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Ishrat Ahmed; Wenxing Liu; Rod D. Roscoe; Elizabeth Reilley; Danielle S. McNamara – Grantee Submission, 2025
Large language models (LLMs) are increasingly being utilized to develop tools and services in various domains, including education. However, due to the nature of the training data, these models are susceptible to inherent social or cognitive biases, which can influence their outputs. Furthermore, their handling of critical topics, such as privacy…
Descriptors: Artificial Intelligence, Natural Language Processing, Computer Mediated Communication, College Students
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Wenhao Wang; Etsuko Kumamoto; Chengjiu Yin – International Educational Data Mining Society, 2024
The e-book system, widely used in learning and teaching, has generated a large amount of log data over time. Researchers analyzing these data have discovered the existence of student's jump back behavior, which is positively correlated with academic achievement. However, they also found that this behavior has the disadvantage of low efficiency. To…
Descriptors: Electronic Books, Natural Language Processing, Artificial Intelligence, Reading
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Wesley Morris; Scott Crossley; Langdon Holmes; Chaohua Ou; Mihai Dascalu; Danielle McNamara – International Journal of Artificial Intelligence in Education, 2025
As intelligent textbooks become more ubiquitous in classrooms and educational settings, the need to make them more interactive arises. An alternative is to ask students to generate knowledge in response to textbook content and provide feedback about the produced knowledge. This study develops Natural Language Processing models to automatically…
Descriptors: Formative Evaluation, Feedback (Response), Textbooks, Artificial Intelligence
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Benjamin Brummernhenrich; Christian L. Paulus; Regina Jucks – British Journal of Educational Technology, 2025
Generative AI systems like chatbots are increasingly being introduced into learning, teaching and assessment scenarios at universities. While previous research suggests that users treat chatbots like humans, computer systems are still often perceived as less trustworthy, potentially impairing their usefulness in learning contexts. How are…
Descriptors: Higher Education, Artificial Intelligence, College Students, Feedback (Response)
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Nguyen, Huy; Xiong, Wenting; Litman, Diane – International Journal of Artificial Intelligence in Education, 2017
A peer-review system that automatically evaluates and provides formative feedback on free-text feedback comments of students was iteratively designed and evaluated in college and high-school classrooms. Classroom assignments required students to write paper drafts and submit them to a peer-review system. When student peers later submitted feedback…
Descriptors: Computer Uses in Education, Computer Mediated Communication, Feedback (Response), Peer Evaluation
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Knight, Allan; Almeroth, Kevin – Journal of Interactive Learning Research, 2011
As part of the research carried out at the University of California, Santa Barbara's Center for Information Technology and Society (CITS), the Paper Authentication and Integrity Research (PAIR) project was launched. We began by investigating how one recent technology affected student learning outcomes. One aspect of this research was to study the…
Descriptors: Plagiarism, Student Attitudes, Form Classes (Languages), Researchers
Eldakak, Sam – Online Submission, 2012
Computers can help the range of ways learners build up their own perception. Students who collect data from the Internet can be self-directed and independent. They can select sources to study and the connections to follow. Relying on the bounds laid down by teachers, the students may be in full control of their subjects and their studies. Students…
Descriptors: Computer Uses in Education, Computer Software, Educational Technology, Multimedia Materials
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Kato, Taichi; Arakawa, Chuichi – Simulation & Gaming, 2008
BIT BY BIT is an encryption game that is designed to improve students' understanding of natural language processing in computers. Participants encode clear words into binary code using an encryption key and exchange them in the game. BIT BY BIT enables participants who do not understand the concept of binary numbers to perform the process of…
Descriptors: Computer Science, Educational Technology, Language Processing, Natural Language Processing
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White, Daniel R.; Joy, Mike S. – Journal on Educational Resources in Computing, 2004
With the increasing levels of access to higher education in the United Kingdom, larger class sizes make it unrealistic for tutors to be expected to identify instances of peer-to-peer plagiarism by eye and so automated solutions to the problem are required. This document details a novel algorithm for comparison of suspect documents at a sentence…
Descriptors: Plagiarism, Computer Software, Foreign Countries, Natural Language Processing