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Suping Yi; Wayan Sintawati; Yibing Zhang – Journal of Computer Assisted Learning, 2025
Background: Natural language processing (NLP) and machine learning technologies offer significant advantages, such as facilitating the delivery of reflective feedback in collaborative learning environments while minimising technical constraints for educators related to time and location. Recently, scholars' interest in reflective feedback has…
Descriptors: Reflection, Feedback (Response), Cooperative Learning, Natural Language Processing
Helen Crompton; Diane Burke – TechTrends: Linking Research and Practice to Improve Learning, 2024
ChatGPT was released to the public in November 30, 2022. This study examines how ChatGPT can be used by educators and students to promote learning and what are the challenges and limitations. This study is unique in providing one of the first systematic reviews using peer review studies to provide an early examination of the field. Using PRISMA…
Descriptors: Artificial Intelligence, Barriers, Technology Uses in Education, Natural Language Processing
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
Yang, Tzu-Chi – Educational Technology & Society, 2023
The development of digital competence has become an important part of higher education, and digital competence assessments have attracted considerable attention and concerns. Previous studies in this area mainly focused on self-reporting and manual review methods such as questionnaires, which offer limited assessment value. To solve this issue,…
Descriptors: Artificial Intelligence, Digital Literacy, Natural Language Processing, Higher Education
Olivia Metzner; Yindong Wang; Wendy Symes; Yizhen Huang; Lena Keller; Gerard de Melo; Rebecca Lazarides – British Journal of Educational Psychology, 2025
Background: Recent studies have examined the relation between teacher motivation, motivational messages and student learning but are limited to an achievement-related context, primarily using survey data. Moreover, our understanding of the relation between various teacher characteristics, such as teacher self-efficacy (TSE), and their motivational…
Descriptors: Teacher Motivation, Motivation Techniques, Academic Achievement, Teacher Characteristics
Yi Lyu; Azhar Bin Md Adnan; Lijuan Zhang – Education and Information Technologies, 2025
This study presents a comprehensive examination of the applications, challenges, and strategies associated with the integration of natural language processing (NLP) technologies in university teaching. By employing qualitative analyses, including interviews, classroom observations, and document review, the study explores the diverse applications…
Descriptors: Foreign Countries, Natural Language Processing, Technology Integration, Teaching Methods
Sebastian Hobert; Florian Berens – Educational Technology Research and Development, 2024
Individualized learning support is an essential part of formal educational learning processes. However, in typical large-scale educational settings, resource constraints result in limited interaction among students, teaching assistants, and lecturers. Due to this, learning success in those settings may suffer. Inspired by current technological…
Descriptors: Individualized Instruction, Intelligent Tutoring Systems, Learning Processes, Teaching Methods
Clinton Chidiebere Anyanwu; Pauline Ndidi Ononiwu; Grace Ngozi Isiozor – Education and Information Technologies, 2024
In contemporary society, information and communication technology permeates every aspect of human life, including education. This study investigates the impact of WhatsApp chatbot technology and Glaser's teaching approaches on the academic performance of economics education students in tertiary institutions. Grounded in activity theory, the study…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Teaching Methods
Alexandra S. Dylman; Marie-France Champoux-Larsson; Candice Frances – Educational Psychology, 2025
We report four experiments investigating the effect of prosody on listening comprehension in 11-13-year-old children. Across all experiments, participants listened to short object descriptions and answered content-based questions about said objects. In Experiments 1-3, the descriptions were read in an emotionally positive or neutral tone of voice.…
Descriptors: Intonation, Middle School Students, Foreign Countries, Listening Comprehension
Jionghao Lin; Wei Tan; Lan Du; Wray Buntine; David Lang; Dragan Gasevic; Guanliang Chen – IEEE Transactions on Learning Technologies, 2024
Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…
Descriptors: Classification, Dialogs (Language), Teaching Methods, Computer Assisted Instruction
Gyeonggeon Lee; Xiaoming Zhai – TechTrends: Linking Research and Practice to Improve Learning, 2025
Educators and researchers have analyzed various image data acquired from teaching and learning, such as images of learning materials, classroom dynamics, students' drawings, etc. However, this approach is labour-intensive and time-consuming, limiting its scalability and efficiency. The recent development in the Visual Question Answering (VQA)…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Learning Processes
Basel Hammoda – International Journal of Technology in Education, 2024
ChatGPT is taking the world and the education sector by storm. Many educators are still hesitant to integrate it within their curricula, owing to the limited practical and theoretical guidance on its applications, despite early conceptual studies advocating for its potential benefits. This pedagogical innovation applied an effectual logic to…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Integration, Educational Innovation
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
Julia Jochim; Vera Kristina Lenz-Kesekamp – Information and Learning Sciences, 2025
Purpose: Large language models such as ChatGPT are a challenge to academic principles, calling into question well-established practices, teaching and exam formats. This study aims to explore the adaptation process regarding text-generative artificial intelligence (AI) of students and teachers in higher education and to identify needs for change.…
Descriptors: Artificial Intelligence, Student Needs, Higher Education, Technology Uses in Education
Maria Magdalena Stan; Cristina Dumitru; Florentina Bucuroiu – Education and Information Technologies, 2025
Understanding teachers' perspectives is essential for successful technology adoption as technology plays an increasingly important role in education. The aim of this study is to explore the nuanced dynamics of using natural language processing models such as ChatGPT in higher education settings. Understanding the complexity of teachers' attitudes…
Descriptors: Artificial Intelligence, Computer Software, Teaching Methods, Technology Integration

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