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Peer reviewed
Direct linkYin Zhang; Menglong Zhang; Liming Wu; Jin Li – Science & Education, 2025
Rapid advancements in the information age have prompted significant digitalization in global higher education, with Chinese higher education particularly adapting to the influence of artificial intelligence. This study focuses on the digital transformation in China's higher education, specifically within AI-assisted engineering education. It…
Descriptors: Foreign Countries, Higher Education, Artificial Intelligence, Computer Assisted Instruction
Thinley Wangdi; Karma Sonam Rigdel – Journal of Education for Teaching: International Research and Pedagogy, 2025
This qualitative study explored the factors that influence teachers' behavioural intention (BI) to use ChatGPT for teaching. The data was collected from 214 Bhutanese teachers using open-ended questions and interviews. The thematic analysis revealed four key factors that are likely to influence teachers' BI to use ChatGPT in the context. These…
Descriptors: Teacher Attitudes, Intention, Artificial Intelligence, Computer Software
Justin Edwards; Andy Nguyen; Joni Lämsä; Marta Sobocinski; Ridwan Whitehead; Belle Dang; Anni-Sofia Roberts; Sanna Järvelä – British Journal of Educational Technology, 2025
Socially shared regulation of learning (SSRL) is a crucial process for groups of learners to successfully collaborate. Detecting and supporting SSRL is a challenge, especially in real time, but hybrid intelligence approaches such as Artificial Intelligence (AI) agents may make this possible. Leveraging the concept of trigger events which invite…
Descriptors: Artificial Intelligence, Computer Software, Technology Uses in Education, Metacognition
Yael Feldman-Maggor; Ron Blonder; Giora Alexandron – Journal of Science Education and Technology, 2025
Artificial intelligence (AI) has made remarkable strides in recent years, finding applications in various fields, including chemistry research and industry. Its integration into chemistry education has gained attention more recently, particularly with the advent of generative AI (GAI) tools. However, there is a need to understand how teachers'…
Descriptors: Chemistry, Science Instruction, Technological Literacy, Pedagogical Content Knowledge
Youngjin Lee – Education and Information Technologies, 2025
This study investigates the development and evaluation of a Retrieval-Augmented Generation (RAG)-based statistics tutor designed to assist students with quantitative analysis methods. The RAG approach was employed to address the well-documented issue of hallucination in Large Language Models (LLMs). A computer tutor was developed that utilizes…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Teachers, Students
Download full textDavid M. Woods; Andrea Hulshult – Information Systems Education Journal, 2025
IT/IS educators continue to work to develop content and activities for teaching Agile practices, processes, and methodologies to their courses to ensure students have the skills expected by businesses. Given the wide range of tools and technologies that fall under the umbrella of Agile and the wide range of places where Agile is applied, educators…
Descriptors: Information Technology, Information Science Education, Computer Science Education, Teaching Methods
Michael D'Addario – Discover Education, 2025
With the proliferation of easy-to-use generative AI tools such as ChatGPT, students in college composition courses can and do take advantage of such technology to assist with essay writing. While a growing body of research does not see using these tools as a problem in itself, institutional, departmental, and instructor policies about generative…
Descriptors: Taxonomy, Language Usage, Artificial Intelligence, Computer Software
Ching-Huei Chen; Victor Law – Educational Technology Research and Development, 2025
This study explores the roles of students' help-seeking profiles when seeking help from AI chatbots, specifically ChatGPT, in a digital game-based learning environment, "Summon of Magicrystal." The study involved 102 middle school students who played an online game with the provision of ChatGPT and sought help from ChatGPT while solving…
Descriptors: Help Seeking, Game Based Learning, Artificial Intelligence, Computer Software
Yiwen Jin; Lies Sercu – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence has been reshaping many industries, and education is no exception. When ChatGPT burst onto the scene in late 2022, it ignited conversations among educators and researchers alike. Despite growing interest and experimentation with this technology in university classrooms, the field has been missing a comprehensive…
Descriptors: Artificial Intelligence, Computer Software, Technology Integration, Higher Education
Jessica R. Gladstone; Noah L. Schroeder; Steffi Heidig; Shan Zhang; Chris Palaguachi; Marcin Pitera – Educational Psychology Review, 2025
The use of pedagogical agents (PAs) as learning tools within digital learning environments is rising. Previous research shows that PAs can aid learning across various domains and age groups, but their impact on learner motivation is unclear. As PAs become more integrated into learning systems, building an in-depth and theory-driven understanding…
Descriptors: Teaching Methods, Student Motivation, Learning Motivation, Technology Integration
Haley A. Delcher; Enas S. Alsatari; Adeyeye I. Haastrup; Sayema Naaz; Lydia A. Hayes-Guastella; Autumn M. McDaniel; Olivia G. Clark; Devin M. Katerski; Francois O. Prinsloo; Olivia R. Roberts; Meredith A. Shaddix; Bridgette N. Sullivan; Isabella M. Swan; Emily M. Hartsell; Jeffrey D. DeMeis; Sunita S. Paudel; Glen M. Borchert – Biochemistry and Molecular Biology Education, 2025
Today, due to the size of many genomes and the increasingly large sizes of sequencing files, independently analyzing sequencing data is largely impossible for a biologist with little to no programming expertise. As such, biologists are typically faced with the dilemma of either having to spend a significant amount of time and effort to learn how…
Descriptors: Artificial Intelligence, Technology Uses in Education, Training, Teaching Methods
Rubén González Vallejo, Editor – IGI Global, 2025
Artificial intelligence (AI) has been introduced into tools and technologies, such as chatbots, for language teaching, allowing educators to better meet the needs of individual students. Chatbots may act as virtual tutors in online learning environments, giving students the ability to access leaning support as needed. Chatbots can improve…
Descriptors: Artificial Intelligence, Computer Mediated Communication, Intelligent Tutoring Systems, Second Language Instruction
Yakun Zhang; Ziwei Pan; Lina Huang; Xingli Zhang; Lung An Chen; Jiannong Shi – Educational Psychology, 2025
The present study is a short-term intervention program aimed at cultivating children's creativity based on the 'butterfly model' of nurturing creativity, adopting a 2 × 3 mixed experimental design with placebo and no-treatment groups. They also received the equal intervention after the experimental group finished for the sake of fairness to all…
Descriptors: Teaching Methods, Childrens Attitudes, Creative Thinking, Creative Development
Mohsin Murtaza; Chi-Tsun Cheng; Mohammad Fard; John Zeleznikow – International Journal of Artificial Intelligence in Education, 2025
As modern vehicles continue to integrate increasingly sophisticated Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles (AV) functions, conventional user manuals may no longer be the most effective medium for conveying knowledge to drivers. This research analysed conventional, paper and video-based instructional methods versus a…
Descriptors: Educational Change, Driver Education, Motor Vehicles, Natural Language Processing
Shireen Jamal Mohammed; Maryam Waleed Khalid – Language Testing in Asia, 2025
While over the last couple of years, there has been a growing investigation into the use of Artificial Intelligence (AI) within language learning, very little has been written regarding how such AI feedback influences the complex experiences of EFL learners in terms of motivation, foreign language peace of mind (FLPoM), trait emotional…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Software, English (Second Language)
