simple model to explore an educational phenomenon where the correct answer emerges from group discussion. We construct our model based on several plausible assumptions: (i) We tend to follow peers' opinions. However, if a peer's opinion is too different from yours, you are not much influenced. In other words, your opinion tends to align with peers' opinions, weighted by the similarity to yours. (ii) Discussion among group members helps the opinion to shift toward the correct answer even when the group members do not know it clearly. However, if everyone tells exactly the same, you often get lost and it becomes more difficult to find the correct answer. In other words, you can find the correct answer when everyone has largely different voices. (iii) We are sometimes stuck to our past. If you keep one opinion for a long time, such a memory works like an inertia in classical mechanics. We use our model to perform numerical investigations and find that the performance of a group is enhanced when initial opinions are diverse, that a lower memory capacity makes consensus occur faster, and that a small group size, typically three or four, is beneficial for better group performance.

physics.soc-ph↗