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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
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
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
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
Zhuo Wang; Zhaoyi Yin; Ying Zheng; Xuehui Li; Li Zhang – Educational Technology & Society, 2025
As AI technologies like GPT models continue to reshape various aspects of society, it is imperative to investigate the perceptions and ethical considerations of graduate students regarding GPT's use in academic settings. This mixed-method exploratory study engaged 21 graduate students through surveys and focus group interviews. The findings…
Descriptors: Graduate Students, Graduate Study, Student Behavior, Ethics
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)
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
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
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)
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
Douglas Harris; Jamie Carroll; Debbie Kim; Nicholas Mattei; Olivia Carr – National Center for Research on Education Access and Choice, 2024
Massive online user review platforms, with their star ratings and text reviews, are reshaping the information available for consumer and public service decisions. We study the leading K-12 schooling platform, GreatSchools, applying machine learning (Natural Language Processing, NLP) to 600,000 reviews that encompass the vast majority of the…
Descriptors: Elementary Secondary Education, School Effectiveness, Parents, Teachers

Sami Baral; Li Lucy; Ryan Knight; Alice Ng; Luca Soldaini; Neil T. Heffernan; Kyle Lo – Grantee Submission, 2024
In real-world settings, vision language models (VLMs) should robustly handle naturalistic, noisy visual content as well as domain-specific language and concepts. For example, K-12 educators using digital learning platforms may need to examine and provide feedback across many images of students' math work. To assess the potential of VLMs to support…
Descriptors: Visual Learning, Visual Perception, Natural Language Processing, Freehand Drawing
Fahad Saleem Al-Hafdi; Sameer Mosa AlNajdi – Education and Information Technologies, 2024
During the last few years, the popularity of chatbots has risen and grown exponentially with the increase in demand for smartphones and messaging applications. Chatbots can be utilized in education by providing information about educational content, communication, and assistance, enhancing classroom participation, and facilitating collaborative…
Descriptors: Artificial Intelligence, Technology Uses in Education, Instructional Effectiveness, Learning Processes