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 expand the Abstract, Links and BibTex record for each paper.
2025
Juarez, A.; Rábago, J.; Pliego, A.; Salazar, G.; Hinrichsen, C.; Castro, M.; Pachajoa, T.
Innovative Methodology for the Integration of Emerging Technologies in Global Education: Mixed Realities, AI, Metaverse, and SDGs Proceedings Article
In: Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 9798350355239 (ISBN).
Abstract | Links | BibTeX | Tags: Artificial intelligence, Arts computing, Collaborative learning, E-Learning, Education computing, Educational Innovation, Educational innovations, Educational Technology, Emerging technologies, Engineering education, Global education, High educations, higher education, Innovative methodologies, Me-xico, Metaverse, Metaverses, Mixed Realities, Mixed reality, Product design, Sebastian, Social aspects, Students, Sustainable development, Sustainable Development Goals, Teaching, Technical skills
@inproceedings{juarez_innovative_2025,
title = {Innovative Methodology for the Integration of Emerging Technologies in Global Education: Mixed Realities, AI, Metaverse, and SDGs},
author = {A. Juarez and J. Rábago and A. Pliego and G. Salazar and C. Hinrichsen and M. Castro and T. Pachajoa},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105011951378&doi=10.1109%2FIFE63672.2025.11024834&partnerID=40&md5=4e101ad649487ce729c3a5fa9e875559},
doi = {10.1109/IFE63672.2025.11024834},
isbn = {9798350355239 (ISBN)},
year = {2025},
date = {2025-01-01},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The academic collaboration among Tecnologico de Monterrey (Mexico), the University of San Sebastián (Chile), and the Catholic University of Colombia was an innovative effort to transform the teaching of the "Formal Representation of Space" through the use of emerging technologies. This project was based on the convergence of the theory of Community of Inquiry (CoI), International Collaborative Online Learning (COIL), and the integration of Mixed Realities, Metaverse, and generative artificial intelligence. The central objective of this collaboration was to improve the technical and creative skills of students of architecture, industrial design, digital art, communication, and music production through a pedagogical approach that utilizes 3D spatial visualization and intercultural interaction. The use of the Tec Virtual Campus's Metaverse and the Global Classroom program was instrumental in facilitating real-time collaboration among students from different countries, allowing for the creation of joint projects that reflect a deep understanding of the Sustainable Development Goals (SDGs). This effort resulted in an advanced methodology that improves students' technical skills and promotes a meaningful global commitment to sustainability and social responsibility, reflecting the transformative power of international collaborative education. © 2025 Elsevier B.V., All rights reserved.},
keywords = {Artificial intelligence, Arts computing, Collaborative learning, E-Learning, Education computing, Educational Innovation, Educational innovations, Educational Technology, Emerging technologies, Engineering education, Global education, High educations, higher education, Innovative methodologies, Me-xico, Metaverse, Metaverses, Mixed Realities, Mixed reality, Product design, Sebastian, Social aspects, Students, Sustainable development, Sustainable Development Goals, Teaching, Technical skills},
pubstate = {published},
tppubtype = {inproceedings}
}
The academic collaboration among Tecnologico de Monterrey (Mexico), the University of San Sebastián (Chile), and the Catholic University of Colombia was an innovative effort to transform the teaching of the "Formal Representation of Space" through the use of emerging technologies. This project was based on the convergence of the theory of Community of Inquiry (CoI), International Collaborative Online Learning (COIL), and the integration of Mixed Realities, Metaverse, and generative artificial intelligence. The central objective of this collaboration was to improve the technical and creative skills of students of architecture, industrial design, digital art, communication, and music production through a pedagogical approach that utilizes 3D spatial visualization and intercultural interaction. The use of the Tec Virtual Campus's Metaverse and the Global Classroom program was instrumental in facilitating real-time collaboration among students from different countries, allowing for the creation of joint projects that reflect a deep understanding of the Sustainable Development Goals (SDGs). This effort resulted in an advanced methodology that improves students' technical skills and promotes a meaningful global commitment to sustainability and social responsibility, reflecting the transformative power of international collaborative education. © 2025 Elsevier B.V., All rights reserved.
