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Showing 1 to 15 of 48 results Save | Export
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Gamze Türkmen – Journal of Educational Computing Research, 2025
Explainable Artificial Intelligence (XAI) refers to systems that make AI models more transparent, helping users understand how outputs are generated. XAI algorithms are considered valuable in educational research, supporting outcomes like student success, trust, and motivation. Their potential to enhance transparency and reliability in online…
Descriptors: Artificial Intelligence, Natural Language Processing, Trust (Psychology), Electronic Learning
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Behzad Mirzababaei; Viktoria Pammer-Schindler – IEEE Transactions on Learning Technologies, 2024
In this article, we investigate a systematic workflow that supports the learning engineering process of formulating the starting question for a conversational module based on existing learning materials, specifying the input that transformer-based language models need to function as classifiers, and specifying the adaptive dialogue structure,…
Descriptors: Learning Processes, Electronic Learning, Artificial Intelligence, Natural Language Processing
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Soomaiya Hamid; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
E-learning is the process of sharing knowledge out of the traditional classrooms through different online tools using internet. The availability and use of these tools are not easy for every student. Many institutions gather e-learning feedback to know the problems of students to improve their systems. In e-learning systems, typically a high…
Descriptors: Feedback (Response), Electronic Learning, Automation, Classification
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Mia Allen; Usman Naeem; Sukhpal Singh Gill – IEEE Transactions on Education, 2024
Contributions: In this article, a generative artificial intelligence (AI)-based Q&A system has been developed by integrating information retrieval and natural language processing techniques, using course materials as a knowledge base and facilitating real-time student interaction through a chat interface. Background: The rise of advanced AI…
Descriptors: Artificial Intelligence, Technology Uses in Education, Information Retrieval, Natural Language Processing
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Micheal M. van Wyk; Michael Agyemang Adarkwah; Samuel Amponsah – Open Praxis, 2023
The launch of ChatGPT has been revolutionary. This AI chatbot can produce conversations which are indistinguishable from that of humans. This exploratory qualitative study is foregrounded in a constructivist-interpretative perspective. The principal objective of this paper is to explore the views of academics on ChatGPT as an AI-based learning…
Descriptors: Artificial Intelligence, Natural Language Processing, Higher Education, Learning Strategies
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Mohammad Daneshvar Kakhki; Abdullah Oguz; Michael Gendron – Journal of Information Systems Education, 2024
This paper investigates the affordances of ChatGPT in higher education and examines how artificial intelligence (AI) technologies may reshape the learning function in higher education. This study utilizes a grounded theory approach to analyze data collected from six sessions of panel discussions with participants from US universities. The study…
Descriptors: Affordances, Educational Benefits, Technology Uses in Education, Educational Technology
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Aras Bozkurt; Ramesh C. Sharma – Asian Journal of Distance Education, 2024
This study explores the transformative potential of Generative AI (GenAI) and ChatBots in educational interaction, communication, and the broader implications of human-GenAI collaboration. By examining the related literature through data mining and analytical methods, the paper identifies three main research themes: the revolutionary role of…
Descriptors: Algorithms, Artificial Intelligence, Man Machine Systems, Technology Uses in Education
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Dorottya Demszky; Jing Liu; Heather C. Hill; Dan Jurafsky; Chris Piech – Educational Evaluation and Policy Analysis, 2024
Providing consistent, individualized feedback to teachers is essential for improving instruction but can be prohibitively resource-intensive in most educational contexts. We develop M-Powering Teachers, an automated tool based on natural language processing to give teachers feedback on their uptake of student contributions, a high-leverage…
Descriptors: Online Courses, Automation, Feedback (Response), Large Group Instruction
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Somers, Rick; Cunningham-Nelson, Samuel; Boles, Wageeh – Australasian Journal of Educational Technology, 2021
In this study, we applied natural language processing (NLP) techniques, within an educational environment, to evaluate their usefulness for automated assessment of students' conceptual understanding from their short answer responses. Assessing understanding provides insight into and feedback on students' conceptual understanding, which is often…
Descriptors: Natural Language Processing, Student Evaluation, Automation, Feedback (Response)
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Héctor J. Pijeira-Díaz; Shashank Subramanya; Janneke van de Pol; Anique de Bruin – Journal of Computer Assisted Learning, 2024
Background: When learning causal relations, completing causal diagrams enhances students' comprehension judgements to some extent. To potentially boost this effect, advances in natural language processing (NLP) enable real-time formative feedback based on the automated assessment of students' diagrams, which can involve the correctness of both the…
Descriptors: Learning Analytics, Automation, Student Evaluation, Causal Models
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Zheng, Lanqin; Long, Miaolang; Chen, Bodong; Fan, Yunchao – International Journal of Educational Technology in Higher Education, 2023
Online collaborative learning is implemented extensively in higher education. Nevertheless, it remains challenging to help learners achieve high-level group performance, knowledge elaboration, and socially shared regulation in online collaborative learning. To cope with these challenges, this study proposes and evaluates a novel automated…
Descriptors: Learning Analytics, Computer Assisted Testing, Cooperative Learning, Graphs
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Bünyami Kayali; Mehmet Yavuz; Sener Balat; Mücahit Çalisan – Australasian Journal of Educational Technology, 2023
The purpose of this study was to determine university students' experiences with the use of ChatGPT in online courses. The sample consisted of 84 associate degree students from a state university in Turkey. A multi-method approach was used in the study. Although quantitative data were collected using the Chatbot Usability Scale, qualitative data…
Descriptors: Student Experience, Artificial Intelligence, Natural Language Processing, Electronic Learning
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Prapasiri Klayklung; Piyawatjana Chocksathaporn; Pongsakorn Limna; Tanpat Kraiwanit; Kris Jangjarat – Online Submission, 2023
The development of conversational artificial intelligence (AI) has brought about new opportunities for improving the learning experience in education. ChatGPT, a large language model trained on a vast corpus of text, has the potential to revolutionize education by enhancing learning through personalized and interactive conversations. This paper…
Descriptors: Artificial Intelligence, Interaction, Foreign Countries, Technology Integration
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Alexander Stanoyevitch – Discover Education, 2024
Online education, while not a new phenomenon, underwent a monumental shift during the COVID-19 pandemic, pushing educators and students alike into the uncharted waters of full-time digital learning. With this shift came renewed concerns about the integrity of online assessments. Amidst a landscape rapidly being reshaped by online exam/homework…
Descriptors: Computer Assisted Testing, Student Evaluation, Artificial Intelligence, Electronic Learning
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Danielle S. McNamara; Tracy Arner; Elizabeth Reilley; Paul Alvarado; Chani Clark; Thomas Fikes; Annie Hale; Betheny Weigele – Grantee Submission, 2022
Accounting for complex interactions between contextual variables and learners' individual differences in aptitudes and background requires building the means to connect and access learner data at large scales, across time, and in multiple contexts. This paper describes the ASU Learning@Scale (L@S) project to develop a digital learning network…
Descriptors: Electronic Learning, Educational Technology, Networks, Learning Analytics
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