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Alex Barrett; Fengfeng Ke; Nuodi Zhang; Chih-Pu Dai; Saptarshi Bhowmik; Xin Yuan; Sherry Southerland – Journal of Technology and Teacher Education, 2025
This case study reports on the perceptions and dialogic behaviors of 15 preservice K-12 teachers engaging in simulation-based teaching practice with AI-powered student agents. Data included transcripts of text-based classroom dialogue, interviews, observations, and conversation logs. Using mixed-methods analyses and a framework of ambitious…
Descriptors: Preservice Teachers, Artificial Intelligence, Computer Simulation, Dialogs (Language)
Tugba Uygun; Ali Sendur; Beyza Top; Kadriye Cosgun-Basegmez – Education and Information Technologies, 2025
Although augmented reality has become one of the most commonly used materials that support learning, especially in learning geometric concepts, it is avoided to be used in the lessons due to its complex structure. At that point, artificial intelligence working as a personal assistant in many fields can help us learn to produce our own model with…
Descriptors: Preservice Teachers, Mathematics Skills, Geometry, Artificial Intelligence
Rhonda Bondie; Elizabeth City – Learning Professional, 2024
New questions and concerns arise every day about the impact of AI in schools, such as how teachers will learn about AI and leverage it in their classrooms, how they can use it to develop their own teaching expertise, and if AI for educators really leads to better teaching and learning. The authors believe that AI can help teachers become more…
Descriptors: Preservice Teacher Education, Artificial Intelligence, Computer Simulation, Microteaching
Ece Avinç; Fatih Dogan – Journal of Interdisciplinary Studies in Education, 2025
Metaverse in education has the potential to transform education by providing students with interactive, immersive and personalized learning experiences. This study examined the impact of Metaverse on the perceptions of pre-service science teachers. The study was designed in two stages. In the first stage, semi-structured preliminary interview…
Descriptors: Preservice Teachers, Science Teachers, Technology Uses in Education, Computer Simulation
Jacqueline Corcoran; Malitta Engstrom; Kate Ledwith; Gerard Jefferies; Tamara J. Cadet – Journal of Teaching in Social Work, 2025
Competency-based education in social work (CSWE, 2022) demands active learning methods that demonstrate professional competencies and practice behaviors. Role-plays and simulations are methods that link learning in the classroom with practice. This article explores role-play and simulation variants: basic role-play, real play, student-scripted…
Descriptors: Role Playing, Simulation, Social Work, Competency Based Education
Surattana Adipat; Rattanawadee Chotikapanich – Shanlax International Journal of Education, 2024
This study explores the transformative journey of higher education towards smart universities, emphasizing integrating cutting-edge technologies such as augmented reality, virtual reality, artificial intelligence, and biometric systems. This evolution responds to the evolving demands of society, aiming to significantly enhance the educational…
Descriptors: Higher Education, Educational Technology, Technology Uses in Education, Computer Simulation
Elisabeth Bauer; Michael Sailer; Frank Niklas; Samuel Greiff; Sven Sarbu-Rothsching; Jan M. Zottmann; Jan Kiesewetter; Matthias Stadler; Martin R. Fischer; Tina Seidel; Detlef Urhahne; Maximilian Sailer; Frank Fischer – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Simulation, Natural Language Processing
Imtiaz Ahamed; Afsana Azmari – Journal of Education and Learning, 2025
A crucial aspect of this research is determining the effectiveness of the tool developed for this study. This tool is built upon the understanding that technology continually evolves and significantly impacts higher education. It is believed that technology plays a vital role in how students learn in college today. This belief is supported by the…
Descriptors: Educational Technology, Educational History, Automation, Educational Innovation
Nurten Gündüz; Mehmet Sincar – Problems of Education in the 21st Century, 2025
Without regulations for higher education institutions in the metaverse, ethical transgressions are unavoidable. Educational metaverse systems, which integrate artificial intelligence, essentially depend on big data as their core technology, leading to considerable privacy issues. Therefore, this study examines data privacy and security issues, a…
Descriptors: Higher Education, Information Security, Privacy, Artificial Intelligence
Sevil Hanbay-Tiryaki; Fatih Balaman – International Journal of Contemporary Educational Research, 2025
This study aims to explore Web 3.0 technology, a transformative internet evolution that has just begun impacting our lives and is expected to play a pivotal role in shaping the future, alongside the Metaverse and its potential applications in education. Through insights gathered from five field experts via semi-structured interviews, this study…
Descriptors: Web 2.0 Technologies, Technology Uses in Education, Educational Technology, Computer Simulation
Patrick Bowers; Kelley Graydon; Tracii Ryan; Jey Han Lau; Dani Tomlin – Australasian Journal of Educational Technology, 2024
This study presents a scoping review of research on artificial intelligence (AI)- driven virtual patients (VPs) for communication skills training of healthcare students. We aimed to establish what is known about these emergent learning tools, to characterise their design and implementation into training programmes. The preferred reporting items…
Descriptors: Allied Health Occupations Education, Artificial Intelligence, Computer Simulation, College Students
Ulla Hemminki-Reijonen; Noha M. A. M. Hassan; Minna Huotilainen; Jaana-Maija Koivisto; Benjamin Ultan Cowley – npj Science of Learning, 2025
Emerging technologies are transforming education, necessitating research on their optimal integration. This article introduces an Intelligent Virtual Reality (IVR) approach that incorporates Generative Artificial Intelligence (GAI) through two GAI-powered pedagogical characters, aiming to address educational needs. This qualitative descriptive…
Descriptors: Artificial Intelligence, Computer Simulation, College Instruction, Instructional Design
O¨zgu¨r Keles¸; Vincent Brubaker-Gianakos; Vimal Viswanathan; Farshid Marbouti – Journal of STEM Education: Innovations and Research, 2023
This paper describes the application of new Virtual Learning Environments (VLEs) in engineering education. It demonstrates how VLEs improve student learning in two engineering concepts compared with the traditional classroom setting. Literature has conflicting studies on both the advantages and disadvantages of learning in VLEs. The application of…
Descriptors: Educational Environment, Virtual Classrooms, Computer Simulation, Artificial Intelligence
Kotlyar, Igor; Sharifi, Tina; Fiksenbaum, Lisa – International Journal of Artificial Intelligence in Education, 2023
Teamwork skills are commonly evaluated by human assessors, which can be logistically challenging and resource intensive. Technological advancements provide an opportunity for a new assessment method -- virtual behavioural simulations with self-scoring algorithms. This study explores whether a rule-based algorithm can match human assessors at…
Descriptors: Algorithms, Undergraduate Students, Computer Simulation, Evaluation
Tran Ai Cam; Nguyen Huu Thanh Chung – Journal of Learning for Development, 2025
This study employs bibliometric methods to analyse impactful and emerging research topics in the digital education ecosystem, using Scopus data from 2019 to 2023. It introduces a new Impact Factor (IF) that considers productivity, growth rate, core papers, and citations to identify key research fronts. The top five areas identified were artificial…
Descriptors: Literature Reviews, Bibliometrics, Educational Research, Electronic Learning

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