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Alex Lyman; Bryce Hepner; Lisa P. Argyle; Ethan C. Busby; Joshua R. Gubler; David Wingate – Sociological Methods & Research, 2025
Generative artificial intelligence (AI) has the potential to revolutionize social science research. However, researchers face the difficult challenge of choosing a specific AI model, often without social science-specific guidance. To demonstrate the importance of this choice, we present an evaluation of the effect of alignment, or human-driven…
Descriptors: Artificial Intelligence, Computer Simulation, Open Source Technology, Social Science Research
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Tina Law; Elizabeth Roberto – Sociological Methods & Research, 2025
Although there is growing social science research examining how generative AI models can be effectively and systematically applied to text-based tasks, whether and how these models can be used to analyze images remain open questions. In this article, we introduce a framework for analyzing images with generative multimodal models, which consists of…
Descriptors: Artificial Intelligence, Visual Aids, Open Source Technology, Social Science Research
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Nga Than; Leanne Fan; Tina Law; Laura K. Nelson; Leslie McCall – Sociological Methods & Research, 2025
Over the past decade, social scientists have adapted computational methods for qualitative text analysis, with the hope that they can match the accuracy and reliability of hand coding. The emergence of GPT and open-source generative large language models (LLMs) has transformed this process by shifting from programming to engaging with models using…
Descriptors: Artificial Intelligence, Coding, Qualitative Research, Cues
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Oscar Stuhler; Cat Dang Ton; Etienne Ollion – Sociological Methods & Research, 2025
Generative AI (GenAI) is quickly becoming a valuable tool for sociological research. Already, sociologists employ GenAI for tasks like classifying text and simulating human agents. We point to another major use case: the extraction of structured information from unstructured text. Information Extraction (IE) is an established branch of Natural…
Descriptors: Artificial Intelligence, Sociology, Social Science Research, Natural Language Processing
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SeHee Jung; Hanwen Wang; Bingyi Su; Lu Lu; Liwei Qing; Xiaolei Fang; Xu Xu – TechTrends: Linking Research and Practice to Improve Learning, 2025
This study presents a mobile application (app) that facilitates undergraduate students to learn data science using their own full-body motion data. The app captures a user's movements through the built-in camera of a mobile device and processes the images for data generation using BlazePose, an open-source computer vision model for real-time pose…
Descriptors: Undergraduate Students, Data Science, Handheld Devices, Open Source Technology
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Sarah Peterson; Don Finn – Active Learning in Higher Education, 2025
In higher education, a primary concern with online learning versus in-person learning centers on offering and facilitating effective communication and collaboration opportunities for students. New technologies, specifically free and open source system (FOSS) applications, help bridge these gaps by giving instructors and students the means to…
Descriptors: Learning Management Systems, Open Source Technology, Adoption (Ideas), Educational Resources
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Ludmila Walaszczyk; Sylvester Arnab – Electronic Journal of e-Learning, 2025
In the current educational environment, e-learning and online education have gained significant prominence, especially highlighted during the COVID-19 pandemic when their importance increased dramatically. Empirical evidence highlights the undeniable benefits of online learning, with learners globally appreciating the flexibility to access course…
Descriptors: Open Source Technology, Gamification, Usability, Electronic Learning
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Manuel T. Rein; Jeroen K. Vermunt; Kim De Roover; Leonie V. D. E. Vogelsmeier – Structural Equation Modeling: A Multidisciplinary Journal, 2025
Researchers often study dynamic processes of latent variables in everyday life, such as the interplay of positive and negative affect over time. An intuitive approach is to first estimate the measurement model of the latent variables, then compute factor scores, and finally use these factor scores as observed scores in vector autoregressive…
Descriptors: Measurement Techniques, Factor Analysis, Scores, Validity
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Emine Turhal; Oktay Bektas – International Journal of Education in Mathematics, Science and Technology, 2025
This research will analyze the issues encountered by two science teachers implementing Arduino-based robotic coding projects. This research employed a case study design. This research has used a criterion sampling group. This study used semi-structured observation, interviews, and video observations as data collection tools. The teachers conducted…
Descriptors: Science Teachers, Teacher Attitudes, Science Instruction, Robotics
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Devika Venugopalan; Ziwen Yan; Conrad Borchers; Jionghao Lin; Vincent Aleven – Grantee Submission, 2025
Caregivers (i.e., parents and members of a child's caring community) are underappreciated stakeholders in learning analytics. Although caregiver involvement can enhance student academic outcomes, many obstacles hinder involvement, most notably knowledge gaps with respect to modern school curricula. An emerging topic of interest in learning…
Descriptors: Homework, Computational Linguistics, Teaching Methods, Learning Analytics
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C. Sean Burns; Jennifer Pusateri; Daniela K. DiGiacomo – Journal of Education for Library and Information Science, 2025
This paper presents a novel approach to designing an online, open-source course in systems librarianship, an area of librarianship that may be perceived as complex and intimidating because of the technologies involved. The course design focuses on making systems librarianship more approachable for library and information science students who may…
Descriptors: Library Science, Online Courses, Open Education, Instructional Design