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Yun-Fang Tu – Educational Technology & Society, 2024
With the rapid development of generative artificial intelligence (GAI), the performance and usability of related tools, such as ChatGPT, have significantly improved. The advancement has fostered researchers to increasingly focus on students' perceptions and application of the roles, functionalities, and interaction patterns of these tools in…
Descriptors: Artificial Intelligence, Interaction, Undergraduate Students, Student Attitudes
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Chia-Ju Lin; Wei-Sheng Wang; Hsin-Yu Lee; Yueh-Min Huang; Ting-Ting Wu – Journal of Educational Computing Research, 2025
This study uses a quasi-experimental design to explore the role of natural language processing (NLP) and speech recognition technologies in supporting teacher interventions during collaborative STEM activities. The Speech Recognition Keywords Analysis System (SRKAS) was developed to extract keywords from student discussions, enabling real-time…
Descriptors: Natural Language Processing, Computational Linguistics, Technology Uses in Education, STEM Education
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Wei Li; Jia-Wei Ji; Judy C. R. Tseng; Cheng-Ye Liu; Ji-Yi Huang; Hai-Ying Liu; Mo Zhou – Educational Technology & Society, 2025
Education is an important way to achieve global Sustainable Development Goals (SDGs), while classroom engagement and collective efficacy are key factors that influence SDG learning outcomes. However, students' in-depth thinking could be limited when they apply to search engines such as Google to support their learning of SDG-related topics. Large…
Descriptors: Learner Engagement, Self Efficacy, Critical Thinking, Artificial Intelligence
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Hui-Chun Chu; Yi-Chun Lu; Yun-Fang Tu – Educational Technology & Society, 2025
This study guided 97 undergraduates using generative artificial intelligence (GenAI) to conduct multimodal digital storytelling (M-DST) learning activities. Furthermore, the study examined the differences in M-DST ability and critical thinking awareness among undergraduates with different levels of learning motivation and their perceptions of this…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Undergraduate Students
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Ting-Ting Wu; Hsin-Yu Lee; Pei-Hua Chen; Chia-Ju Lin; Yueh-Min Huang – Journal of Computer Assisted Learning, 2025
Background: Science, Technology, Engineering, and Mathematics (STEM) education in Asian universities struggles to integrate Knowledge, Skills, and Attitudes (KSA) due to large classes and student reluctance. While ChatGPT offers solutions, its conventional use may hinder independent critical thinking. Objectives: This study introduces PA-GPT,…
Descriptors: Peer Evaluation, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
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Xiaojing Weng; Qi Xia; Mingyue Gu; Kumaran Rajaram; Thomas K. F. Chiu – Australasian Journal of Educational Technology, 2024
Generative artificial intelligence (GenAI) impacts higher education assessment and learning outcomes, which are closely related and intertwined. Literature suggests that educators and researchers have many varied concerns regarding student assessment in the higher education GenAI context, such as how to assess students' learning and the new…
Descriptors: Evaluation Methods, Outcomes of Education, Artificial Intelligence, Natural Language Processing
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Tzu-Yu Tai; Howard Hao-Jan Chen – Computer Assisted Language Learning, 2024
English speaking is considered the most difficult and anxiety-provoking language skill for EFL learners due to lack of access to authentic language use, fear of making mistakes, and peers' negative comments. With automatic speech recognition and natural language processing, intelligent personal assistants (IPAs) have potential in foreign language…
Descriptors: English (Second Language), Speech Communication, English Language Learners, Anxiety
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Anna Y. Q. Huang; Jei Wei Chang; Albert C. M. Yang; Hiroaki Ogata; Shun Ting Li; Ruo Xuan Yen; Stephen J. H. Yang – Educational Technology & Society, 2023
To improve students' learning performance through review learning activities, we developed a personalized intervention tutoring approach that leverages learning analysis based on artificial intelligence. The proposed intervention first uses text-processing artificial intelligence technologies, namely bidirectional encoder representations from…
Descriptors: Academic Achievement, Tutoring, Artificial Intelligence, Individualized Instruction
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Hsiao-Ling Hsu; Howard Hao-Jan Chen; Andrew G. Todd – Interactive Learning Environments, 2023
With advances in technology, intelligent personal assistants (IPAs) have become available to assist users with a variety of tasks using voice commands. Because IPAs may induce dialogic interactions, researchers speculated that they may benefit second language learning, especially regarding pronunciation, listening and speaking skills. So far, very…
Descriptors: Foreign Countries, College Students, English (Second Language), Artificial Intelligence