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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
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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
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Da-Lun Chen; Kirsi Aaltonen; Hannele Lampela; Jaakko Kujala – Technology, Knowledge and Learning, 2025
The breakthrough in generative artificial intelligence (AI) has unlocked new possibilities for higher education. There are many studies on educational chatbots in the fields of science, technology, engineering, and mathematics; however, studies on designing and leveraging chatbots in a multidisciplinary field like project management have been…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Higher Education
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Toni Taipalus; Hilkka Grahn; Saima Ritonummi; Valtteri Siitonen; Tero Vartiainen; Denis Zhidkikh – ACM Transactions on Computing Education, 2025
SQL compiler error messages are the primary way users receive feedback when they encounter syntax errors or other issues in their SQL queries. Effective error messages can enhance the user experience by providing clear, informative, and actionable feedback. Despite the age of SQL compilers, it still remains largely unclear what contributes to an…
Descriptors: Computer Science Education, Novices, Information Systems, Programming Languages
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Ibnatul Jalilah Yusof – Journal of Information Technology Education: Research, 2025
Aim/Purpose: This paper examines the potential of ChatGPT-assisted retrieval practice to enhance students' final exam performance. ChatGPT was utilized to generate questions and deliver timely feedback during retrieval practice, supporting learning in large class settings where providing personalized feedback is often challenging. Background:…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Scores
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Hao Zhou; Wenge Rong; Jianfei Zhang; Qing Sun; Yuanxin Ouyang; Zhang Xiong – IEEE Transactions on Learning Technologies, 2025
Knowledge tracing (KT) aims to predict students' future performances based on their former exercises and additional information in educational settings. KT has received significant attention since it facilitates personalized experiences in educational situations. Simultaneously, the autoregressive (AR) modeling on the sequence of former exercises…
Descriptors: Learning Experience, Academic Achievement, Data, Artificial Intelligence
Christopher Mah; Mei Tan; Lena Phalen; Alexa Sparks; Dorottya Demszky – Annenberg Institute for School Reform at Brown University, 2025
Effective writing feedback is a powerful tool for enhancing student learning, encouraging revision, and increasing motivation and agency. Yet, teachers face many challenges that prevent them from consistently providing effective writing feedback. Recent advances in generative artificial intelligence (AI) have led educators and researchers to…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Writing Evaluation
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Xinming Chen; Ziqian Zhou; Malila Prado – International Journal of Assessment Tools in Education, 2025
This study explores the efficacy of ChatGPT-3.5, an AI chatbot, used as an Automatic Essay Scoring (AES) system and feedback provider for IELTS essay preparation. It investigates the alignment between scores given by ChatGPT-3.5 and those assigned by official IELTS examiners to establish its reliability as an AES. It also identifies the strategies…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Automation
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Saida Ulfa; Ence Surahman; Agus Wedi; Izzul Fatawi; Rex Bringula – Knowledge Management & E-Learning, 2025
Online assessment is one of the important factors in online learning today. An online summary assessment is an example of an open-ended question, offering the advantage of probing students' understanding of the learning materials. However, grading students' summary writings is challenging due to the time-consuming process of evaluating students'…
Descriptors: Knowledge Management, Automation, Documentation, Feedback (Response)
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Mary Rice; Nicholas DePascal; Joaquín T. Argüello de Jesús; Helen McFeely; Amy Traylor; Lehman Heaviland – Professional Development in Education, 2025
With the introduction of artificial intelligence (AI), particularly Generative AI (GenAI) to school settings, teachers are likely to be drawn into professional learning scenarios where they will be expected to learn how to use programs and applications for remediation and tutoring of children. Previous research highlights how professional learning…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
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Tobias Wyrwich; Marcus Kubsch; Hendrik Drachsler; Knut Neumann – Physical Review Physics Education Research, 2025
Students struggle to acquire the needed energy understanding to meaningfully participate in the energy discourse about socially relevant topics, such as energy transformation or climate change. Identifying students on differing learning trajectories, as well as differences in knowledge used, is essential to help students achieve the needed energy…
Descriptors: Learning Processes, Physics, Energy, Science Instruction
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Kexin Li; Wei Su – Innovations in Education and Teaching International, 2025
Incorporating Vygotsky's concepts of scaffolding and Zone of Proximal Development, this paper presents a qualitative study examining student roles in dialogic peer feedback learning, focusing on Chinese English-as-a-foreign-language (EFL) students in mixed translation proficiency triads within an English-Chinese translation course. During feedback…
Descriptors: Student Role, Scaffolding (Teaching Technique), English (Second Language), Second Language Learning
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Xiaoling Bai; Nur Rasyidah Mohd Nordin – Eurasian Journal of Applied Linguistics, 2025
A perfect writing skill has been deemed instrumental to achieving competence in EFL, yet it is considered one of the most impressive learning domains. This study investigates the impact of human-AI collaborative feedback on the writing proficiency of EFL students. It examines key teaching domains, including the teaching environment, teacher…
Descriptors: Artificial Intelligence, Feedback (Response), Evaluators, Writing Skills
Dorottya Demszky; Heather C. Hill; Eric S. Taylor; Ashlee Kupor; Deepak Varuvel Dennison; Chris Piech – Annenberg Institute for School Reform at Brown University, 2025
The role of teacher agency in professional learning has been the subject of several qualitative studies but has not yet been tested in an experimental setting. To provide causal evidence of the impact of teacher agency on the effectiveness of professional learning, we conducted a preregistered randomized controlled trial in an online computer…
Descriptors: Professional Autonomy, Faculty Development, Attribution Theory, Online Courses
Xiaoming Zhai, Editor; Joseph Krajcik, Editor – Oxford University Press, 2025
In the age of rapid technological advancements, the integration of Artificial Intelligence (AI), machine learning (ML), and large language models (LLMs) in Science, Technology, Engineering, and Mathematics (STEM) education has emerged as a transformative force, reshaping pedagogical approaches and assessment methodologies. "Uses of AI in STEM…
Descriptors: Artificial Intelligence, STEM Education, Technology Uses in Education, Educational Technology