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Ziqing Peng; Yan Wan – Education and Information Technologies, 2025
What makes students prefer to self-disclosure to AI teaching assistant (AI TA) than human teaching assistants? Understanding this question can help online learning platforms better understand students' needs in the data collection stage to provide more appropriate recommendations and deploy AI and human-AI collaboration more effectively. Based on…
Descriptors: Teaching Assistants, Artificial Intelligence, Student Attitudes, Self Disclosure (Individuals)
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Joanna Blahopoulou; Silvia Ortiz-Bonnin – Education and Information Technologies, 2025
Today, there is no doubt that Artificial Intelligence (AI) presents both opportunities and challenges in higher education. This study examines three key areas: (1) students' use of ChatGPT, (2) their perceptions of its benefits and costs, and (3) the differences in attitudes toward AI integration in higher education between ChatGPT users and…
Descriptors: Student Attitudes, Undergraduate Students, Artificial Intelligence, Technology Uses in Education
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Yuntian Xie; Ying Li; Taowen Yu; Yuxuan Liu – Education and Information Technologies, 2025
This study aimed to develop and validate the Metacognitions about Generative AI Use Scale (MGAUS) to assess college students' metacognitive beliefs about generative AI and to explore these metacognitions as predictors of generative AI addiction risk. A total of 1229 college students from China participated in the study, providing data through an…
Descriptors: Foreign Countries, College Students, Metacognition, Student Attitudes
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Mathieu Balaguer; Julien Pinquier; Jérôme Farinas; Virginie Woisard – International Journal of Language & Communication Disorders, 2025
Background: Perceptual evaluation of speech disorders produces scores that poorly predict the consequences of speech impairment on the communication abilities of patients treated for oral/oropharyngeal cancer. This may be mitigated by automatic speech analysis. Aim: To measure communication and speech impairment using automatic analyses of…
Descriptors: Prediction, Speech Impairments, Patients, Cancer
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Yu Xiong; Shengyi Chen; Ting Cai; Lulu Chen; Jun Li – International Educational Data Mining Society, 2025
Teacher gesture recognition aims to identify and interpret teacher gestures within academic settings. It has been applied in domains such as teaching performance evaluation, the optimization of online education, and special needs education. However, the background similarity of teacher gestures, the inter-class similarity, and the intra-class…
Descriptors: Artificial Intelligence, Natural Language Processing, Nonverbal Communication, Classroom Communication
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Liang Tang; Nigel Bosch – International Educational Data Mining Society, 2025
Feature engineering plays a critical role in the development of machine learning systems for educational contexts, yet its impact on student trust remains understudied. Traditional approaches have focused primarily on optimizing model performance through expert-crafted features, while the emergence of AutoML offers automated alternatives for…
Descriptors: Artificial Intelligence, Design, Trust (Psychology), Student Attitudes
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Anurata Prabha Hridi; Muntasir Hoq; Zhikai Gao; Collin Lynch; Rajeev Sahay; Seyyedali Hosseinalipour; Bita Akram – International Educational Data Mining Society, 2025
Social interactions among classroom peers, represented as social learning networks (SLNs), play a crucial role in enhancing learning outcomes. While SLN analysis has recently garnered attention, most existing approaches rely on centralized training, where data is aggregated and processed on a local/cloud server with direct access to raw data.…
Descriptors: Privacy, Peer Relationship, Online Courses, Social Networks
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Michel C. Desmarais; Arman Bakhtiari; Ovide Bertrand Kuichua Kandem; Samira Chiny Folefack Temfack; Chahé Nerguizian – International Educational Data Mining Society, 2025
We propose a novel method for automated short answer grading (ASAG) designed for practical use in real-world settings. The method combines LLM embedding similarity with a nonlinear regression function, enabling accurate prediction from a small number of expert-graded responses. In this use case, a grader manually assesses a few responses, while…
Descriptors: Grading, Automation, Artificial Intelligence, Natural Language Processing
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Maciej Pankiewicz; Yang Shi; Ryan S. Baker – International Educational Data Mining Society, 2025
Knowledge Tracing (KT) models predicting student performance in intelligent tutoring systems have been successfully deployed in several educational domains. However, their usage in open-ended programming problems poses multiple challenges due to the complexity of the programming code and a complex interplay between syntax and logic requirements…
Descriptors: Algorithms, Artificial Intelligence, Models, Intelligent Tutoring Systems
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Fan Yang; Jill E. Stefaniak – Educational Technology Research and Development, 2025
In this study, Q methodology was employed to explore instructional designers' perceptions of integrating ChatGPT in their design practices. Compared with traditional survey-based instruments that rely heavily on Likert-scale items, open-ended questions, interviews, or focus groups, Q methodology has the potential to systematically reveal and study…
Descriptors: Instructional Design, Technology Integration, Artificial Intelligence, Teacher Attitudes
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Abdulrahman M. Al-Zahrani – SAGE Open, 2025
This study examines the impact of Artificial Intelligence (AI) chatbots on the loss of human connection and emotional support among higher education students. To do so, a quantitative research design is employed. An online survey questionnaire is distributed to a sample of 819 higher education students, assessing concerns about human connection,…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, College Students
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Terrell L. Strayhorn – Journal of College Student Development, 2025
Data from 296 college students were analyzed to examine their use and perceptions of artificial intelligence (AI) tools. A diverse sample across different academic majors reported relatively pervasive use of AI tools. Almost 80% reported using voice assistants such as Alexa, Google, and SIRI. Nearly three-fourths reported using ChatGPT, one of the…
Descriptors: College Students, Student Attitudes, Artificial Intelligence, Technology Uses in Education
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Yuxing Cai; Sha Tian – Education and Information Technologies, 2025
The rise of Generative AI (GenAI) tools, such as ChatGPT, is transforming translators' information-seeking behavior (ISB), traditionally centered on web search. This study compares student translators' ISB in web-based and GenAI-driven contexts using a literature-informed ISB analytical framework, developed from a systematic review of existing ISB…
Descriptors: Translation, Web Sites, Artificial Intelligence, Technology Uses in Education
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Ioulia Koniou; Elise Douard; Marc J. Lanovaz – Journal of Autism and Developmental Disorders, 2025
Purpose: The purpose of the study was to develop and test a virtual reality application designed to put the participants "in the shoes" of an autistic person during a routine task. Method: The study involved a randomized controlled trial that included 103 participants recruited from a technical college. Each participant responded to…
Descriptors: Computer Uses in Education, Artificial Intelligence, Computer Simulation, Consciousness Raising
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Eva Heinrich – Open Praxis, 2025
Online proctoring systems are employed to monitor students during exams, safeguarding assessment integrity when in-person observation is not feasible. The systems leverage advanced technologies, including artificial intelligence (AI) and biometrics, to authenticate students and identify potential exam rule violations. However, concerns about data…
Descriptors: Supervision, Privacy, Information Security, Artificial Intelligence
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