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Hongfeng Zhang; Fanbo Li; Xiaolong Chen – Journal of Educational Computing Research, 2025
This study addresses the gap in understanding graduate students' sustained engagement behavior (SEB) with generative artificial intelligence (GAI) by integrating the Technology Acceptance Model (TAM), Expectation Confirmation Theory (ECT), and Theory of Reasoned Action (TRA) into a comprehensive embedding model. It introduces the Technology…
Descriptors: Graduate Students, Artificial Intelligence, Learner Engagement, Foreign Countries
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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
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Alison M. O'Connor; Jennifer Gongola; Kaila C. Bruer; Thomas D. Lyon; Angela D. Evans – Applied Cognitive Psychology, 2025
The accurate detection of children's truthful and dishonest reports is essential as children can serve as important providers of information. Research using automated facial coding and machine learning found that children who were asked to lie about an event were more likely to look surprised when hearing the first question during an interview…
Descriptors: Deception, Nonverbal Communication, Recognition (Psychology), Children
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Changyu Yang; Adam Stivers – Journal of Education for Business, 2024
The rapid advancement of artificial intelligence (AI) has given rise to sophisticated language models that excel in understanding and generating human-like text. With the capacity to process vast amounts of information, these models effectively tackle problems across diverse domains. In this paper, we present a comparative analysis of prominent AI…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Comparative Analysis
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Giannakas, Filippos; Troussas, Christos; Krouska, Akrivi; Sgouropoulou, Cleo; Voyiatzis, Ioannis – Education and Information Technologies, 2022
Working in groups is an important collaboration activity in the educational context, where a variety of factors can influence the prediction of the teams' performance. In the pertinent bibliography, several machine learning models are available for delivering predictions. In this sense, the main goal of the current research is to assess 28…
Descriptors: Comparative Analysis, Artificial Intelligence, Prediction, Cooperative Learning
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Thomas Mgonja – Education and Information Technologies, 2024
The successful completion of remedial mathematics is widely recognized as a crucial factor for college success. However, there is considerable concern and ongoing debate surrounding the low completion rates observed in remedial mathematics courses across various parts of the world. This study applies explainable artificial intelligence (XAI) tools…
Descriptors: Higher Education, Remedial Mathematics, Artificial Intelligence, Predictor Variables
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Alyssa P. Lawson; Amedee Marchand Martella; Kristen LaBonte; Cynthia Y. Delgado; Fangzheng Zhao; Justin A. Gluck; Mitchell E. Munns; Ashleigh Wells LeRoy; Richard E. Mayer – Educational Psychology Review, 2024
A substantial amount of media comparison research has been conducted in the last decade to investigate whether students learn Science, Technology, Engineering, and Mathematics (STEM) content better in immersive virtual reality (IVR) or more traditional learning environments. However, a thorough review of the design and implementation of…
Descriptors: Mass Media, Comparative Analysis, Artificial Intelligence, STEM Education
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Mark Johnson; Rafiq Saleh – Interactive Learning Environments, 2024
Educational assessment is inherently uncertain, where physiological, psychological and social factors play an important role in establishing judgements which are assumed to be "absolute". AI and other algorithmic approaches to grading of student work strip-out uncertainty, leading to a lack of inspectability in machine judgement and…
Descriptors: Artificial Intelligence, Evaluation Methods, Technology Uses in Education, Man Machine Systems
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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)
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Wei Li; Walter Leite; Jia Quan – Society for Research on Educational Effectiveness, 2023
Background: Multilevel randomized controlled trials (MRCTs) have been widely used to evaluate the causal effects of educational interventions. Traditionally, educational researchers and policymakers focused on the average treatment effects (ATE) of the intervention. Recently there has been an increasing interest in evaluating the heterogeneity of…
Descriptors: Artificial Intelligence, Identification, Hierarchical Linear Modeling, Randomized Controlled Trials
Kye, Anna – ProQuest LLC, 2023
Every year, the national high school graduation rate is declining and impacting the number of students applying to colleges. Moreover, the majority of students are applying to more than one college. This makes a lot of colleges to be highly competitive in student recruitment for enrollment and thus, the necessity for institutions to anticipate…
Descriptors: Comparative Analysis, Classification, College Enrollment, Prediction
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Xiaoming Zhai; Matthew Nyaaba; Wenchao Ma – Science & Education, 2025
This study aimed to examine an assumption regarding whether generative artificial intelligence (GAI) tools can overcome the cognitive intensity that humans suffer when solving problems. We examine the performance of ChatGPT and GPT-4 on NAEP science assessments and compare their performance to students by cognitive demands of the items. Fifty-four…
Descriptors: Artificial Intelligence, National Competency Tests, Elementary Secondary Education, Problem Solving
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Siyi Cao; Yizhong Xu; Tongquan Zhou; Siruo Zhou – Education and Information Technologies, 2025
ChatGPT has been demonstrated to possess significant capabilities in generating intricate human-like text, and recent studies have established that its performance in theory of mind (ToM) tasks is strikingly comparable to a nine-year-old child's. However, it remains unknown whether ChatGPT outperforms children of this age group in Chinese writing,…
Descriptors: Foreign Countries, Artificial Intelligence, Theory of Mind, Chinese
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Alexis Danielle Bolick; Rafael Leonardo da Silva – TechTrends: Linking Research and Practice to Improve Learning, 2024
This article explores the potential impact of Artificial Intelligence (AI) tools on Instructional Design (ID) workflows and organizations from a systems thinking perspective (Meadows, 2008). We provide an in-depth analysis of how three AI tools, ChatGPT, Midjourney, and Descript, can enhance efficiency in instructional design content creation…
Descriptors: Artificial Intelligence, Instructional Design, Task Analysis, Ethics
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Yuan Tian; Xi Yang; Suhail A. Doi; Luis Furuya-Kanamori; Lifeng Lin; Joey S. W. Kwong; Chang Xu – Research Synthesis Methods, 2024
RobotReviewer is a tool for automatically assessing the risk of bias in randomized controlled trials, but there is limited evidence of its reliability. We evaluated the agreement between RobotReviewer and humans regarding the risk of bias assessment based on 1955 randomized controlled trials. The risk of bias in these trials was assessed via two…
Descriptors: Risk, Randomized Controlled Trials, Classification, Robotics
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