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Davison, Mark L.; Davenport, Ernest C., Jr.; Jia, Hao; Seipel, Ben; Carlson, Sarah E. – Grantee Submission, 2022
A regression model of predictor trade-offs is described. Each regression parameter equals the expected change in Y obtained by trading 1 point from one predictor to a second predictor. The model applies to predictor variables that sum to a constant T for all observations; for example, proportions summing to T=1.0 or percentages summing to T=100…
Descriptors: Regression (Statistics), Prediction, Predictor Variables, Models
Botarleanu, Robert-Mihai; Dascalu, Mihai; Allen, Laura K.; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2022
Automated scoring of student language is a complex task that requires systems to emulate complex and multi-faceted human evaluation criteria. Summary scoring brings an additional layer of complexity to automated scoring because it involves two texts of differing lengths that must be compared. In this study, we present our approach to automate…
Descriptors: Automation, Scoring, Documentation, Likert Scales
Botarleanu, Robert-Mihai; Dascalu, Mihai; Watanabe, Micah; Crossley, Scott Andrew; McNamara, Danielle S. – Grantee Submission, 2022
Age of acquisition (AoA) is a measure of word complexity which refers to the age at which a word is typically learned. AoA measures have shown strong correlations with reading comprehension, lexical decision times, and writing quality. AoA scores based on both adult and child data have limitations that allow for error in measurement, and increase…
Descriptors: Age Differences, Vocabulary Development, Correlation, Reading Comprehension
Kathryn A. Tremblay; Katherine S. Binder; Scott P. Ardoin; Armani Talwar; Elizabeth L. Tighe – Grantee Submission, 2021
Background: Of the myriad of reading comprehension (RC) assessments used in schools, multiple-choice (MC) questions continue to be one of the most prevalent formats used by educators and researchers. Outcomes from RC assessments dictate many critical factors encountered during a student's academic career, and it is crucial that we gain a deeper…
Descriptors: Reading Strategies, Eye Movements, Expository Writing, Grade 3
Metcalfe, Janet – Grantee Submission, 2017
Although error avoidance during learning appears to be the rule in American classrooms, laboratory studies suggest that it may be a counterproductive strategy, at least for neurologically typical students. Experimental investigations indicate that errorful learning followed by corrective feedback is beneficial to learning. Interestingly, the…
Descriptors: Error Patterns, Error Correction, Feedback (Response), Educational Benefits
Hershkovitz, Arnon; Baker, Ryan S. J. d.; Gobert, Janice; Wixon, Michael; Sao Pedro, Michael – Grantee Submission, 2013
In recent years, an increasing number of analyses in Learning Analytics and Educational Data Mining (EDM) have adopted a "Discovery with Models" approach, where an existing model is used as a key component in a new EDM/analytics analysis. This article presents a theoretical discussion on the emergence of discovery with models, its…
Descriptors: Learning Analytics, Models, Learning Processes, Case Studies