AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2025
Nguyen, A.; Gul, F.; Dang, B.; Huynh, L.; Tuunanen, T.
Designing embodied generative artificial intelligence in mixed reality for active learning in higher education Journal Article
In: Innovations in Education and Teaching International, 2025, ISSN: 14703297 (ISSN).
Abstract | Links | BibTeX | Tags: Active learning, Generative AI, higher education, Mixed reality, Self-regulated learning
@article{nguyen_designing_2025,
title = {Designing embodied generative artificial intelligence in mixed reality for active learning in higher education},
author = {A. Nguyen and F. Gul and B. Dang and L. Huynh and T. Tuunanen},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105004906187&doi=10.1080%2f14703297.2025.2499177&partnerID=40&md5=4a59b74e6278024ec9dadf9ad9e1a50d},
doi = {10.1080/14703297.2025.2499177},
issn = {14703297 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Innovations in Education and Teaching International},
abstract = {Generative Artificial Intelligence (GenAI) technologies have introduced significant changes to higher education, but the role of Embodied GenAI Agents in Mixed Reality (MR) environments is still relatively unexplored. This study was carried out to develop an embodied GenAI system designed to facilitate active learning, self-regulated learning and enhance human-AI shared regulation in educational settings. The study also aimed to understand how adult learners engage with and perceive these anthropomorphic agents in an immersive MR setting, with a particular focus on their effects on active learning and cognitive load. Using an echeloned Design Science Research (eDSR) approach, we developed an MR learning experience incorporating an Embodied GenAI Agent. The application was demonstrated with 26 higher education learners through questionnaires and observational recordings. Our study contributes to the ongoing design and development of AI-based educational tools, with the potential to afford more active and agentic learning experiences. © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.},
keywords = {Active learning, Generative AI, higher education, Mixed reality, Self-regulated learning},
pubstate = {published},
tppubtype = {article}
}
Generative Artificial Intelligence (GenAI) technologies have introduced significant changes to higher education, but the role of Embodied GenAI Agents in Mixed Reality (MR) environments is still relatively unexplored. This study was carried out to develop an embodied GenAI system designed to facilitate active learning, self-regulated learning and enhance human-AI shared regulation in educational settings. The study also aimed to understand how adult learners engage with and perceive these anthropomorphic agents in an immersive MR setting, with a particular focus on their effects on active learning and cognitive load. Using an echeloned Design Science Research (eDSR) approach, we developed an MR learning experience incorporating an Embodied GenAI Agent. The application was demonstrated with 26 higher education learners through questionnaires and observational recordings. Our study contributes to the ongoing design and development of AI-based educational tools, with the potential to afford more active and agentic learning experiences. © 2025 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.
Wang, W. -S.; Lin, C. -J.; Lee, H. -Y.; Huang, Y. -M.; Wu, T. -T.
Enhancing self-regulated learning and higher-order thinking skills in virtual reality: the impact of ChatGPT-integrated feedback aids Journal Article
In: Education and Information Technologies, 2025, ISSN: 13602357 (ISSN).
Abstract | Links | BibTeX | Tags: ChatGPT, Cognitive levels, feedback mechanisms, Higher-order thinking skills, Self-regulated learning, Virtual Reality
@article{wang_enhancing_2025,
title = {Enhancing self-regulated learning and higher-order thinking skills in virtual reality: the impact of ChatGPT-integrated feedback aids},
author = {W. -S. Wang and C. -J. Lin and H. -Y. Lee and Y. -M. Huang and T. -T. Wu},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105002253324&doi=10.1007%2fs10639-025-13557-x&partnerID=40&md5=d737f7160ecfb478201b4f1f960031e4},
doi = {10.1007/s10639-025-13557-x},
issn = {13602357 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Education and Information Technologies},
abstract = {This study explores the integration of ChatGPT technology into Virtual Reality (VR) learning environments to support self-regulated learning (SRL) strategies and foster higher-order thinking skills (HOTS). Utilizing a randomized controlled trial (RCT) design, 81 undergraduate students were randomly assigned to either an experimental group with GPT-feedback-supported VR learning or a control group with traditional feedback-supported VR learning. The VR learning environment focused on embedded IoT tasks, structured into six learning units aligned with Bloom’s taxonomy. Results indicate that the experimental group demonstrated significantly higher cognitive levels across memory, understanding, and application tasks compared to the control group. Notably, GPT feedback markedly improved problem-solving and critical thinking skills, though its impact on creativity was limited. This limitation may be attributed to the directive nature of GPT feedback or the structured scope of learning tasks, which may not have encouraged open-ended creative exploration. SRL abilities were also significantly improved in the experimental group, highlighting the efficacy of GPT feedback in promoting self-reflection, goal setting, and strategy adjustment. The findings underscore the potential of integrating generative AI technologies like ChatGPT into VR learning environments to provide targeted, real-time feedback, thus addressing limitations of traditional VR feedback mechanisms. This integration supports deeper engagement and more effective learning outcomes, particularly in problem-solving and critical thinking, providing valuable insights for future educational technology implementations. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.},
keywords = {ChatGPT, Cognitive levels, feedback mechanisms, Higher-order thinking skills, Self-regulated learning, Virtual Reality},
pubstate = {published},
tppubtype = {article}
}
This study explores the integration of ChatGPT technology into Virtual Reality (VR) learning environments to support self-regulated learning (SRL) strategies and foster higher-order thinking skills (HOTS). Utilizing a randomized controlled trial (RCT) design, 81 undergraduate students were randomly assigned to either an experimental group with GPT-feedback-supported VR learning or a control group with traditional feedback-supported VR learning. The VR learning environment focused on embedded IoT tasks, structured into six learning units aligned with Bloom’s taxonomy. Results indicate that the experimental group demonstrated significantly higher cognitive levels across memory, understanding, and application tasks compared to the control group. Notably, GPT feedback markedly improved problem-solving and critical thinking skills, though its impact on creativity was limited. This limitation may be attributed to the directive nature of GPT feedback or the structured scope of learning tasks, which may not have encouraged open-ended creative exploration. SRL abilities were also significantly improved in the experimental group, highlighting the efficacy of GPT feedback in promoting self-reflection, goal setting, and strategy adjustment. The findings underscore the potential of integrating generative AI technologies like ChatGPT into VR learning environments to provide targeted, real-time feedback, thus addressing limitations of traditional VR feedback mechanisms. This integration supports deeper engagement and more effective learning outcomes, particularly in problem-solving and critical thinking, providing valuable insights for future educational technology implementations. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2025.