NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Ames, Allison; Myers, Aaron – Educational Measurement: Issues and Practice, 2019
Drawing valid inferences from modern measurement models is contingent upon a good fit of the data to the model. Violations of model-data fit have numerous consequences, limiting the usefulness and applicability of the model. As Bayesian estimation is becoming more common, understanding the Bayesian approaches for evaluating model-data fit models…
Descriptors: Bayesian Statistics, Psychometrics, Models, Predictive Measurement
Peer reviewed Peer reviewed
Direct linkDirect link
Zagallo, Patricia; Meddleton, Shanice; Bolger, Molly S. – CBE - Life Sciences Education, 2016
We present our design for a cell biology course to integrate content with scientific practices, specifically data interpretation and model-based reasoning. A 2-year research project within this course allowed us to understand how students interpret authentic biological data in this setting. Through analysis of written work, we measured the extent…
Descriptors: Undergraduate Students, Science Education, Cytology, Instructional Design
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Andrade, Alejandro; Delandshere, Ginette; Danish, Joshua A. – Journal of Learning Analytics, 2016
One of the challenges many learning scientists face is the laborious task of coding large amounts of video data and consistently identifying social actions, which is time consuming and difficult to accomplish in a systematic and consistent manner. It is easier to catalog observable behaviours (e.g., body motions or gaze) without explicitly…
Descriptors: Student Behavior, Data Analysis, Models, Video Technology
Peer reviewed Peer reviewed
Direct linkDirect link
Wurtz, Keith – Journal of Applied Research in the Community College, 2008
The purpose of this article is to provide the necessary tools for institutional researchers to conduct a logistic regression analysis and interpret the results. Aspects of the logistic regression procedure that are necessary to evaluate models are presented and discussed with an emphasis on cutoff values and choosing the appropriate number of…
Descriptors: Regression (Statistics), Predictor Variables, Educational Background, Grades (Scholastic)