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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
Lawrence Ibeh; Noah Cheruiyot Mutai; Olufunke Mercy Popoola; Nguyen Manh Cuong; Sandra Ejiofor – Research in Learning Technology, 2025
For this study, 350 university students in Germany were surveyed to understand how they perceive ChatGPT's educational advantages and challenges. Using a combination of quantitative and qualitative methods, it found out that students tend to see ChatGPT as helpful for academic performance (53.14%), writing (47.14%), and exam preparation (50.00%).…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Technology Uses in Education
Jussi S. Jauhiainen; Agustín Garagorry Guerra – Innovations in Education and Teaching International, 2025
The study highlights ChatGPT-4's potential in educational settings for the evaluation of university students' open-ended written examination responses. ChatGPT-4 evaluated 54 written responses, ranging from 24 to 256 words in English. It assessed each response using five criteria and assigned a grade on a six-point scale from fail to excellent,…
Descriptors: Artificial Intelligence, Technology Uses in Education, Student Evaluation, Writing Evaluation
Neil E. J. A. Bowen; Richard Watson Todd – Teaching English with Technology, 2025
An increasing number of studies have investigated how ChatGPT can aid in written assessment and feedback provision. However, many studies overlook its conversational design and underlying architecture, raising concerns about the reliability and validity of their analytical outputs. Therefore, applying first principles thinking to prompt use, and…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Cues
Hanadi Aldreabi; Nisreen Kareem Salama Dahdoul; Mohammad Alhur; Nidal Alzboun; Najeh Rajeh Alsalhi – Electronic Journal of e-Learning, 2025
The examination of the impact of Generative AI (GenAI) on higher education, especially from the viewpoint of students, is gaining significance. Although prior research has underscored GenAI's potential advantages in higher education, there exists a discernible research gap concerning the determinants that affect its adoption. In the present study,…
Descriptors: Student Behavior, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
Iria Estévez-Ayres; Patricia Callejo; Miguel Ángel Hombrados-Herrera; Carlos Alario-Hoyos; Carlos Delgado Kloos – International Journal of Artificial Intelligence in Education, 2025
The emergence of Large Language Models (LLMs) has marked a significant change in education. The appearance of these LLMs and their associated chatbots has yielded several advantages for both students and educators, including their use as teaching assistants for content creation or summarisation. This paper aims to evaluate the capacity of LLMs…
Descriptors: Artificial Intelligence, Natural Language Processing, Computer Mediated Communication, Technology Uses in Education
Hung Thanh Nguyen; Phuoc Tai Nguyen – Educational Process: International Journal, 2025
Background/purpose: Artificial intelligence, namely ChatGPT, has garnered significant interest in language education due to its potential to enhance instruction and learning. Three primary topics are highlighted in this study's analysis of recent research on ChatGPT's use in language instruction: Reflection on instruction, instructor feedback, and…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Language Teachers
Ursula Holzmann; Sulekha Anand; Alexander Y. Payumo – Advances in Physiology Education, 2025
Generative large language models (LLMs) like ChatGPT can quickly produce informative essays on various topics. However, the information generated cannot be fully trusted, as artificial intelligence (AI) can make factual mistakes. This poses challenges for using such tools in college classrooms. To address this, an adaptable assignment called the…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Thinking Skills
Ted M. Clark; Ellie Anderson; Nicole M. Dickson-Karn; Comelia Soltanirad; Nicolas Tafini – Journal of Chemical Education, 2023
Student performance on open-response calculations involving acid and base solutions before and after instruction in general chemistry and analytical chemistry courses was compared with the output from the artificial intelligence chatbot ChatGPT. Applying a theoretical model of expertise for problem solving that includes problem conceptualization,…
Descriptors: Academic Achievement, College Students, College Science, Chemistry
Xiaoling Bai; Nur Rasyidah Mohd Nordin – Eurasian Journal of Applied Linguistics, 2025
A perfect writing skill has been deemed instrumental to achieving competence in EFL, yet it is considered one of the most impressive learning domains. This study investigates the impact of human-AI collaborative feedback on the writing proficiency of EFL students. It examines key teaching domains, including the teaching environment, teacher…
Descriptors: Artificial Intelligence, Feedback (Response), Evaluators, Writing Skills
Qiao Wang; Ralph L. Rose; Ayaka Sugawara; Naho Orita – Vocabulary Learning and Instruction, 2025
VocQGen is an automated tool designed to generate multiple-choice cloze (MCC) questions for vocabulary assessment in second language learning contexts. It leverages several natural language processing (NLP) tools and OpenAI's GPT-4 model to produce MCC items quickly from user-specified word lists. To evaluate its effectiveness, we used the first…
Descriptors: Vocabulary Skills, Artificial Intelligence, Computer Software, Multiple Choice Tests
Rybinski, Krzysztof; Kopciuszewska, Elzbieta – Assessment & Evaluation in Higher Education, 2021
This article presents the first-ever big data study of the student evaluation of teaching (SET) using artificial intelligence (AI). We train natural language processing (NLP) models on 1.6 million student evaluations from the US and the UK. We address two research questions: (1) are these models able to predict student ratings from the student…
Descriptors: Artificial Intelligence, Technology Uses in Education, Student Evaluation of Teacher Performance, Natural Language Processing
Bosch, Nigel; Crues, R. Wes; Shaik, Najmuddin; Paquette, Luc – Grantee Submission, 2020
Online courses often include discussion forums, which provide a rich source of data to better understand and improve students' learning experiences. However, forum messages frequently contain private information that prevents researchers from analyzing these data. We present a method for discovering and redacting private information including…
Descriptors: Privacy, Discussion Groups, Asynchronous Communication, Methods
Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – Grantee Submission, 2017
This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…
Descriptors: Artificial Intelligence, Natural Language Processing, Reading Comprehension, Literature
Balyan, Renu; McCarthy, Kathryn S.; McNamara, Danielle S. – International Educational Data Mining Society, 2017
This study examined how machine learning and natural language processing (NLP) techniques can be leveraged to assess the interpretive behavior that is required for successful literary text comprehension. We compared the accuracy of seven different machine learning classification algorithms in predicting human ratings of student essays about…
Descriptors: Artificial Intelligence, Natural Language Processing, Reading Comprehension, Literature
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