Anvitha, K.; Durjay, T.; Sathvika, K.; Gnanendra, G.; Annamalai, S.; Natarajan, S. K.
EduBot: A Compact AI-Driven Study Assistant for Contextual Knowledge Retrieval Proceedings Article
In: Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 9798331507756 (ISBN).
Abstract | Links | BibTeX | Tags: Chatbots, Computer aided instruction, Contextual knowledge, Curricula, Digital Education, E-Learning, Education computing, Educational Technology, Engineering education, Indexing (of information), Information Retrieval, Intelligent systems, Knowledge retrieval, LangChain Framework, Language Model, Large language model, learning experience, Learning experiences, Learning systems, LLM, PDF - Driven Chatbot, Query processing, Students, Teaching, Traditional learning, Virtual Reality
@inproceedings{anvitha_edubot_2025,
title = {EduBot: A Compact AI-Driven Study Assistant for Contextual Knowledge Retrieval},
author = {K. Anvitha and T. Durjay and K. Sathvika and G. Gnanendra and S. Annamalai and S. K. Natarajan},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105013615976&doi=10.1109%2FGINOTECH63460.2025.11077097&partnerID=40&md5=b08377283f2ea2ee406d38d1d23f1e42},
doi = {10.1109/GINOTECH63460.2025.11077097},
isbn = {9798331507756 (ISBN)},
year = {2025},
date = {2025-01-01},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {In the evolving landscape of educational technology, intelligent systems are redefining traditional learning methods by enhancing accessibility, adaptability, and engagement in instructional processes. This paper presents EduBot, a PDF-Driven Chatbot developed using advanced Large Language Models (LLMs) and leveraging frameworks like LangChain, OpenAI's Chat-Gpt, and Pinecone. EduBot is designed as an interactive educational assistant, responding to student queries based on faculty-provided guidelines embedded in PDF documents. Through natural language processing, EduBot streamlines information retrieval, providing accurate, context-aware responses that foster a self- directed learning experience. By aligning with specific academic requirements and enhancing clarity in information delivery, EduBot stands as a promising tool in personalized digital learning support. This paper explores the design, implementation, and impact of EduBot, offering insights into its potential as a scalable solution for academic institutions The demand for accessible and adaptive educational tools is increasing as students seek more personalized and efficient ways to enhance their learning experience. EduBot is a cutting- edge PDF-driven chatbot designed to act as a virtual educational assistant, helping students to navigate and understand course materials by answering queries directly based on faculty guidelines. Built upon Large Language Models (LLMs), specifically utilizing frameworks such as LangChain and OpenAI's GPT-3.5, EduBot provides a sophisticated solution for integrating curated academic content into interactive learning. With its backend support from Pinecone for optimized data indexing, EduBot offers accurate and context-specific responses, facilitating a deeper level of engagement and comprehension. The average relevancy score is 80%. This paper outlines the design and deployment of EduBot, emphasizing its architecture, adaptability, and contributions to the educational landscape, where such AI- driven tools are poised to become indispensable in fostering autonomous, personalized learning environments. © 2025 Elsevier B.V., All rights reserved.},
keywords = {Chatbots, Computer aided instruction, Contextual knowledge, Curricula, Digital Education, E-Learning, Education computing, Educational Technology, Engineering education, Indexing (of information), Information Retrieval, Intelligent systems, Knowledge retrieval, LangChain Framework, Language Model, Large language model, learning experience, Learning experiences, Learning systems, LLM, PDF - Driven Chatbot, Query processing, Students, Teaching, Traditional learning, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
In the evolving landscape of educational technology, intelligent systems are redefining traditional learning methods by enhancing accessibility, adaptability, and engagement in instructional processes. This paper presents EduBot, a PDF-Driven Chatbot developed using advanced Large Language Models (LLMs) and leveraging frameworks like LangChain, OpenAI's Chat-Gpt, and Pinecone. EduBot is designed as an interactive educational assistant, responding to student queries based on faculty-provided guidelines embedded in PDF documents. Through natural language processing, EduBot streamlines information retrieval, providing accurate, context-aware responses that foster a self- directed learning experience. By aligning with specific academic requirements and enhancing clarity in information delivery, EduBot stands as a promising tool in personalized digital learning support. This paper explores the design, implementation, and impact of EduBot, offering insights into its potential as a scalable solution for academic institutions The demand for accessible and adaptive educational tools is increasing as students seek more personalized and efficient ways to enhance their learning experience. EduBot is a cutting- edge PDF-driven chatbot designed to act as a virtual educational assistant, helping students to navigate and understand course materials by answering queries directly based on faculty guidelines. Built upon Large Language Models (LLMs), specifically utilizing frameworks such as LangChain and OpenAI's GPT-3.5, EduBot provides a sophisticated solution for integrating curated academic content into interactive learning. With its backend support from Pinecone for optimized data indexing, EduBot offers accurate and context-specific responses, facilitating a deeper level of engagement and comprehension. The average relevancy score is 80%. This paper outlines the design and deployment of EduBot, emphasizing its architecture, adaptability, and contributions to the educational landscape, where such AI- driven tools are poised to become indispensable in fostering autonomous, personalized learning environments. © 2025 Elsevier B.V., All rights reserved.
