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Showing 1 to 15 of 24 results Save | Export
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Patrícia Takaki; Moisés Lima Dutra – Education and Information Technologies, 2024
Much of the data produced and consumed by students, teachers, and educational managers is in textual format. Text Mining (TM) and Natural Language Processing (NLP) have been applied in the educational context in different ways. Ideally, such applications combine computational, linguistic, pedagogical, and psychological aspects. This article aims…
Descriptors: Literature Reviews, Higher Education, Distance Education, Content Analysis
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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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Dania Bilal; Li-Min Cassandra Huang – Information and Learning Sciences, 2025
Purpose: This paper aims to investigate user voice-switching behavior in voice assistants (VAs), embodiments and perceived trust in information accuracy, usefulness and intelligence. The authors addressed four research questions: RQ1. What is the nature of users' voice-switching behavior in VAs? RQ2: What are user preferences for embodied voice…
Descriptors: Undergraduate Students, Artificial Intelligence, Natural Language Processing, Information Retrieval
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Pedro Isaias; Tania Hoque; Paula Miranda – International Association for Development of the Information Society, 2024
While the higher education sector is continuously searching for innovative technologies, the use of chatbots requires extensive research and careful consideration of their pedagogical value. The lessons learned from lecturers who experiment with chatbots can constitute important evidence to support their use. This paper presents a chatbot…
Descriptors: Instructional Material Evaluation, Artificial Intelligence, Technology Uses in Education, Natural Language Processing
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Laeeq, Kashif; Memon, Zulfiqar Ali – Interactive Learning Environments, 2021
The existing Learning Management Systems (LMSs) are profoundly effective in empowering the organization of e-learning, however, lacking in usability and learnability. The complex navigation and an immature search system are catalysing the issues that needs vigorous improvement. This paper aims to enhance the usability of LMSs by introducing an…
Descriptors: Integrated Learning Systems, Artificial Intelligence, Natural Language Processing, Information Retrieval
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Ghadeer Sawalha; Imran Taj; Abdulhadi Shoufan – Cogent Education, 2024
Large language models present new opportunities for teaching and learning. The response accuracy of these models, however, is believed to depend on the prompt quality which can be a challenge for students. In this study, we aimed to explore how undergraduate students use ChatGPT for problem-solving, what prompting strategies they develop, the link…
Descriptors: Cues, Artificial Intelligence, Natural Language Processing, Technology Uses in Education
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Yi-Ping Wu; Hui-Hsien Feng; Bo-Ren Mau – Interpreter and Translator Trainer, 2025
Corpus analysis methods have been widely employed in literary translation research by numerous scholars. However, their integration into literary translation training has yet to be developed. With the advancement of AI technology, this paper explores the potential of employing AI-enhanced corpus text analysis and text mining techniques in this…
Descriptors: Translation, Computer Software, Comparative Analysis, Language Styles
Olney, Andrew M. – Grantee Submission, 2021
In contrast to simple feedback, which provides students with the correct answer, elaborated feedback provides an explanation of the correct answer with respect to the student's error. Elaborated feedback is thus a challenge for AI in education systems because it requires dynamic explanations, which traditionally require logical reasoning and…
Descriptors: Feedback (Response), Error Patterns, Artificial Intelligence, Test Format
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Wonkyung Choi; Jun Jo; Geraldine Torrisi-Steele – International Journal of Adult Education and Technology, 2024
Despite best efforts, the student experience remains poorly understood. One under-explored approach to understanding the student experience is the use of big data analytics. The reported study is a work in progress aimed at exploring the value of big data methods for understanding the student experience. A big data analysis of an open dataset of…
Descriptors: College Students, Data Analysis, Data Collection, Learning Analytics
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Lang, David; Wang, Alex; Dalal, Nathan; Paepcke, Andreas; Stevens, Mitchell L. – AERA Open, 2022
Committing to a major is a fateful step in an undergraduate education, yet the relationship between courses taken early in an academic career and ultimate major issuance remains little studied at scale. Using transcript data capturing the academic careers of 26,892 undergraduates enrolled at a private university between 2000 and 2020, we describe…
Descriptors: Undergraduate Students, Majors (Students), College Planning, Natural Language Processing
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Kappagantula, Sri Rama Kartheek; Adamo-Villani, Nicoletta; Wu, Meng-Lin; Popescu, Voicu – IEEE Transactions on Learning Technologies, 2020
We present a system that automatically generates deictic gestures for animated pedagogical agents (APAs). The system takes audio and text as input, which define what the APA has to say, and generates animated gestures based on a set of rules. The automatically generated gestures point to the exact locations of elements on a whiteboard nearby the…
Descriptors: Animation, Nonverbal Communication, Lecture Method, Video Technology
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Machado, Crystiano José Richard; Maciel, Alexandre Magno Andrade; Rodrigues, Rodrigo Lins – International Journal of Distance Education Technologies, 2019
Discussion forums in learning management systems (LMS) have been shown to promote student interaction and contribute to the collaborative practice in the teaching-learning process. By evaluating the postings, teachers can identify students with learning difficulties. However, due to the large volume of posts that are generated on a daily basis in…
Descriptors: Discussion Groups, Integrated Learning Systems, Learning Problems, Content Analysis
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Cleary, Anne M.; Claxton, Alexander B. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2015
This study shows that the presence of a tip-of-the-tongue (TOT) state--the sense that a word is in memory when its retrieval fails--is used as a heuristic for inferring that an inaccessible word has characteristics that are consistent with greater word perceptibility. When reporting a TOT state, people judged an unretrieved word as more likely to…
Descriptors: Recall (Psychology), Heuristics, Metacognition, Memory
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Sathick, Javubar; Venkat, Jaya – International Review of Research in Open and Distributed Learning, 2015
Mining social web data is a challenging task and finding user interest for personalized and non-personalized recommendation systems is another important task. Knowledge sharing among web users has become crucial in determining usage of web data and personalizing content in various social websites as per the user's wish. This paper aims to design a…
Descriptors: Web Sites, Social Networks, Information Retrieval, Knowledge Management
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Ezen-Can, Aysu; Boyer, Kristy Elizabeth – Journal of Educational Data Mining, 2015
Within the landscape of educational data, textual natural language is an increasingly vast source of learning-centered interactions. In natural language dialogue, student contributions hold important information about knowledge and goals. Automatically modeling the dialogue act of these student utterances is crucial for scaling natural language…
Descriptors: Classification, Dialogs (Language), Computational Linguistics, Information Retrieval
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