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Showing 1 to 15 of 46 results Save | Export
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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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Siqi Yi; Soo Young Rieh – Information and Learning Sciences, 2025
Purpose: This paper aims to critically review the intersection of searching and learning among children in the context of voice-based conversational agents (VCAs). This study presents the opportunities and challenges around reconfiguring current VCAs for children to facilitate human learning, generate diverse data to empower VCAs, and assess…
Descriptors: Literature Reviews, Children, Childrens Attitudes, Artificial Intelligence
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Jionghao Lin; Wei Tan; Lan Du; Wray Buntine; David Lang; Dragan Gasevic; Guanliang Chen – IEEE Transactions on Learning Technologies, 2024
Automating the classification of instructional strategies from a large-scale online tutorial dialogue corpus is indispensable to the design of dialogue-based intelligent tutoring systems. Despite many existing studies employing supervised machine learning (ML) models to automate the classification process, they concluded that building a…
Descriptors: Classification, Dialogs (Language), Teaching Methods, Computer Assisted Instruction
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Jie Zhang – International Journal of Information and Communication Technology Education, 2024
This paper explores the development of an intelligent translation system for spoken English using Recurrent Neural Network (RNN) models. The fundamental principles of RNNs and their advantages in processing sequential data, particularly in handling time-dependent natural language data, are discussed. The methodology for constructing the…
Descriptors: Oral Language, Translation, Computational Linguistics, Computer Software
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Ardeshir Geranpayeh – Language Teaching Research Quarterly, 2023
The recent surge in the popularity of Large Language Models (LLM) for language assessment underscores the growing significance of cost-effective language evaluation in our increasingly digitalized society. This paper posits that the application of computational psychometrics can enable the incorporation of technology into language assessment,…
Descriptors: Computational Linguistics, Psychometrics, Second Language Learning, Second Language Instruction
C. M. Downey – ProQuest LLC, 2024
Advances in Natural Language Processing (NLP) over the past decade have largely been driven by the scale of data and computation used to train large neural network-based models. However, these techniques are inapplicable to the vast majority of the world's languages, which lack the vast digitized text datasets available for English and a few other…
Descriptors: Multilingualism, Natural Language Processing, Transfer of Training, Second Language Learning
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Chia-Ju Lin; Wei-Sheng Wang; Hsin-Yu Lee; Yueh-Min Huang; Ting-Ting Wu – Journal of Educational Computing Research, 2025
This study uses a quasi-experimental design to explore the role of natural language processing (NLP) and speech recognition technologies in supporting teacher interventions during collaborative STEM activities. The Speech Recognition Keywords Analysis System (SRKAS) was developed to extract keywords from student discussions, enabling real-time…
Descriptors: Natural Language Processing, Computational Linguistics, Technology Uses in Education, STEM Education
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Hosseini, Mohammad; Resnik, David B.; Holmes, Kristi – Research Ethics, 2023
In this article, we discuss ethical issues related to using and disclosing artificial intelligence (AI) tools, such as ChatGPT and other systems based on large language models (LLMs), to write or edit scholarly manuscripts. Some journals, such as "Science," have banned the use of LLMs because of the ethical problems they raise concerning…
Descriptors: Ethics, Artificial Intelligence, Computational Linguistics, Natural Language Processing
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Priti Oli; Rabin Banjade; Jeevan Chapagain; Vasile Rus – Grantee Submission, 2023
This paper systematically explores how Large Language Models (LLMs) generate explanations of code examples of the type used in intro-to-programming courses. As we show, the nature of code explanations generated by LLMs varies considerably based on the wording of the prompt, the target code examples being explained, the programming language, the…
Descriptors: Computational Linguistics, Programming, Computer Science Education, Programming Languages
Renu Balyan; Danielle S. McNamara; Scott A. Crossley; William Brown; Andrew J. Karter; Dean Schillinger – Grantee Submission, 2022
Online patient portals that facilitate communication between patient and provider can improve patients' medication adherence and health outcomes. The effectiveness of such web-based communication measures can be influenced by the health literacy (HL) of a patient. In the context of diabetes, low HL is associated with severe hypoglycemia and high…
Descriptors: Computational Linguistics, Patients, Physicians, Information Security
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Margaret A.L. Blackie – Teaching in Higher Education, 2024
Large language models such as ChatGPT can be seen as a major threat to reliable assessment in higher education. In this point of departure, I argue that these tools are a major game changer for society at large. Many of the jobs we now consider highly skilled are based on pattern recognition that can much more reliably be carried by fine-tuned…
Descriptors: Artificial Intelligence, Synchronous Communication, Science and Society, Evaluation
Abt Associates, 2022
Internet search engines have empowered citizens in their quest for seeking insights on a multitude of issues. Knowledge curation and evidence review requires systematic and rigorous fact-finding, baseline subject matter expertise, and the right tool to work at scale. Finding and summarizing knowledge has a direct impact on the research and…
Descriptors: Automation, Knowledge Management, Natural Language Processing, Bibliometrics
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Yishen Song; Qianta Zhu; Huaibo Wang; Qinhua Zheng – IEEE Transactions on Learning Technologies, 2024
Manually scoring and revising student essays has long been a time-consuming task for educators. With the rise of natural language processing techniques, automated essay scoring (AES) and automated essay revising (AER) have emerged to alleviate this burden. However, current AES and AER models require large amounts of training data and lack…
Descriptors: Scoring, Essays, Writing Evaluation, Computer Software
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Chenghao Wang; Xueyun Li – International Journal of Computer-Assisted Language Learning and Teaching, 2025
D-ID Creative Reality Studio (D-ID) is a platform for creating Artificial Intelligence (AI) presenter (digital human) videos, translating videos, and designing conversational agents. D-ID seamlessly integrates deep-learning face animation technology, large language models (LLMs), natural language processing (NLP), and speech synthesis and…
Descriptors: Artificial Intelligence, Design, Video Technology, Animation
Danielle S. McNamara; Tracy Arner; Reese Butterfuss; Debshila Basu Mallick; Andrew S. Lan; Rod D. Roscoe; Henry L. Roediger; Richard G. Baraniuk – Grantee Submission, 2022
The learning sciences inherently involve interdisciplinary research with an overarching objective of advancing theories of learning and to inform the design and implementation of effective instructional methods and learning technologies. In these endeavors, learning sciences encompass diverse constructs, measures, processes, and outcomes…
Descriptors: Artificial Intelligence, Learning Processes, Learning Motivation, Educational Research
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