Zhao, P.; Wei, X.
The Role of 3D Virtual Humans in Communication and Assisting Students' Learning in Transparent Display Environments: Perspectives of Pre-Service Teachers Proceedings Article
In: Chui, K. T.; Jaikaeo, C.; Niramitranon, J.; Kaewmanee, W.; Ng, K. -K.; Ongkunaruk, P. (Ed.): pp. 319–323, Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 9798331595500 (ISBN).
Abstract | Links | BibTeX | Tags: 3D virtual human, Assistive technology, CDIO teaching model, Collaborative learning, Collaborative practices, Display environments, E-Learning, Educational Technology, Engineering education, feedback, Integration, Knowledge delivery, Knowledge transfer, Learning algorithms, Natural language processing systems, Preservice teachers, Psychology computing, Student learning, Students, Teaching, Teaching model, Transparent display environment, Transparent displays, Virtual Reality
@inproceedings{zhao_role_2025,
title = {The Role of 3D Virtual Humans in Communication and Assisting Students' Learning in Transparent Display Environments: Perspectives of Pre-Service Teachers},
author = {P. Zhao and X. Wei},
editor = {K. T. Chui and C. Jaikaeo and J. Niramitranon and W. Kaewmanee and K. -K. Ng and P. Ongkunaruk},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105015746241&doi=10.1109%2FISET65607.2025.00069&partnerID=40&md5=08c39b84fa6bd6ac13ddbed203d7b1d9},
doi = {10.1109/ISET65607.2025.00069},
isbn = {9798331595500 (ISBN)},
year = {2025},
date = {2025-01-01},
pages = {319–323},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {The integration of transparent display and 3D virtual human technologies into education is expanding rapidly; however, their systematic incorporation into the CDIO teaching model remains underexplored, particularly in supporting complex knowledge delivery and collaborative practice. This study developed an intelligent virtual teacher assistance system based on generative AI and conducted a teaching experiment combining transparent display and 3D virtual human technologies. Feedback was collected through focus group interviews with 24 pre-service teachers. Results show that the virtual human, through natural language and multimodal interaction, significantly enhanced classroom engagement and contextual understanding, while its real-time feedback and personalized guidance effectively supported CDIO-based collaborative learning. Nonetheless, challenges remain in contextual adaptability and emotional feedback accuracy. Accordingly, the study proposes a path for technical optimization through the integration of multimodal emotion recognition, adaptive instructional algorithms, and nonintrusive data collection, offering empirical and theoretical insights into educational technology integration within the CDIO framework and future intelligent learning tools. © 2025 Elsevier B.V., All rights reserved.},
keywords = {3D virtual human, Assistive technology, CDIO teaching model, Collaborative learning, Collaborative practices, Display environments, E-Learning, Educational Technology, Engineering education, feedback, Integration, Knowledge delivery, Knowledge transfer, Learning algorithms, Natural language processing systems, Preservice teachers, Psychology computing, Student learning, Students, Teaching, Teaching model, Transparent display environment, Transparent displays, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
The integration of transparent display and 3D virtual human technologies into education is expanding rapidly; however, their systematic incorporation into the CDIO teaching model remains underexplored, particularly in supporting complex knowledge delivery and collaborative practice. This study developed an intelligent virtual teacher assistance system based on generative AI and conducted a teaching experiment combining transparent display and 3D virtual human technologies. Feedback was collected through focus group interviews with 24 pre-service teachers. Results show that the virtual human, through natural language and multimodal interaction, significantly enhanced classroom engagement and contextual understanding, while its real-time feedback and personalized guidance effectively supported CDIO-based collaborative learning. Nonetheless, challenges remain in contextual adaptability and emotional feedback accuracy. Accordingly, the study proposes a path for technical optimization through the integration of multimodal emotion recognition, adaptive instructional algorithms, and nonintrusive data collection, offering empirical and theoretical insights into educational technology integration within the CDIO framework and future intelligent learning tools. © 2025 Elsevier B.V., All rights reserved.
