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Deliang Wang; Yaqian Zheng; Jinjiang Li; Gaowei Chen – IEEE Transactions on Learning Technologies, 2025
Researchers have increasingly utilized artificial intelligence to automatically analyze classroom dialogue, aiming to provide timely feedback to teachers due to its educational significance. However, traditional machine learning and deep learning models face challenges, such as limited performance and lack of generalizability, across various…
Descriptors: Classroom Communication, Computational Linguistics, Cues, Generalization
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Liuying Gong; Jingyuan Chen; Fei Wu – IEEE Transactions on Learning Technologies, 2025
The capabilities of large language models (LLMs) in language comprehension, conversational interaction, and content generation have led to their widespread adoption across various educational stages and contexts. Given the fundamental role of education, concerns are rising about whether LLMs can serve as competent teachers. To address the…
Descriptors: Artificial Intelligence, Computer Software, Computational Linguistics, Comparative Analysis
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Cleon Xavier; Luiz Rodrigues; Newarney Costa; Rodrigues Neto; Gabriel Alves; Taciana Pontual Falcao; Dragan Gasevic; Rafael Ferreira Mello – IEEE Transactions on Learning Technologies, 2025
Providing timely and personalized feedback on open-ended student responses is a challenge in education due to the increased workloads and time constraints educators face. While existing research has explored how learning analytic approaches can support feedback provision, previous studies have not sufficiently investigated educators' perspectives…
Descriptors: Teacher Empowerment, Learning Analytics, Artificial Intelligence, Computer Software
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Chad C. Tossell; Nathan L. Tenhundfeld; Ali Momen; Katrina Cooley; Ewart J. de Visser – IEEE Transactions on Learning Technologies, 2024
This article examined student experiences before and after an essay writing assignment that required the use of ChatGPT within an undergraduate engineering course. Utilizing a pre-post study design, we gathered data from 24 participants to evaluate ChatGPT's support for both completing and grading an essay assignment, exploring its educational…
Descriptors: Student Attitudes, Computer Software, Artificial Intelligence, Grading
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Yishen Song; Qianta Zhu; Huaibo Wang; Qinhua Zheng – IEEE Transactions on Learning Technologies, 2024
Manually scoring and revising student essays has long been a time-consuming task for educators. With the rise of natural language processing techniques, automated essay scoring (AES) and automated essay revising (AER) have emerged to alleviate this burden. However, current AES and AER models require large amounts of training data and lack…
Descriptors: Scoring, Essays, Writing Evaluation, Computer Software
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Gasevic, D.; Zouaq, Amal; Torniai, Carlo; Jovanovic, J.; Hatala, Marek – IEEE Transactions on Learning Technologies, 2011
Recent research in learning technologies has demonstrated many promising contributions from the use of ontologies and semantic web technologies for the development of advanced learning environments. In spite of those benefits, ontology development and maintenance remain the key research challenges to be solved before ontology-enhanced learning…
Descriptors: Foreign Countries, Natural Language Processing, Computer Interfaces, Web 2.0 Technologies