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Taylor V. Williams – ProQuest LLC, 2022
Clustering, a prevalent class of machine learning (ML) algorithms used in data mining and pattern-finding--has increasingly helped engineering education researchers and educators see and understand assessment patterns at scale. However, a challenge remains to make ML-enabled educational inferences that are useful and reliable for research or…
Descriptors: Multivariate Analysis, Data Analysis, Student Evaluation, Large Group Instruction
Clauser, Amanda L.; Keller, Lisa A.; Mcdermott, Kathryn A. – Journal of School Leadership, 2016
Increasing numbers of states have incorporated measures of students' academic growth into their data and accountability policies. Measuring growth is a statistically complicated task and complex growth measures can be easy to misinterpret. This paper reports on a survey of 317 Massachusetts principals' understanding of the Student Growth…
Descriptors: Principals, Data Use, Data Interpretation, Outcome Measures
Meyer, J. Patrick; Doromal, Justin B.; Wei, Xiaoxin; Zhu, Shi – Research in Higher Education, 2017
We developed a criterion-referenced student rating of instruction (SRI) to facilitate formative assessment of teaching. It involves four dimensions of teaching quality that are grounded in current instructional design principles: Organization and structure, Assessment and feedback, Personal interactions, and Academic rigor. Using item response…
Descriptors: Criterion Referenced Tests, Student Evaluation of Teacher Performance, Instructional Effectiveness, Course Evaluation