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Labor-Based Grading Contracts In The Multilingual Fyc Classroom: Unpacking The Variables, Kara Kristina Larson
Labor-Based Grading Contracts In The Multilingual Fyc Classroom: Unpacking The Variables, Kara Kristina Larson
USF Tampa Graduate Theses and Dissertations
This descriptive, exploratory study’s purpose is to determine the effects of labor-based grading contracts on students whose historical exclusion results in their current day underrepresentation in higher education. A key component of this study is the emphasis on the student’s own perceptions and feelings about the use of labor-based grading contracts. Using a purposive sample of multilingual First-Year Composition (FYC) sections at an R1 university, I investigated the variables of labor-based grading contracts: demographics and written language characteristics, student motivation, ecological variables (i.e., perceptions of grading contracts), and academic performance measures. Research questions include: 1) How do labor-based grading contracts …
Investigating The Fit Of The Generalized Graded Unfolding Model (Ggum) When Calibrated To Irt Generated Data From Dominance And Ideal Point Models, Abdulla Alzarouni
Investigating The Fit Of The Generalized Graded Unfolding Model (Ggum) When Calibrated To Irt Generated Data From Dominance And Ideal Point Models, Abdulla Alzarouni
College of Education and Human Sciences: Dissertations, Theses, and Student Research
The assessment of model fit in latent trait modelling, better known as item response theory (IRT), is an integral part of model testing if one is to make valid inferences about the estimated parameters and their properties based on the selected IRT model. Though important, the assessment of model fit has been less utilized in IRT research than it should. For example, there have been less research investigating fit for polytomous dominance models such the Graded Response Model (GRM), and to a lesser extent ideal point models such as the Generalized Graded Unfolding Models (GGUM), both in its dichotomous and …