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Dazhen Tong; Yang Tao; Kangkang Zhang; Xinxin Dong; Yangyang Hu; Sudong Pan; Qiaoyi Liu – Asia Pacific Education Review, 2024
Artificial intelligence (AI) technologies have been consistently influencing the progress of education for an extended period, with its impact becoming more significant especially after the launch of ChatGPT-3.5 at the end of November 2022. In the field of physics education, recent research regarding the performance of ChatGPT-3.5 in solving…
Descriptors: Artificial Intelligence, Natural Language Processing, Technology Uses in Education, Performance
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Steven A. Stolz; Ali Lucas Winterburn; Edward Palmer – Educational Philosophy and Theory, 2024
The recent proliferation of Large Language Models (LLMs) raises questions as to the role of such tools both within an educational learning environment and their epistemic capacity. If, as Alfred North Whitehead remarked, western philosophy indeed 'consists of a series of footnotes to Plato', it would be of doubtless importance to evaluate the…
Descriptors: Artificial Intelligence, Technology Uses in Education, Natural Language Processing, Philosophy
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Ying Qian Ong; Jaehoon Lee; Shin Ying Chu; Siaw Chui Chai; Kok Beng Gan; Norlinah Mohamed Ibrahim; Steven M. Barlow – International Journal of Language & Communication Disorders, 2024
Background: Parkinson's disease (PD) has an impact on speech production, manifesting in various ways including alterations in voice quality, challenges in articulating sounds and a decrease in speech rate. Numerous investigations have been conducted to ascertain the oral-diadochokinesis (O-DDK) rate in individuals with PD. However, the existing…
Descriptors: Foreign Countries, Neurological Impairments, Speech Communication, Language Processing
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Kanwal Zahoor; Narmeen Zakaria Bawany – Interactive Learning Environments, 2024
Mobile application developers rely largely on user reviews for identifying issues in mobile applications and meeting the users' expectations. User reviews are unstructured, unorganized and very informal. Identifying and classifying issues by extracting required information from reviews is difficult due to a large number of reviews. To automate the…
Descriptors: Artificial Intelligence, Computer Oriented Programs, Courseware, Learning Processes
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Xiaopeng Zhang; Nan Gong – Studies in Second Language Acquisition, 2024
This study examined how linguistic complexity features contribute to second language (L2) processing effort by analyzing the Dutch English-L2 learners' eye movements from GECO and MECO, two eye-tracking corpora. Processing effort was operationalized as reading rate, mean fixation duration, regression rate, skipping rate, and mean saccade…
Descriptors: Second Language Learning, Linguistics, Language Processing, English (Second Language)
Nikki Robertson-Griffin – Knowledge Quest, 2024
Schools (and some librarians) relegated librarians to the "business of books" and disregarded them of proven technological expertise. Fortunately, school librarians have either continued to insert themselves into digital technologies or emerged from the stacks to reclaim their role as digital resource experts in their schools. So, how do…
Descriptors: School Libraries, Librarians, Social Media, Technological Literacy
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Jiaqi Yin; Tiong-Thye Goh; Yi Hu – International Journal of Educational Technology in Higher Education, 2024
Educational chatbots (EC) have shown their promise in providing instructional support. However, limited studies directly explored the impact of EC on learners' emotional responses. This study investigated the induced emotions from interacting with micro-learning EC and how they impact learning motivation. In this context, the EC interactions…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Psychological Patterns
Paiheng Xu; Jing Liu; Nathan Jones; Julie Cohen; Wei Ai – Annenberg Institute for School Reform at Brown University, 2024
Assessing instruction quality is a fundamental component of any improvement efforts in the education system. However, traditional manual assessments are expensive, subjective, and heavily dependent on observers' expertise and idiosyncratic factors, preventing teachers from getting timely and frequent feedback. Different from prior research that…
Descriptors: Educational Quality, Educational Assessment, Teacher Effectiveness, Natural Language Processing
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Rebeckah K. Fussell; Emily M. Stump; N. G. Holmes – Physical Review Physics Education Research, 2024
Physics education researchers are interested in using the tools of machine learning and natural language processing to make quantitative claims from natural language and text data, such as open-ended responses to survey questions. The aspiration is that this form of machine coding may be more efficient and consistent than human coding, allowing…
Descriptors: Physics, Educational Researchers, Artificial Intelligence, Natural Language Processing
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Michelle Pauley Murphy; Woei Hung – TechTrends: Linking Research and Practice to Improve Learning, 2024
Constructing a consensus problem space from extensive qualitative data for an ill-structured real-life problem and expressing the result to a broader audience is challenging. To effectively communicate a complex problem space, visualization of that problem space must elucidate inter-causal relationships among the problem variables. In this…
Descriptors: Information Retrieval, Data Analysis, Pattern Recognition, Artificial Intelligence
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Spyridoula Cheimariou; Laura M. Morett – Communication Disorders Quarterly, 2024
One of the basic tenets of predictive theories of language processing is that of misprediction cost. Post-N400 positive event-related potential (ERP) components are suitable for studying misprediction cost but are not adequately described, especially in older adults, who show attenuated N400 ERP effects. We report a secondary analysis of a…
Descriptors: Prediction, Costs, Older Adults, Aging (Individuals)
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Maira Klyshbekova; Pamela Abbott – Electronic Journal of e-Learning, 2024
There is a current debate about the extent to which ChatGPT, a natural language AI chatbot, can disrupt processes in higher education settings. The chatbot is capable of not only answering queries in a human-like way within seconds but can also provide long tracts of texts which can be in the form of essays, emails, and coding. In this study, in…
Descriptors: Artificial Intelligence, Higher Education, Technology Uses in Education, Evaluation Methods
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Jaeho Jeon; Seongyong Lee; Seongyune Choi – Interactive Learning Environments, 2024
Chatbot research has received growing attention due to the rapid diversification of chatbot technology, as demonstrated by the emergence of large language models (LLMs) and their integration with automatic speech recognition. However, among various chatbot types, speech-recognition chatbots have received limited attention in relevant research…
Descriptors: Literature Reviews, Content Analysis, Second Language Learning, Artificial Intelligence
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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
Lalitha Balachandran – ProQuest LLC, 2024
Segmentation is a cornerstone of language processing across levels of linguistic analysis, and yet, standard models of linguistic memory leave the role of higher-order segments in online comprehension understudied. This dissertation advances the Context-Sensitive Encoding (CSE) hypothesis: that implicit prosodic boundaries (Bader, 1998; J. Fodor,…
Descriptors: Memory, Cognitive Processes, Sentences, Reading Comprehension
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