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Ibnatul Jalilah Yusof – Journal of Information Technology Education: Research, 2025
Aim/Purpose: This paper examines the potential of ChatGPT-assisted retrieval practice to enhance students' final exam performance. ChatGPT was utilized to generate questions and deliver timely feedback during retrieval practice, supporting learning in large class settings where providing personalized feedback is often challenging. Background:…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Scores
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Morgan J. Clark; Micke Reynders; Thomas A. Holme – Journal of Chemical Education, 2024
In the field of education, ChatGPT has become a topic of debate for its usefulness as a learning tool. This article focuses on non-science majors' (n = 29) perceptions of a ChatGPT enabled final exam, where, prior to the exam, students wrote papers on science and sustainability and, during the final exam, students were asked to compare their paper…
Descriptors: Student Experience, Artificial Intelligence, Natural Language Processing, Tests
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Akpinar, Nil-Jana; Ramdas, Aaditya; Acar, Umut – International Educational Data Mining Society, 2020
Educational software data promises unique insights into students' study behaviors and drivers of success. While much work has been dedicated to performance prediction in massive open online courses, it is unclear if the same methods can be applied to blended courses and a deeper understanding of student strategies is often missing. We use pattern…
Descriptors: Learning Strategies, Blended Learning, Learning Analytics, Student Behavior
Allen, Laura K.; Mills, Caitlin; Jacovina, Matthew E.; Crossley, Scott; D'Mello, Sidney; McNamara, Danielle S. – Grantee Submission, 2016
Writing training systems have been developed to provide students with instruction and deliberate practice on their writing. Although generally successful in providing accurate scores, a common criticism of these systems is their lack of personalization and adaptive instruction. In particular, these systems tend to place the strongest emphasis on…
Descriptors: Learner Engagement, Psychological Patterns, Writing Instruction, Essays
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Crossley, Scott; Allen, Laura K.; Snow, Erica L.; McNamara, Danielle S. – Grantee Submission, 2015
This study investigates a new approach to automatically assessing essay quality that combines traditional approaches based on assessing textual features with new approaches that measure student attributes such as demographic information, standardized test scores, and survey results. The results demonstrate that combining both text features and…
Descriptors: Automation, Scoring, Essays, Evaluation Methods
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Sukkarieh, Jane Z.; von Davier, Matthias; Yamamoto, Kentaro – ETS Research Report Series, 2012
This document describes a solution to a problem in the automatic content scoring of the multilingual character-by-character highlighting item type. This solution is language independent and represents a significant enhancement. This solution not only facilitates automatic scoring but plays an important role in clustering students' responses;…
Descriptors: Scoring, Multilingualism, Test Items, Role
Zafra, Amelia; Ventura, Sebastian – International Working Group on Educational Data Mining, 2009
The ability to predict a student's performance could be useful in a great number of different ways associated with university-level learning. In this paper, a grammar guided genetic programming algorithm, G3P-MI, has been applied to predict if the student will fail or pass a certain course and identifies activities to promote learning in a…
Descriptors: Foreign Countries, Programming, Academic Achievement, Grades (Scholastic)