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David Broska; Michael Howes; Austin van Loon – Sociological Methods & Research, 2025
Large language models (LLMs) provide cost-effective but possibly inaccurate predictions of human behavior. Despite growing evidence that predicted and observed behavior are often not "interchangeable," there is limited guidance on using LLMs to obtain valid estimates of causal effects and other parameters. We argue that LLM predictions…
Descriptors: Artificial Intelligence, Observation, Prediction, Correlation
Jeremy L. Hsu; Sara Gartland; Joelle Prate; Charles Hohensee – CBE - Life Sciences Education, 2025
Quantitative reasoning (QR) is a key skill for undergraduate biology education. Despite this, many students struggle with QR. Here, we use the theoretical framework of student noticing to investigate why some students struggle with QR in introductory biology labs. Under this framework, what students notice when given new information and data…
Descriptors: Thinking Skills, Numeracy, Introductory Courses, Biology
Lyrica Lucas; Anum Khushal; Robert Mayes; Brian A. Couch; Joseph Dauer – International Journal of Science Education, 2025
Educational reform priorities such as emphasis on quantitative modelling (QM) have positioned undergraduate biology instructors as designers of QM experiences to engage students in authentic science practices that support the development of data-driven and evidence-based reasoning. Yet, little is known about how biology instructors adapt to the…
Descriptors: Undergraduate Students, College Science, Biology, Classroom Observation Techniques