Barbu, M.; Iordache, D. -D.; Petre, I.; Barbu, D. -C.; Bajenaru, L.
Framework Design for Reinforcing the Potential of XR Technologies in Transforming Inclusive Education Journal Article
In: Applied Sciences (Switzerland), vol. 15, no. 3, 2025, ISSN: 20763417 (ISSN), (Publisher: Multidisciplinary Digital Publishing Institute (MDPI)).
Abstract | Links | BibTeX | Tags: Adaptive Learning, Adversarial machine learning, Artificial intelligence technologies, Augmented Reality, Contrastive Learning, Educational Technology, Extended reality (XR), Federated learning, Framework designs, Generative adversarial networks, Immersive, immersive experience, Immersive learning, Inclusive education, Learning platform, Special education needs
@article{barbu_framework_2025,
title = {Framework Design for Reinforcing the Potential of XR Technologies in Transforming Inclusive Education},
author = {M. Barbu and D. -D. Iordache and I. Petre and D. -C. Barbu and L. Bajenaru},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85217742383&doi=10.3390%2Fapp15031484&partnerID=40&md5=9ff9c99c76855723172055c73049fb5a},
doi = {10.3390/app15031484},
issn = {20763417 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Applied Sciences (Switzerland)},
volume = {15},
number = {3},
abstract = {This study presents a novel approach to inclusive education by integrating augmented reality (XR) and generative artificial intelligence (AI) technologies into an immersive and adaptive learning platform designed for students with special educational needs. Building upon existing solutions, the approach uniquely combines XR and generative AI to facilitate personalized, accessible, and interactive learning experiences tailored to individual requirements. The framework incorporates an intuitive Unity XR-based interface alongside a generative AI module to enable near real-time customization of content and interactions. Additionally, the study examines related generative AI initiatives that promote inclusion through enhanced communication tools, educational support, and customizable assistive technologies. The motivation for this study arises from the pressing need to address the limitations of traditional educational methods, which often fail to meet the diverse needs of learners with special educational requirements. The integration of XR and generative AI offers transformative potential by creating adaptive, immersive, and inclusive learning environments. This approach ensures real-time adaptability to individual progress and accessibility, addressing critical barriers such as static content and lack of inclusivity in existing systems. The research outlines a pathway toward more inclusive and equitable education, significantly enhancing opportunities for learners with diverse needs and contributing to broader social integration and equity in education. © 2025 Elsevier B.V., All rights reserved.},
note = {Publisher: Multidisciplinary Digital Publishing Institute (MDPI)},
keywords = {Adaptive Learning, Adversarial machine learning, Artificial intelligence technologies, Augmented Reality, Contrastive Learning, Educational Technology, Extended reality (XR), Federated learning, Framework designs, Generative adversarial networks, Immersive, immersive experience, Immersive learning, Inclusive education, Learning platform, Special education needs},
pubstate = {published},
tppubtype = {article}
}
This study presents a novel approach to inclusive education by integrating augmented reality (XR) and generative artificial intelligence (AI) technologies into an immersive and adaptive learning platform designed for students with special educational needs. Building upon existing solutions, the approach uniquely combines XR and generative AI to facilitate personalized, accessible, and interactive learning experiences tailored to individual requirements. The framework incorporates an intuitive Unity XR-based interface alongside a generative AI module to enable near real-time customization of content and interactions. Additionally, the study examines related generative AI initiatives that promote inclusion through enhanced communication tools, educational support, and customizable assistive technologies. The motivation for this study arises from the pressing need to address the limitations of traditional educational methods, which often fail to meet the diverse needs of learners with special educational requirements. The integration of XR and generative AI offers transformative potential by creating adaptive, immersive, and inclusive learning environments. This approach ensures real-time adaptability to individual progress and accessibility, addressing critical barriers such as static content and lack of inclusivity in existing systems. The research outlines a pathway toward more inclusive and equitable education, significantly enhancing opportunities for learners with diverse needs and contributing to broader social integration and equity in education. © 2025 Elsevier B.V., All rights reserved.
