Teacher education faces persistent challenges, including limited access to authentic field experiences and a disconnect between theoretical instruction and classroom practice. While virtual reality (VR) simulations offer an alternative, most are constrained by inflexible design and lack scalability, failing to mirror the complexity of real teaching environments. This study introduces TeacherGen@i, a generative AI (GenAI)-enhanced VR simulation designed to provide pre-service teachers with immersive, adaptive teaching practice through realistic GenAI agents. Using an explanatory case study with a mixed-methods approach, the study examines the simulation’s usability, design challenges, and instructional utility within a university-based teacher preparation course. Data sources included usability surveys and reflective journals, analyzed through thematic coding and computational linguistic analysis using LIWC. Findings suggest that TeacherGen@i facilitates meaningful development of teaching competencies such as instructional decision-making, classroom communication, and student engagement, while also identifying notable design limitations related to cognitive load, user interface design, and instructional scaffolding. This exploratory research offers preliminary insights into the integration of generative AI in teacher simulations and its potential to support responsive and scalable simulation-based learning environments.

This scoping review investigates the roles of intelligent learning companion systems (LCS) within educational settings, as well as the presences artificial intelligence (AI) embodies within these roles, and their application in education. Employing the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines for scoping reviews, we analyzed 24 studies on the multifaceted nature of LCS roles and their implications for learning. AI-empowered LCS were identified as adaptive systems that emulate human learning companions, providing a dynamic social context to offer learners support and companionship. By simulating human-like characteristics, AI-empowered companions enhance personalized learning experiences and outcomes, optimizing educational outcomes. Our review categorized 14 roles played by intelligent LCS, underlining their versatility and potential to adapt to and meet learners’ needs and abilities. This review offers a comprehensive classification of LCS roles, elucidating their presences and illustrating their practical applications in educational contexts. The findings highlight the transformative role of AI in education, demonstrating its capability to mimic and augment human teaching and learning interactions.

This study aims to investigate how an instructional approach that integrates artificial intelligence and digital tools, grounded in the pedagogical characteristics of technology-enhanced instruction shaped by technological advancements, affects teachers’ ai-tpack competencies and students’ ai literacy. The study involved 21 teachers and 344 seventh-grade students and was conducted over the course of one semester. Teachers participated in a professional development ( pd ) program and individualized coaching sessions designed to support the meaningful integration of ai and digital technologies into classroom practice. ai -integrated lessons were implemented across multiple subject areas, and data were collected through surveys, interviews, classroom observations, and lesson plan analyses. Although no statistically significant differences were found for teachers, positive trends were observed across all knowledge domains ( tk , tpk , tck , and tpack ). Furthermore, classroom observations and lesson plan analyses revealed how teachers applied tpack knowledge in their instructional practices. For students, pre- and post-survey results ( n = 148) indicated a significant improvement in overall ai literacy (p < .05), with particularly notable gains in the domain of practical use. Taken together, these findings suggest that ai -integrated instruction holds potential for enhancing teachers’ ai-tpack competencies and students’ ai literacy. The study underscores the importance of sustained professional development and authentically designed learning experiences to support effective ai integration in K-12 education.

목적 본 연구는 가상공간인 메타버스에서 사회문화⋅경제⋅교육 활동 등이 가능해짐에 따라 고등교육 맥락을 기반으로 고등교육수업환경에 적합한 메타버스 교수⋅학습 공간을 개발하고 실제 수업에 적용한 사례 연구이다. 방법 교육용 메타버스 플랫폼 개발과 운영을 위해 해당 교육기관과 교수자, 학습자 그리고 내용 전문가의 의견을 지속적으로 반영할수 있는 래피트 프로토타입 개발방법론을 적용하였다. 연구 과정은 분석, 설계, 개발, 실행 및 평가의 순서로 진행되었으며 최종 개발물의 질 향상, 사용자의 만족도 증진, 개발 시간 최적화를 위해 선행연구와 실제 사례를 분석하였으며 이를 기반으로 사용자 요구조사, 면담 그리고 전문가 타당화를 단계별로 진행하였다. 결과 최종 도출된 메타버스 교수⋅학습 공간은 메인 광장, 본관, 강의실, 행사관, 정각원으로 구성하였으며 3개 교과목을 대상으로3개의 수업을 진행하였다. 수업 강좌에 대한 전반적인 만족도 평균은 4.68점, 메타버스 활용에 대한 만족도 평균은 4.55점으로 나타났다. 결론 본 연구는 교수학습을 목적으로 메타버스 플랫폼을 개발하고 이를 수업에 적용함으로써 교육적 활용 가능성을 탐색했다는 점에 의의가 있다. 추후 플랫폼 기능에 대한 기술적 측면을 추가적으로 보완하고 대학 차원의 지원을 기반으로 한 후속 연구를 통해교육용 메타버스 플랫폼에 대한 다각적인 연구가 필요할 것이다. Objectives This study explores the development and implementation of a metaverse-based teaching and learning space tailored for higher education contexts, as the virtual realm of the metaverse enables diverse socio-cultural, economic, and educational activities. The research focuses on the integration of Metaverse technologies into higher education environments, presenting a case study where the developed Metaverse teaching and learning space is applied in actual classroom settings. Methods For the development and operation of an educational Metaverse platform, we applied a iterative prototyping methodology that allows continuous input from the educational institution, instructors, learners, and content experts. The research process followed the sequence of analysis, design, development, execution, and evaluation. To enhance the quality of the final product, improve user satisfaction, and optimize development time, we analyzed prior research and real-world cases. Based on this analysis, we conducted user surveys, interviews, and expert validation in a step-by-step manner. Results Three courses were partially taught in these spaces. In each class, interactive activities such as role-playing, OX quizzes, presentations and feedback, discussions, and Q&A sessions were carried out. The overall satisfaction score for the three courses was 4.68, and the satisfaction score for the use of the Metaverse was 4.55. Conclusions The significance of this study lies in the exploration of the educational potential of the Metaverse platform by developing it for teaching and learning purposes and applying it to actual classes. Further research is needed to address the technical aspects of platform features and to support the development of an educational Metaverse platform through follow-up studies based on university-level support.

This study aims to develop a ChatGPT-based educational program for instructional designers using the ADDIE model and to verify its effectiveness. An educational program for instructional designers was developed through a review of previous research and case analyses following the ADDIE model. The program involved 36 middle-aged and older instructional designers. To assess the program’s effectiveness, testes were conducted before and after the program with participation of 16 instructional designers. The analysis methods included the paired sample t-test and the non-parametric Wilcoxon signed-rank test. The study’s findings are summarized as follows. First, the educational program was designed in consideration of the characteristics of the learners. This study presented examples of how to develop a training program using ChatGPT based on the ADDIE model, such as the age group of learners, their motivation, and their relevance to learners. Second, as a result of measuring the educational effectiveness of the educational program using ChatGPT for middle-aged and elderly instructional designers, it was found that it had a positive effect on efficacy, intention to continue learning. In conclusion, middle-aged and older instructional designers are need to possess the ability to understand and utilize technology in instructional design.