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Yucheng Chu; Hang Li; Kaiqi Yang; Harry Shomer; Yasemin Copur-Gencturk; Leonora Kaldaras; Kevin Haudek; Joseph Krajcik; Namsoo Shin; Hui Liu; Jiliang Tang – International Educational Data Mining Society, 2025
Open-text responses provide researchers and educators with rich, nuanced insights that multiple-choice questions cannot capture. When reliably assessed, such responses have the potential to enhance teaching and learning. However, scaling and consistently capturing these nuances remain significant challenges, limiting the widespread use of…
Descriptors: Grading, Automation, Artificial Intelligence, Natural Language Processing
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Aimee Weathers; Diana Curtis – Journal of Technology and Teacher Education, 2025
The purpose of this mixed-methods study was to investigate how generative AI tools, particularly ChatGPT, impact preservice teachers' lesson plans and attitudes toward mathematics. Fifty-five undergraduate students who were enrolled in their first semester of a teacher education program participated in the study. Each student created two lesson…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Mathematics Instruction
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Mohammed Q. Shormani; Abdulrahaman Alfahad – SAGE Open, 2025
This article presents an empirical study investigating the ability of ChatGPT to translate religious texts involved in academic writing. Specifically, religious texts are not easy to translate even for human proficient translators. Three Arabic academic abstracts, religion-oriented, were involved in our study taken from AlQalam Journal which is…
Descriptors: Artificial Intelligence, Intelligent Tutoring Systems, Natural Language Processing, Arabic
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Mohsin Murtaza; Chi-Tsun Cheng; Mohammad Fard; John Zeleznikow – International Journal of Artificial Intelligence in Education, 2025
As modern vehicles continue to integrate increasingly sophisticated Advanced Driver Assistance Systems (ADAS) and Autonomous Vehicles (AV) functions, conventional user manuals may no longer be the most effective medium for conveying knowledge to drivers. This research analysed conventional, paper and video-based instructional methods versus a…
Descriptors: Educational Change, Driver Education, Motor Vehicles, Natural Language Processing
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Wen-Chiang Ivan Lim; Neil T. Heffernan III; Ivan Eroshenko; Wai Khumwang; Pei-Chen Chan – Grantee Submission, 2025
Intelligent tutoring systems are increasingly used in schools, providing teachers with valuable analytics on student learning. However, many teachers lack the time to review these reports in detail due to heavy workloads, and some face challenges with data literacy. This project investigates the use of large language models (LLMs) to generate…
Descriptors: Intelligent Tutoring Systems, Natural Language Processing, Assignments, Learning Management Systems
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Stephanie Moore; Amir Hedayati-Mehdiabadi; Victor Law; Sung Pil Kang – TechTrends: Linking Research and Practice to Improve Learning, 2024
Early hype cycles surrounding new technologies may promote simplistic binary options of either adoption or rejection, but socio-historical analyses of technologies illuminate how they are worked into shape by human actors. Humans enact agency through many choices that result in adaptations and contextual variations. In this piece, we argue that…
Descriptors: Artificial Intelligence, Natural Language Processing, Man Machine Systems, Ethics
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Patrícia Takaki; Moisés Lima Dutra – Education and Information Technologies, 2024
Much of the data produced and consumed by students, teachers, and educational managers is in textual format. Text Mining (TM) and Natural Language Processing (NLP) have been applied in the educational context in different ways. Ideally, such applications combine computational, linguistic, pedagogical, and psychological aspects. This article aims…
Descriptors: Literature Reviews, Higher Education, Distance Education, Content Analysis
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Alice Watanabe – Electronic Journal of e-Learning, 2024
Artificial intelligence (AI) in higher education is a complex issue that can be discussed from many different perspectives. There is currently a great need for ethical discussions about the use of AI in universities. For example, educational researchers and teachers are already talking a lot about fairness, accountability, transparency, bias,…
Descriptors: Artificial Intelligence, Higher Education, Ethics, Technology Uses in Education
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Bihao Hu; Longwei Zheng; Jiayi Zhu; Lishan Ding; Yilei Wang; Xiaoqing Gu – IEEE Transactions on Learning Technologies, 2024
This study explores and analyzes the specific performance of large language models (LLMs) in instructional design, aiming to unveil their potential strengths and possible weaknesses. Recently, the influence of LLMs has gradually increased in multiple fields, yet exploratory research on their application in education remains relatively scarce. In…
Descriptors: Artificial Intelligence, Natural Language Processing, Instructional Design, Prompting
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Kelsey Behringer; Devyn Maguire – New Directions for Community Colleges, 2024
This article dives into the reality of how, since 2023, generative artificial intelligence (AI) has emerged as an inescapable force in education and highlights the work of community college faculty in use of AI in teaching and learning. ChatGPT is an example of a relatively new and rapidly evolving aspect of AI research, the large language model.…
Descriptors: Artificial Intelligence, Technology Uses in Education, Opportunities, College Faculty
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Shuguang Wang; Le Qin; Qian Yu – AERA Online Paper Repository, 2024
ChatGPT, a generative, pre-trained transformer gained great attention in various fields, Education included. The authors feel the need to investigate the views of practitioners and researchers regarding this issue. Using the systematic review as the structure of research method, the authors created their criteria, and got 65 papers after applying…
Descriptors: Artificial Intelligence, Metacognition, Plagiarism, Teaching Methods
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Bahar Radmehr; Adish Singla; Tanja Käser – International Educational Data Mining Society, 2024
There has been a growing interest in developing learner models to enhance learning and teaching experiences in educational environments. However, existing works have primarily focused on structured environments relying on meticulously crafted representations of tasks, thereby limiting the agent's ability to generalize skills across tasks. In this…
Descriptors: Reinforcement, Artificial Intelligence, Educational Environment, Natural Language Processing
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Manh Hung Nguyen; Sebastian Tschiatschek; Adish Singla – International Educational Data Mining Society, 2024
Student modeling is central to many educational technologies as it enables predicting future learning outcomes and designing targeted instructional strategies. However, open-ended learning domains pose challenges for accurately modeling students due to the diverse behaviors and a large space of possible misconceptions. To approach these…
Descriptors: Artificial Intelligence, Natural Language Processing, Synthesis, Student Behavior
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Jionghao Lin; Eason Chen; Zifei Han; Ashish Gurung; Danielle R. Thomas; Wei Tan; Ngoc Dang Nguyen; Kenneth R. Koedinger – International Educational Data Mining Society, 2024
Automated explanatory feedback systems play a crucial role in facilitating learning for a large cohort of learners by offering feedback that incorporates explanations, significantly enhancing the learning process. However, delivering such explanatory feedback in real-time poses challenges, particularly when high classification accuracy for…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Feedback (Response)
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Ramotowska, Sonia; Steinert-Threlkeld, Shane; Maanen, Leendert; Szymanik, Jakub – Cognitive Science, 2023
According to logical theories of meaning, a meaning of an expression can be formalized and encoded in truth conditions. Vagueness of the language and individual differences between people are a challenge to incorporate into the meaning representations. In this paper, we propose a new approach to study truth-conditional representations of vague…
Descriptors: Computation, Models, Semantics, Decision Making
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