Guo, P.; Zhang, Q.; Tian, C.; Xue, W.; Feng, X.
Digital Human Techniques for Education Reform Proceedings Article
In: ICETM - Proc. Int. Conf. Educ. Technol. Manag., pp. 173–178, Association for Computing Machinery, Inc, 2025, ISBN: 9798400717468 (ISBN).
Abstract | Links | BibTeX | Tags: Augmented Reality, Contrastive Learning, Digital elevation model, Digital human technique, Digital Human Techniques, Digital humans, Education Reform, Education reforms, Educational Technology, Express emotions, Federated learning, Human behaviors, Human form models, Human techniques, Immersive, Innovative technology, Modeling languages, Natural language processing systems, Teachers', Teaching, Virtual environments, Virtual humans
@inproceedings{guo_digital_2025,
title = {Digital Human Techniques for Education Reform},
author = {P. Guo and Q. Zhang and C. Tian and W. Xue and X. Feng},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105001671326&doi=10.1145%2F3711403.3711428&partnerID=40&md5=fe9030a088666939b363c6c8c2fc5f66},
doi = {10.1145/3711403.3711428},
isbn = {9798400717468 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {ICETM - Proc. Int. Conf. Educ. Technol. Manag.},
pages = {173–178},
publisher = {Association for Computing Machinery, Inc},
abstract = {The rapid evolution of artificial intelligence, big data, and generative AI models has ushered in significant transformations across various sectors, including education. Digital Human Technique, an innovative technology grounded in advanced computer science and artificial intelligence, is reshaping educational paradigms by enabling virtual humans to simulate human behavior, express emotions, and interact with users. This paper explores the application of Digital Human Technique in education reform, focusing on creating immersive, intelligent classroom experiences that foster meaningful interactions between teachers and students. We define Digital Human Technique and delve into its key technical components such as character modeling and rendering, natural language processing, computer vision, and augmented reality technologies. Our methodology involves analyzing the role of educational digital humans created through these technologies, assessing their impact on educational processes, and examining various application scenarios in educational reform. Results indicate that Digital Human Technique significantly enhances the learning experience by enabling personalized teaching, increasing engagement, and fostering emotional connections. Educational digital humans serve as virtual teachers, interactive learning aids, and facilitators of emotional interaction, effectively addressing the challenges of traditional educational methods. They also promote a deeper understanding of complex concepts through simulated environments and interactive digital content. © 2025 Elsevier B.V., All rights reserved.},
keywords = {Augmented Reality, Contrastive Learning, Digital elevation model, Digital human technique, Digital Human Techniques, Digital humans, Education Reform, Education reforms, Educational Technology, Express emotions, Federated learning, Human behaviors, Human form models, Human techniques, Immersive, Innovative technology, Modeling languages, Natural language processing systems, Teachers', Teaching, Virtual environments, Virtual humans},
pubstate = {published},
tppubtype = {inproceedings}
}
The rapid evolution of artificial intelligence, big data, and generative AI models has ushered in significant transformations across various sectors, including education. Digital Human Technique, an innovative technology grounded in advanced computer science and artificial intelligence, is reshaping educational paradigms by enabling virtual humans to simulate human behavior, express emotions, and interact with users. This paper explores the application of Digital Human Technique in education reform, focusing on creating immersive, intelligent classroom experiences that foster meaningful interactions between teachers and students. We define Digital Human Technique and delve into its key technical components such as character modeling and rendering, natural language processing, computer vision, and augmented reality technologies. Our methodology involves analyzing the role of educational digital humans created through these technologies, assessing their impact on educational processes, and examining various application scenarios in educational reform. Results indicate that Digital Human Technique significantly enhances the learning experience by enabling personalized teaching, increasing engagement, and fostering emotional connections. Educational digital humans serve as virtual teachers, interactive learning aids, and facilitators of emotional interaction, effectively addressing the challenges of traditional educational methods. They also promote a deeper understanding of complex concepts through simulated environments and interactive digital content. © 2025 Elsevier B.V., All rights reserved.
