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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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Rakovic, Mladen; Iqbal, Sehrish; Li, Tongguang; Fan, Yizhou; Singh, Shaveen; Surendrannair, Surya; Kilgour, Jonathan; Graaf, Joep; Lim, Lyn; Molenaar, Inge; Bannert, Maria; Moore, Johanna; Gaševic, Dragan – Journal of Computer Assisted Learning, 2023
Background: Assignments that involve writing based on several texts are challenging to many learners. Formative feedback supporting learners in these tasks should be informed by the characteristics of evolving written product and by the characteristics of learning processes learners enacted while developing the product. However, formative feedback…
Descriptors: Artificial Intelligence, Essays, High Achievement, Writing Achievement
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Safaa M. Abdelhalim – Journal of Computer Assisted Learning, 2024
Background: Introducing new technologies in education sparks debates, disrupting traditional practices, and requiring teacher adaptation. ChatGPT is an example. Research explores its benefits and concerns in education, with recommendations for classroom use. Nevertheless, limited evidence supports ChatGPT as a tool for supporting English as a…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Second Language Learning
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Dabae Lee; Taekwon Son; Sheunghyun Yeo – Journal of Computer Assisted Learning, 2025
Background: Artificial Intelligence (AI) technologies offer unique capabilities for preservice teachers (PSTs) to engage in authentic and real-time interactions using natural language. However, the impact of AI technology on PSTs' responsive teaching skills remains uncertain. Objectives: The primary objective of this study is to examine whether…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Preservice Teachers
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Xin Tang; Zhiqiang Yuan; Shaojun Qu – Journal of Computer Assisted Learning, 2025
Background: Generative artificial intelligence (AI) represents a significant technological leap, with platforms like OpenAI's ChatGPT and Baidu's Ernie Bot at the forefront of innovation. This technology has seen widespread adoption across various sectors of society and is anticipated to revolutionise the educational landscape, especially in the…
Descriptors: Influences, College Students, Student Behavior, Intention
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Ting-Ting Wu; Hsin-Yu Lee; Pei-Hua Chen; Chia-Ju Lin; Yueh-Min Huang – Journal of Computer Assisted Learning, 2025
Background: Science, Technology, Engineering, and Mathematics (STEM) education in Asian universities struggles to integrate Knowledge, Skills, and Attitudes (KSA) due to large classes and student reluctance. While ChatGPT offers solutions, its conventional use may hinder independent critical thinking. Objectives: This study introduces PA-GPT,…
Descriptors: Peer Evaluation, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
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Liou, H.-C.; Yang, P.-C.; Chang, J. S. – Journal of Computer Assisted Learning, 2012
Various writing assistance tools have been developed through efforts in the areas of natural language processing with different degrees of success of curriculum integration depending on their functional rigor and pedagogical designs. In this paper, we developed a system, WriteAhead, that provides six types of suggestions when non-native graduate…
Descriptors: Graduate Students, Second Language Learning, Computer Software, Computer System Design
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Dinet, Jrme; Favart, Monik; Passerault, Jean-Michel – Journal of Computer Assisted Learning, 2004
Boolean systems still constitute most of the installed base of online public access catalogues (OPACs) in the French universities even if many studies have shown that Boolean operators are not frequently used by non-librarian users (by contrast with professional librarians). The first study examined the use of Boolean operators by French…
Descriptors: Natural Language Processing, Librarians, Foreign Countries, College Students