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Direct linkRobson Gonçalves Fechine Feitosa; Gustavo Augusto Lima de Campos; Ismayle de Sousa Santos; Carlos Hairon Ribeiro Gonçalves; Antônio de Barros Serra; Alisson Romão de Oliveira; Pedro Lucas Pereira Feitosa; Yuri David Santos; Esdras Lins Bispo Jr.; Guilherme Álvaro Rodrigues Maia Esmeraldo – International Journal of Artificial Intelligence in Education, 2025
Many existing solutions for the automatic assessment of open-ended questions predominantly rely on machine learning models, primarily focusing on aspects such as writing style and assigning a final score. However, these solutions often overlook the crucial factor of feedback content relevance, specifically, how well the response aligns with the…
Descriptors: Competency Based Education, Skill Development, Artificial Intelligence, Feedback (Response)
Long Zhang; Khe Foon Hew – Education and Information Technologies, 2025
Although self-regulated learning (SRL) plays an important role in supporting online learning performance, the lack of student self-regulation skills poses a persistent problem to many educators. Recommender systems have the potential to promote SRL by delivering personalized feedback and tailoring learning strategies to meet individual learners'…
Descriptors: Independent Study, Electronic Learning, Online Courses, Artificial Intelligence
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)
Hui Liu; Wei Guo – European Journal of Education, 2025
In contemporary music education, innovative technologies, particularly artificial intelligence (AI)-based tools, play a crucial role. The objective of this study was to assess the effectiveness of AI-based tools in enhancing students' success and creativity. The study involved 158 students from a leading music institution, who were divided into…
Descriptors: Instructional Effectiveness, Artificial Intelligence, Performance, Creativity
Felicity F. Frinsel; Fabio Trecca; Morten H. Christiansen – Cognitive Science, 2024
In language learning, learners engage with their environment, incorporating cues from different sources. However, in lab-based experiments, using artificial languages, many of the cues and features that are part of real-world language learning are stripped away. In three experiments, we investigated the role of positive, negative, and mixed…
Descriptors: Feedback (Response), Language Acquisition, Mathematical Linguistics, Role Theory
Elvis Ortega-Ochoa; Marta Arguedas; Thanasis Daradoumis – British Journal of Educational Technology, 2024
Artificial intelligence (AI) and natural language processing technologies have fuelled the growth of Pedagogical Conversational Agents (PCAs) with empathic conversational capabilities. However, no systematic literature review has explored the intersection between conversational agents, education and emotion. Therefore, this study aimed to outline…
Descriptors: Empathy, Artificial Intelligence, Databases, Dialogs (Language)
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
Rico-Juan, Juan Ramon; Sanchez-Cartagena, Victor M.; Valero-Mas, Jose J.; Gallego, Antonio Javier – IEEE Transactions on Learning Technologies, 2023
Online Judge (OJ) systems are typically considered within programming-related courses as they yield fast and objective assessments of the code developed by the students. Such an evaluation generally provides a single decision based on a rubric, most commonly whether the submission successfully accomplished the assignment. Nevertheless, since in an…
Descriptors: Artificial Intelligence, Models, Student Behavior, Feedback (Response)
Emmanuel Fokides; Eirini Peristeraki – Education and Information Technologies, 2025
This research analyzed the efficacy of ChatGPT as a tool for the correction and provision of feedback on primary school students' short essays written in both the English and Greek languages. The accuracy and qualitative aspects of ChatGPT-generated corrections and feedback were compared to that of educators. For the essays written in English, it…
Descriptors: Artificial Intelligence, Error Correction, Feedback (Response), Elementary School Students
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
Anderson Pinheiro Cavalcanti; Rafael Ferreira Mello; Dragan Gaševic; Fred Freitas – International Journal of Artificial Intelligence in Education, 2024
Educational feedback is a crucial factor in the student's learning journey, as through it, students are able to identify their areas of deficiencies and improve self-regulation. However, the literature shows that this is an area of great dissatisfaction, especially in higher education. Providing effective feedback becomes an increasingly…
Descriptors: Prediction, Feedback (Response), Artificial Intelligence, Automation
Da-Wei Zhang; Melissa Boey; Yan Yu Tan; Alexis Hoh Sheng Jia – npj Science of Learning, 2024
This study evaluates the ability of large language models (LLMs) to deliver criterion-based grading and examines the impact of prompt engineering with detailed criteria on grading. Using well-established human benchmarks and quantitative analyses, we found that even free LLMs achieve criterion-based grading with a detailed understanding of the…
Descriptors: Artificial Intelligence, Natural Language Processing, Criterion Referenced Tests, Grading
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
Buckingham Shum, Simon; Lim, Lisa-Angelique; Boud, David; Bearman, Margaret; Dawson, Phillip – International Journal of Educational Technology in Higher Education, 2023
Effective learning depends on effective feedback, which in turn requires a set of skills, dispositions and practices on the part of both students and teachers which have been termed "feedback literacy." A previously published teacher "feedback literacy competency framework" has identified what is needed by teachers to implement…
Descriptors: Automation, Feedback (Response), Learning Analytics, Artificial Intelligence
Keith J. Topping; Ed Gehringer; Hassan Khosravi; Srilekha Gudipati; Kaushik Jadhav; Surya Susarla – International Journal of Educational Technology in Higher Education, 2025
This paper surveys research and practice on enhancing peer assessment with artificial intelligence. Its objectives are to give the structure of the theoretical framework underpinning the study, synopsize a scoping review of the literature that illustrates this structure, and provide a case study which further illustrates this structure. The…
Descriptors: Peer Evaluation, Artificial Intelligence, Grades (Scholastic), Feedback (Response)
