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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
Crossley, Scott; Wan, Qian; Allen, Laura; McNamara, Danielle – Reading and Writing: An Interdisciplinary Journal, 2023
Synthesis writing is widely taught across domains and serves as an important means of assessing writing ability, text comprehension, and content learning. Synthesis writing differs from other types of writing in terms of both cognitive and task demands because it requires writers to integrate information across source materials. However, little is…
Descriptors: Writing Skills, Cognitive Processes, Essays, Cues
Chen, Howard Hao-Jan; Yang, Christine Ting-Yu; Lai, Kyle Kuo-Wei – Interactive Learning Environments, 2023
Recent studies on the use of Intelligent Personal Assistant (IPA) for second language (L2) learning have found that IPAs such as "Amazon's Alexa" is useful and motivating for L2 learners and that learners' language proficiency might influence their perceptions toward IPAs. However, most existing studies focused on the potentials of…
Descriptors: English (Second Language), Second Language Learning, College Students, Artificial Intelligence
Yoo, Jiseung; Kim, Min Kyeong – Contemporary Educational Technology, 2023
This study focuses on how teachers' pedagogical content knowledge (PCK) of mathematics may differ depending on teacher interactions in an online teacher community of practice (CoP). The study utilizes data from 26,857 posts collected from the South Korean self-generated online teacher CoP, 'Indischool'. This data was then analyzed using natural…
Descriptors: Natural Language Processing, Elementary School Teachers, Pedagogical Content Knowledge, Mathematics Instruction
Hannah K. D’Apice; Patricia Bromley – Environmental Education Research, 2023
Anthropogenic climate change is a scientific fact, but U.S. public discourse around the issue remains mired in controversy, including in education. Our study leverages natural language processing methods to give a precise look into the extent to which climate change-related topics are covered in 30 of the most widely used high school history…
Descriptors: Environmental Education, Climate, Discourse Analysis, United States History
Advancing Language Assessment with AI and ML--Leaning into AI Is Inevitable, but Can Theory Keep Up?
Xiaoming Xi – Language Assessment Quarterly, 2023
Following the burgeoning growth of artificial intelligence (AI) and machine learning (ML) applications in language assessment in recent years, the meteoric rise of ChatGPT and its sweeping applications in almost every sector have left us in awe, scrambling to catch up by developing theories and best practices. This special issue features studies…
Descriptors: Artificial Intelligence, Theory Practice Relationship, Language Tests, Man Machine Systems
Chahna Gonsalves – Journal of Learning Development in Higher Education, 2023
Multiple-choice quizzes (MCQs) are a popular form of assessment. A rapid shift to online assessment during the COVID-19 pandemic in 2020, drove the uptake of MCQs, yet limited invigilation and wide access to material on the internet allow students to solve the questions via internet search. ChatGPT, an artificial intelligence (AI) agent trained on…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Multiple Choice Tests
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