Song, Y.; Fu, J.; Chiu, T. K. F.; King, I.; Qu, H.
Exploring the Potential of AI-Generated Lesson Designs Underpinned by the TPACK Framework for Educators in Higher Education: A Comparative Study Journal Article
In: Global Chinese Conference on Computers in Education Main Conference Proceedings (English Paper), vol. 2025, pp. 95–98, 2025, ISSN: 30053218 (ISSN), (Publisher: Global Chinese Society for Computers in Education).
Abstract | Links | BibTeX | Tags: Educational Technology, Generative AI, Lesson design, TPACK framework
@article{song_exploring_2025,
title = {Exploring the Potential of AI-Generated Lesson Designs Underpinned by the TPACK Framework for Educators in Higher Education: A Comparative Study},
author = {Y. Song and J. Fu and T. K. F. Chiu and I. King and H. Qu},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105016693856&partnerID=40&md5=88331590398d8a4d639fa1f43136ae85},
issn = {30053218 (ISSN)},
year = {2025},
date = {2025-01-01},
journal = {Global Chinese Conference on Computers in Education Main Conference Proceedings (English Paper)},
volume = {2025},
pages = {95–98},
abstract = {This paper investigates the potential of integrating generative AI into lesson design underpinned by the Technological Pedagogical Content Knowledge (TPACK) framework for educators in higher education. The study introduces a novel workflow that uses multiple AI agents to generate tailored lesson designs in two learning environments: one in a traditional classroom and another in the metaverse learning environment. A comparative study was conducted in a university-level product design course using three lesson designs under three conditions: Lesson design (LD) 1 – Manually designed lesson design in a traditional classroom, LD 2 – AI-generated lesson design in a traditional classroom, and LD 3 – AI-generated lesson design in the metaverse environment. The TPACK framework with the same lesson objectives underpinned all the lesson designs. Through qualitative analysis, the paper compares the three lesson designs, examining the potential of AI-generated lesson designs in supporting teacher professional development. The findings indicate that AI-generated lesson designs have great potential to enhance lesson design underpinned by the TPACK framework for educators. © 2025 Elsevier B.V., All rights reserved.},
note = {Publisher: Global Chinese Society for Computers in Education},
keywords = {Educational Technology, Generative AI, Lesson design, TPACK framework},
pubstate = {published},
tppubtype = {article}
}
This paper investigates the potential of integrating generative AI into lesson design underpinned by the Technological Pedagogical Content Knowledge (TPACK) framework for educators in higher education. The study introduces a novel workflow that uses multiple AI agents to generate tailored lesson designs in two learning environments: one in a traditional classroom and another in the metaverse learning environment. A comparative study was conducted in a university-level product design course using three lesson designs under three conditions: Lesson design (LD) 1 – Manually designed lesson design in a traditional classroom, LD 2 – AI-generated lesson design in a traditional classroom, and LD 3 – AI-generated lesson design in the metaverse environment. The TPACK framework with the same lesson objectives underpinned all the lesson designs. Through qualitative analysis, the paper compares the three lesson designs, examining the potential of AI-generated lesson designs in supporting teacher professional development. The findings indicate that AI-generated lesson designs have great potential to enhance lesson design underpinned by the TPACK framework for educators. © 2025 Elsevier B.V., All rights reserved.
2024
Tan, B. S.; Ong, S. H.; Andrew, K. H. T.; Wong, T. L.; Bai, P. S.; Rao, A. P.
