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Pooja G. Sidney; Julie F. Shirah; Lauren Zahrn; Clarissa A. Thompson – Grantee Submission, 2022
In mathematics, learners often spontaneously draw on prior knowledge when learning new ideas. In this study, we examined whether the specific diagrams used to represent more familiar (i.e., whole number division) and less familiar ideas (i.e., fraction division) shape successful transfer. Undergraduates (N = 177) were randomly assigned to…
Descriptors: Mathematics Education, Prior Learning, Transfer of Training, Visual Aids
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2023
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction; and…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
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Hardcastle, Joseph; Herrmann Abell, Cari; DeBoer, George – Grantee Submission, 2019
Students' ability to explain phenomena were compared when they were provided a model versus asked to draw their own model. As part of a pilot test, 1,405 students in the fourth through twelfth grades from across the United States responded to one of three different modeling tasks. Each task presented students with a phenomenon related to energy…
Descriptors: Elementary School Students, Energy, Concept Formation, Freehand Drawing
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2022
This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Booth, Julie L.; McGinn, Kelly M.; Young, Laura K.; Barbieri, Christina – Grantee Submission, 2015
Findings from the fields of cognitive science and cognitive development propose a variety of evidence-based principles for improving learning. One such recommendation is that instead of having students practice solving long strings of problems on their own after a lesson, worked-out examples of problem solutions should be incorporated into…
Descriptors: STEM Education, Problem Solving, Models, Textbooks
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Johannes, Kristen; Powers, Jacklyn; Couper, Lisa; Silberglitt, Matt; Davenport, Jodi – Grantee Submission, 2016
Can novel 3D models help students develop a deeper understanding of core concepts in molecular biology? We adapted 3D molecular models, developed by scientists, for use in high school science classrooms. The models accurately represent the structural and functional properties of complex DNA and Virus molecules, and provide visual and haptic…
Descriptors: Molecular Biology, Science Instruction, Teacher Role, Scientific Concepts