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Vitale, Jonathan M.; Lai, Kevin; Linn, Marcia C. – Journal of Research in Science Teaching, 2015
We present a new system for automated scoring of graph construction items that address complex science concepts, feature qualitative prompts, and support a range of possible solutions. This system utilizes analysis of spatial features (e.g., slope of a line) to evaluate potential student ideas represented within graphs. Student ideas are then…
Descriptors: Scoring, Graphs, Scientific Concepts, Prompting
Kai, Shiming; Paquette, Luc; Baker, Ryan S.; Bosch, Nigel; D'Mello, Sidney; Ocumpaugh, Jaclyn; Shute, Valerie; Ventura, Matthew – International Educational Data Mining Society, 2015
Increased attention to the relationships between affect and learning has led to the development of machine-learned models that are able to identify students' affective states in computerized learning environments. Data for these affect detectors have been collected from multiple modalities including physical sensors, dialogue logs, and logs of…
Descriptors: Video Technology, Interaction, Physics, Affective Behavior
Fulmer, Gavin W.; Liang, Ling L.; Liu, Xiufeng – International Journal of Science Education, 2014
This exploratory study applied a proposed force and motion learning progression (LP) to high-school and university students and to content involving both one- and two-dimensional force and motion situations. The Force Concept Inventory (FCI) was adapted, based on a previous content analysis and coding of the questions in the FCI in terms of the…
Descriptors: Secondary School Science, High School Students, College Science, College Students