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Implications of Bias in Automated Writing Quality Scores for Fair and Equitable Assessment Decisions
Michael Matta; Sterett H. Mercer; Milena A. Keller-Margulis – Grantee Submission, 2023
Recent advances in automated writing evaluation have enabled educators to use automated writing quality scores to improve assessment feasibility. However, there has been limited investigation of bias for automated writing quality scores with students from diverse racial or ethnic backgrounds. The use of biased scores could contribute to…
Descriptors: Bias, Automation, Writing Evaluation, Scoring
Kent, Shawn C.; Wanzek, Jeanne; Yun, Joonmo – Grantee Submission, 2019
This study examined the predictive validity and classification accuracy of individual and group-administered screening measures relative to student performance on a year-end state reading assessment in two states. A sample of 321 students were assessed in the areas of word-level and text fluency, as well as reading comprehension in the fall of…
Descriptors: Screening Tests, Grade 4, Elementary School Students, At Risk Students
Olsen, Jennifer K.; Aleven, Vincent; Rummel, Nikol – Grantee Submission, 2015
Student models for adaptive systems may not model collaborative learning optimally. Past research has either focused on modeling individual learning or for collaboration, has focused on group dynamics or group processes without predicting learning. In the current paper, we adjust the Additive Factors Model (AFM), a standard logistic regression…
Descriptors: Educational Environment, Predictive Measurement, Predictor Variables, Cooperative Learning