Usability Study of GenAI for English Learning in VR Journal Article
In: Pakistan Journal of Life and Social Sciences, vol. 22, no. 2, pp. 7367–7382, 2024, ISSN: 17274915 (ISSN); 22217630 (ISSN), (Publisher: Elite Scientific Publications).
Abstract | Links | BibTeX | Tags: Education, Educational Technology, English Language, generative artificial intelligence, Virtual Reality
@article{tan_usability_2024,
title = {Usability Study of GenAI for English Learning in VR},
author = {B. S. Tan and S. H. Ong and K. H. T. Andrew and T. L. Wong and P. S. Bai and A. P. Rao},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85207260177&doi=10.57239%2FPJLSS-2024-22.2.00556&partnerID=40&md5=27ead67912da5963edef20fd57ce6469},
doi = {10.57239/PJLSS-2024-22.2.00556},
issn = {17274915 (ISSN); 22217630 (ISSN)},
year = {2024},
date = {2024-01-01},
journal = {Pakistan Journal of Life and Social Sciences},
volume = {22},
number = {2},
pages = {7367–7382},
abstract = {Traditional English learning environments in university often hindered by outdated focus on reading and writing, limited textbook content, insufficient speaking practice opportunities, and pre-programmed artificial intelligence (AI) in English speaking practice. This study explores the potential of leveraging VR technologies and generative AI (GenAI) to overcome these barriers. EasyEnglish is a real-time conversation game with GenAI non-player character (NPC)s. This game utilizes voice input recognition, large language model (LLM) for language assessment and text-to-speech (TTS) for NPC lip-sync animation. The content validity was assessed by 3 experts to evaluate the conversation quality. A usability test was conducted using a purposive sampling method with 7 undergraduate non-native English speakers who have less than 1 year experience in using VR technology. This study employed System Usability Scale (SUS) and Content Validity Index (CVI) metrics for assessment. The CVI result showed satisfactory agreement in conversation quality but highlighted areas for improvement in learning objectives. The SUS result revealed satisfaction in consistency of user interface (UI) and learnability of EasyEnglish, while also highlighting the need for improvement in UI, setup, and visual cues. The significance of the study lies in the GenAI's ability to provide diverse response, avoid repetitive dialogue and speak using gestures to undergraduate students. GenAI effectively identify and assess irrelevant words in conversation, provide immediate grammar and vocabulary correction and suggestion of conversation improvement accurately. Future research should focus on improving accessibility, include more multimodal interactions, and mapping learning objectives with the soft skills emphasized by the World Economic Forum (WEF). © 2024 Elsevier B.V., All rights reserved.},
note = {Publisher: Elite Scientific Publications},
keywords = {Education, Educational Technology, English Language, generative artificial intelligence, Virtual Reality},
pubstate = {published},
tppubtype = {article}
}
Traditional English learning environments in university often hindered by outdated focus on reading and writing, limited textbook content, insufficient speaking practice opportunities, and pre-programmed artificial intelligence (AI) in English speaking practice. This study explores the potential of leveraging VR technologies and generative AI (GenAI) to overcome these barriers. EasyEnglish is a real-time conversation game with GenAI non-player character (NPC)s. This game utilizes voice input recognition, large language model (LLM) for language assessment and text-to-speech (TTS) for NPC lip-sync animation. The content validity was assessed by 3 experts to evaluate the conversation quality. A usability test was conducted using a purposive sampling method with 7 undergraduate non-native English speakers who have less than 1 year experience in using VR technology. This study employed System Usability Scale (SUS) and Content Validity Index (CVI) metrics for assessment. The CVI result showed satisfactory agreement in conversation quality but highlighted areas for improvement in learning objectives. The SUS result revealed satisfaction in consistency of user interface (UI) and learnability of EasyEnglish, while also highlighting the need for improvement in UI, setup, and visual cues. The significance of the study lies in the GenAI's ability to provide diverse response, avoid repetitive dialogue and speak using gestures to undergraduate students. GenAI effectively identify and assess irrelevant words in conversation, provide immediate grammar and vocabulary correction and suggestion of conversation improvement accurately. Future research should focus on improving accessibility, include more multimodal interactions, and mapping learning objectives with the soft skills emphasized by the World Economic Forum (WEF). © 2024 Elsevier B.V., All rights reserved.