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Michael Agyemang Adarkwah; Samuel Anokye Badu; Evans Appiah Osei; Enoch Adu-Gyamfi; Jonathan Odame; Käthe Schneider – Discover Education, 2025
The advancement of artificial intelligence (AI) tools has revolutionized teaching and learning, particularly in healthcare education, where they enhance pedagogy, foster immersive learning, and support healthcare provision. However, their use in healthcare education is contentious, warranting careful examination, especially regarding Generative AI…
Descriptors: Artificial Intelligence, Health Services, Medical Education, Technological Advancement
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Hanbing Xue; Weishan Liu – SAGE Open, 2025
The application of natural language processing (NLP) technology in the field of education has attracted considerable attention. This study takes 716 articles from the Web of Science database from 1998 to 2023 as its research sample. Using bibliometrics as the theoretical foundation, and employing methods such as literature review and knowledge…
Descriptors: Bibliometrics, Natural Language Processing, Technology Uses in Education, Educational Trends
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Andrew Williams – Intersection: A Journal at the Intersection of Assessment and Learning, 2025
Generative AI has the potential to transform higher education assessment. This study examines the opportunities and challenges of integrating AI into coursework assessments, highlighting the need to rethink traditional paradigms. A case study is presented that explores AI as an auxiliary learning tool in postgraduate coursework. Students found AI…
Descriptors: Artificial Intelligence, Technology Uses in Education, Technology Integration, Higher Education
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Eguchi, Masaki; Kyle, Kristopher – Modern Language Journal, 2020
Lexical sophistication has been an important indicator of productive lexical proficiency for almost 30 years. Although lexical sophistication has most often been operationalized as the proportion of low frequency words in a text, a growing body of research has indicated that a number of indices such as concreteness, hypernymy, and n-gram…
Descriptors: Oral Language, Language Proficiency, Lexicology, English Language Learners
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Kurdi, Ghader; Leo, Jared; Parsia, Bijan; Sattler, Uli; Al-Emari, Salam – International Journal of Artificial Intelligence in Education, 2020
While exam-style questions are a fundamental educational tool serving a variety of purposes, manual construction of questions is a complex process that requires training, experience, and resources. This, in turn, hinders and slows down the use of educational activities (e.g. providing practice questions) and new advances (e.g. adaptive testing)…
Descriptors: Computer Assisted Testing, Adaptive Testing, Natural Language Processing, Questioning Techniques
Nicula, Bogdan; Perret, Cecile A.; Dascalu, Mihai; McNamara, Danielle S. – Grantee Submission, 2020
Theories of discourse argue that comprehension depends on the coherence of the learner's mental representation. Our aim is to create a reliable automated representation to estimate readers' level of comprehension based on different productions, namely self-explanations and answers to open-ended questions. Previous work relied on Cohesion Network…
Descriptors: Network Analysis, Reading Comprehension, Automation, Artificial Intelligence
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Walker, Jeremy; Coleman, Jason – College & Research Libraries, 2021
This study aims to evaluate the effectiveness and potential utility of using machine learning and natural language processing techniques to develop models that can reliably predict the relative difficulty of incoming chat reference questions. Using a relatively large sample size of chat transcripts (N = 15,690), an empirical experimental design…
Descriptors: Artificial Intelligence, Natural Language Processing, Prediction, Library Services
Botarleanu, Robert-Mihai; Dascalu, Mihai; Allen, Laura K.; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2021
Text summarization is an effective reading comprehension strategy. However, summary evaluation is complex and must account for various factors including the summary and the reference text. This study examines a corpus of approximately 3,000 summaries based on 87 reference texts, with each summary being manually scored on a 4-point Likert scale.…
Descriptors: Computer Assisted Testing, Scoring, Natural Language Processing, Computer Software
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Jia, Qinjin; Cui, Jialin; Xiao, Yunkai; Liu, Chengyuan; Rashid, Parvez; Gehringer, Edward – International Educational Data Mining Society, 2021
Peer assessment has been widely applied across diverse academic fields over the last few decades, and has demonstrated its effectiveness. However, the advantages of peer assessment can only be achieved with high-quality peer reviews. Previous studies have found that high-quality review comments usually comprise several features (e.g., contain…
Descriptors: Peer Evaluation, Models, Artificial Intelligence, Evaluation Methods
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Romualdo Atibagos Mabuan – International Journal of Technology in Education, 2024
This study investigates the perceptions of English language teachers regarding the use of ChatGPT in English Language Teaching (ELT). The study aims to fill the research gap by exploring teachers' perspectives on the integration of ChatGPT as an instructional tool and its implications for ELT practices. Using a mixed methods approach, the study…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, English (Second Language)
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Shi Pu; Yu Yan; Brandon Zhang – Journal of Educational Data Mining, 2024
We propose a novel model, Wide & Deep Item Response Theory (Wide & Deep IRT), to predict the correctness of students' responses to questions using historical clickstream data. This model combines the strengths of conventional Item Response Theory (IRT) models and Wide & Deep Learning for Recommender Systems. By leveraging clickstream…
Descriptors: Prediction, Success, Data Analysis, Learning Analytics
Hong Jiao, Editor; Robert W. Lissitz, Editor – IAP - Information Age Publishing, Inc., 2024
With the exponential increase of digital assessment, different types of data in addition to item responses become available in the measurement process. One of the salient features in digital assessment is that process data can be easily collected. This non-conventional structured or unstructured data source may bring new perspectives to better…
Descriptors: Artificial Intelligence, Natural Language Processing, Psychometrics, Computer Assisted Testing
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Yasemin Cetin; Özgür Tas; Halil Alakus; Halil Ibrahim Kaplan – Educational Process: International Journal, 2024
Background/purpose: ChatGPT has become one of the groundbreaking examples of artificial intelligence-based chatbots with its capacity to produce texts and engage in human-like conversations. Therefore, it has garnered the attention of people with diverse backgrounds, including educational professionals. The current study aims to investigate how…
Descriptors: Principals, Administrator Attitudes, Teacher Attitudes, Artificial Intelligence
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Mustafa Taktak; Mehmet Sükrü Bellibas; Mustafa Özgenel – Educational Process: International Journal, 2024
Background/Purpose: Integrating artificial intelligence tools within educational settings has generated considerable debate, yet empirical research that offers implications of its usage remains scarce. This study aims to qualitatively assess the perceptions and experiences of school principals and teachers regarding the use of ChatGPT in K-12…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Futures (of Society)
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Md. Rabiul Awal; Asaduzzaman – Higher Education, Skills and Work-based Learning, 2024
Purpose: This qualitative work aims to explore the university students' attitude toward advantages, drawbacks and prospects of ChatGPT. Design/methodology/approach: This paper applies well accepted Colaizzi's phenomenological descriptive method of enquiry and content analysis method to reveal the ChatGPT user experience of students in the higher…
Descriptors: Student Experience, Technology Uses in Education, Artificial Intelligence, Natural Language Processing
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