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Amir Abdul Reda; Semuhi Sinanoglu; Mohamed Abdalla – Sociological Methods & Research, 2024
How can we measure the resource mobilization (RM) efforts of social movements on Twitter? In this article, we create the first ever measure of social movements' RM efforts on a social media platform. To this aim, we create a four-conditional lexicon that can parse through tweets and identify those concerned with RM. We also create a simple RM…
Descriptors: Social Media, Social Action, Natural Language Processing, Politics
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Xuelin Liu; Hua Zhang; Yue Cheng – International Journal of Web-Based Learning and Teaching Technologies, 2024
In this article, a dialogue text feature extraction model based on big data and machine learning is constructed, which transforms the high-dimensional space of text features into the low-dimensional space that is easy to process, so that the best feature words can be selected to represent the document set. Tests show that in most cases, the…
Descriptors: Artificial Intelligence, Data, Text Structure, Classification
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Amal Abdullah Alibrahim – South African Journal of Education, 2024
After ChatGPT was released late in 2022, many arguments about its accuracy and use in education arose. In this article, I seek to provide evidence of the accuracy and validity of ChatGPT's responses to users' queries in education by applying a systematic review methodology to analyse publications in specific databases following PRISMA guidelines…
Descriptors: Artificial Intelligence, Technology Uses in Education, Reliability, Natural Language Processing
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Salomé Do; Étienne Ollion; Rubing Shen – Sociological Methods & Research, 2024
The last decade witnessed a spectacular rise in the volume of available textual data. With this new abundance came the question of how to analyze it. In the social sciences, scholars mostly resorted to two well-established approaches, human annotation on sampled data on the one hand (either performed by the researcher, or outsourced to…
Descriptors: Computation, Social Sciences, Natural Language Processing, Artificial Intelligence
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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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Jian Liao; Linrong Zhong; Longting Zhe; Handan Xu; Ming Liu; Tao Xie – IEEE Transactions on Learning Technologies, 2024
ChatGPT has received considerable attention in education, particularly in programming education because of its capabilities in automated code generation and program repairing and scoring. However, few empirical studies have investigated the use of ChatGPT to customize a learning system for scaffolding students' computational thinking. Therefore,…
Descriptors: Scaffolding (Teaching Technique), Thinking Skills, Computation, Artificial Intelligence
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Funda Nayir; Tamer Sari; Aras Bozkurt – Journal of Educational Technology and Online Learning, 2024
From personalized advertising to economic forecasting, artificial intelligence (AI) is becoming an increasingly important element of our daily lives. These advancements raise concerns regarding the transhumanist perspective and associated discussions in the context of technology-human interaction, as well as the influence of artificial…
Descriptors: Artificial Intelligence, Technology Uses in Education, Humanism, Capacity Building
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Zhao Wanli; Tang Youjun; Ma Xiaomei – SAGE Open, 2025
Deeper learning (DL) is firmly rooted in learning science and computer science. However, a dearth of review studies has probed its trajectory in DL in foreign languages (DLFL). Utilizing SSCI from the Web of Science Core Collection, we employ Citespace and Vosviewer to analyze the scientific knowledge graph of DLFL literature. Our analysis…
Descriptors: Bibliometrics, Second Language Learning, Computer Science, Educational Research