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Mark Feng Teng – European Journal of Education, 2025
The present study explored EFL students' perceptions and experiences in utilising ChatGPT to seek feedback for writing. The present study also examined how levels of metacognitive awareness (MA) influenced these perceptions and experiences. Utilising a mixed-method research design, the study collected data from a total of 40 EFL undergraduates…
Descriptors: English (Second Language), Student Attitudes, Feedback (Response), Writing (Composition)
Lanqin Zheng; Yunchao Fan; Bodong Chen; Zichen Huang; LeiGao; Miaolang Long – Education and Information Technologies, 2024
Online collaborative learning has been broadly applied in higher education. However, learners face many challenges in collaborating with one another and coregulating their learning, leading to low group performance. To address the gaps, this study proposed an artificial intelligence (AI)-enabled feedback and feedforward approach that not only…
Descriptors: Artificial Intelligence, Feedback (Response), Electronic Learning, Cooperative Learning
Jinglei Yu; Shengquan Yu; Ling Chen – British Journal of Educational Technology, 2025
Video-based teacher online learning enables teachers to engage in reflective practice by watching others' classroom videos, providing peer feedback (PF) and reviewing others' work. However, the quality and reliability of PF often suffer due to variations in teaching proficiency among providers, which limits its usefulness for reviewers. To improve…
Descriptors: Artificial Intelligence, Peer Evaluation, Feedback (Response), Reflection
Rhonda Bondie; Elizabeth City – Learning Professional, 2024
New questions and concerns arise every day about the impact of AI in schools, such as how teachers will learn about AI and leverage it in their classrooms, how they can use it to develop their own teaching expertise, and if AI for educators really leads to better teaching and learning. The authors believe that AI can help teachers become more…
Descriptors: Preservice Teacher Education, Artificial Intelligence, Computer Simulation, Microteaching
Flora Ji-Yoon Jin; Bhagya Maheshi; Wenhua Lai; Yuheng Li; Danijela Gasevic; Guanliang Chen; Nicola Charwat; Philip Wing Keung Chan; Roberto Martinez-Maldonado; Dragan Gaševic; Yi-Shan Tsai – Journal of Learning Analytics, 2025
This paper explores the integration of generative AI (GenAI) in the feedback process in higher education through a learning analytics (LA) tool, examined from a feedback literacy perspective. Feedback literacy refers to students' ability to understand, evaluate, and apply feedback effectively to improve their learning, which is crucial for…
Descriptors: College Students, Student Attitudes, Artificial Intelligence, Learning Analytics
Dominic Lohr; Hieke Keuning; Natalie Kiesler – Journal of Computer Assisted Learning, 2025
Background: Feedback as one of the most influential factors for learning has been subject to a great body of research. It plays a key role in the development of educational technology systems and is traditionally rooted in deterministic feedback defined by experts and their experience. However, with the rise of generative AI and especially large…
Descriptors: College Students, Programming, Artificial Intelligence, Feedback (Response)
Jussi S. Jauhiainen; Agustin Bernardo Garagorry Guerra – Journal of Information Technology Education: Innovations in Practice, 2025
Aim/Purpose: This article investigates the process of identifying and correcting hallucinations in ChatGPT-4's recall of student-written responses as well as its evaluation of these responses, and provision of feedback. Effective prompting is examined to enhance the pre-evaluation, evaluation, and post-evaluation stages. Background: Advanced Large…
Descriptors: Artificial Intelligence, Student Evaluation, Writing Evaluation, Feedback (Response)
Xian Li; Guangxin Han; Bei Fang; Juhou He – Asia-Pacific Education Researcher, 2025
The development of artificial intelligence (AI) significantly improves the effectiveness of classroom dialogue systems, but their integration into the learning environment remains challenging. To address this gap, this research presents a framework for automatic intelligent dialogue analysis, intending to promote high-quality classroom dialogue…
Descriptors: Artificial Intelligence, Classroom Communication, Discourse Analysis, Dialogs (Language)
Sophia Soomin Lee; Robert L. Moore – Online Learning, 2024
In this systematic review, we synthesize ten empirical peer-reviewed articles published between 2019 and 2023 that used generative artificial intelligence (GenAI) for automated feedback in higher education. There are significant opportunities and challenges to integrate these tools effectively into learning environments as the demand for timely…
Descriptors: Artificial Intelligence, Higher Education, Feedback (Response), Grading
Khameel B. Mustapha; Eng Hwa Yap; Yousif Abdalla Abakr – Interactive Technology and Smart Education, 2024
Purpose: Following the recent rise in generative artificial intelligence (GenAI) tools, fundamental questions about their wider impacts have started to reverberate around various disciplines. This study aims to track the unfolding landscape of general issues surrounding GenAI tools and to elucidate the specific opportunities and limitations of…
Descriptors: Engineering Education, Artificial Intelligence, Computer Software, Synchronous Communication
Dake, Delali Kwasi; Gyimah, Esther – Education and Information Technologies, 2023
Text analytics in education has evolved to form a critical component of the future SMART campus architecture. Sentiment analysis and qualitative feedback from students is now a crucial application domain of text analytics relevant to institutions. The implementation of sentiment analysis helps understand learners' appreciation of lessons, which…
Descriptors: Feedback (Response), College Students, Psychological Patterns, Algorithms
Elisabeth Bauer; Michael Sailer; Frank Niklas; Samuel Greiff; Sven Sarbu-Rothsching; Jan M. Zottmann; Jan Kiesewetter; Matthias Stadler; Martin R. Fischer; Tina Seidel; Detlef Urhahne; Maximilian Sailer; Frank Fischer – Journal of Computer Assisted Learning, 2025
Background: Artificial intelligence, particularly natural language processing (NLP), enables automating the formative assessment of written task solutions to provide adaptive feedback automatically. A laboratory study found that, compared with static feedback (an expert solution), adaptive feedback automated through artificial neural networks…
Descriptors: Artificial Intelligence, Feedback (Response), Computer Simulation, Natural Language Processing
Ankit Dhamija; Deepika Dhamija – Journal of Interdisciplinary Studies in Education, 2025
The rapid integration of AI in education has transformed instructional methodologies and administrative tasks. However, higher education teachers face challenges in creating quality assignments amidst increasing administrative burdens. This study investigates the potential of AI, specifically ChatGPT, in streamlining assignment creation. By…
Descriptors: College Faculty, Teacher Attitudes, Computer Attitudes, Artificial Intelligence
Abbas Bodaubekov; Shakhrizat Agaidarova; Talgat Zhussipbek; Davronzhon Gaipov; Nuri Balta – Contemporary Educational Technology, 2025
This study investigates the effectiveness of feedback provided by teachers versus feedback generated by the Write & Improve platform in enhancing the writing skills of senior undergraduate students enrolled in a "two foreign language" program at a private university in Kazakhstan. The quasi-experimental design involved four teachers,…
Descriptors: Artificial Intelligence, Feedback (Response), Writing Skills, Undergraduate Students
Abrar H. Alsofyani; Amal M. Barzanji – Journal of Educational Computing Research, 2025
Corrective feedback plays a critical role in enhancing writing skills among English as a Foreign Language (EFL) learners, but large class sizes often hinder the provision of personalized feedback. Generative AI tools such as ChatGPT have emerged as promising solutions that offer immediate and individualized feedback for writing. This study…
Descriptors: Feedback (Response), Artificial Intelligence, English (Second Language), Second Language Learning