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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
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
Sarah Levine; Sarah W. Beck; Chris Mah; Lena Phalen; Jaylen PIttman – Journal of Adolescent & Adult Literacy, 2025
Educators and researchers are interested in ways that ChatGPT and other generative AI tools might move beyond the role of "cheatbot" and become part of the network of resources students use for writing. We studied how high school students used ChatGPT as a writing support while writing arguments about topics like school mascots. We…
Descriptors: Natural Language Processing, Artificial Intelligence, Technology Uses in Education, Writing (Composition)
Yucheng Chu; Hang Li; Kaiqi Yang; Harry Shomer; Yasemin Copur-Gencturk; Leonora Kaldaras; Kevin Haudek; Joseph Krajcik; Namsoo Shin; Hui Liu; Jiliang Tang – International Educational Data Mining Society, 2025
Open-text responses provide researchers and educators with rich, nuanced insights that multiple-choice questions cannot capture. When reliably assessed, such responses have the potential to enhance teaching and learning. However, scaling and consistently capturing these nuances remain significant challenges, limiting the widespread use of…
Descriptors: Grading, Automation, Artificial Intelligence, Natural Language Processing
Gal Sasson Lazovsky; Tuval Raz; Yoed N. Kenett – Journal of Creative Behavior, 2025
As artificial intelligence and natural language processing methods rapidly develop, communication plays a pivotal role in every-day interactions. In this theoretical paper, we explore the overlap and commonalities between question-asking and prompt engineering. While seemingly distinct, these processes share a common foundation in essential skills…
Descriptors: Creativity, Questioning Techniques, Inquiry, Artificial Intelligence
Pablo Flores Romero; Kin Nok Nicholas Fung; Guang Rong; Benjamin Ultan Cowley – npj Science of Learning, 2025
Large Language Models (LLMs) present a radically new paradigm for the study of "information foraging behavior." We study how LLM technology is used for pedagogical content creation by a sample of 25 participants in a doctoral-level Artificial Intelligence (AI) in Education course, and the role of computational-thinking skills in shaping…
Descriptors: Man Machine Systems, Artificial Intelligence, Natural Language Processing, Interaction
Linh Huynh; Danielle S. McNamara – Grantee Submission, 2025
We conducted two experiments to assess the alignment between Generative AI (GenAI) text personalization and hypothetical readers' profiles. In Experiment 1, four LLMs (i.e., Claude 3.5 Sonnet; Llama; Gemini Pro 1.5; ChatGPT 4) were prompted to tailor 10 science texts (i.e., biology, chemistry, physics) to accommodate four different profiles…
Descriptors: Natural Language Processing, Profiles, Individual Differences, Semantics
Neil E. J. A. Bowen; Richard Watson Todd – Teaching English with Technology, 2025
An increasing number of studies have investigated how ChatGPT can aid in written assessment and feedback provision. However, many studies overlook its conversational design and underlying architecture, raising concerns about the reliability and validity of their analytical outputs. Therefore, applying first principles thinking to prompt use, and…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Cues
Andrew Runge; Sarah Goodwin; Yigal Attali; Mya Poe; Phoebe Mulcaire; Kai-Ling Lo; Geoffrey T. LaFlair – Language Testing, 2025
A longstanding criticism of traditional high-stakes writing assessments is their use of static prompts in which test takers compose a single text in response to a prompt. These static prompts do not allow measurement of the writing process. This paper describes the development and validation of an innovative interactive writing task. After the…
Descriptors: Material Development, Writing Evaluation, Writing Assignments, Writing Skills
Brendan Bartanen; Andrew Kwok; Andrew Avitabile; Brian Heseung Kim – Grantee Submission, 2025
Heightened concerns about the health of the teaching profession highlight the importance of studying the early teacher pipeline. This exploratory, descriptive article examines preservice teachers' expressed motivation for pursuing a teaching career. Using data from a large teacher education program in Texas, we use a natural language processing…
Descriptors: Career Choice, Teaching (Occupation), Teacher Education Programs, Preservice Teachers

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