ArticleCBE life sciences education2021
Comparison of Cluster Analysis Methodologies for Characterization of Classroom Observation Protocol for Undergraduate STEM (COPUS) Data.
Article in CBE life sciences education, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
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Who cites it
8 citing papers in PubMed, 25 citations in OpenAlex.
- Exploring the Complementarity of Measures of Instructional Practices.CBE life sciences education · 2023Article
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- Participation and Performance by Gender in Synchronous Online Lectures: Three Unique Case Studies during Emergency Remote Teaching.Journal of microbiology & biology education · 2022Article
- Predicting implementation of active learning by tenure-track teaching faculty using robust cluster analysis.International journal of STEM education · 2022Article
- Brief Training and Intensive Mentoring Guide Postdoctoral Scholars to Student-Centered Instruction.CBE life sciences education · 2021Article
- Look Who's Talking: Teaching and Discourse Practices across Discipline, Position, Experience, and Class Size in STEM College Classrooms.Bioscience · 2021Article
- Are Faculty Changing? How Reform Frameworks, Sampling Intensities, and Instrument Measures Impact Inferences about Student-Centered Teaching Practices.CBE life sciences education · 2021Article
- Instructor facilitation mediates students' negative perceptions of active learning instruction.PloS one · 2021Article
Corrections and comments
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The Classroom Observation Protocol for Undergraduate STEM (COPUS) provides descriptive feedback to instructors by capturing student and instructor behaviors occurring in the classroom. Due to the increasing prevalence of COPUS data collection, it is important to recognize how researchers determine whether groups of courses or instructors have unique classroom characteristics. One approach uses cluster analysis, highlighted by a recently developed tool, the COPUS Analyzer, that enables the characterization of COPUS data into one of seven clusters representing three groups of instructional styles (didactic, interactive, and student centered). Here, we examine a novel 250 course data set and present evidence that a predictive cluster analysis tool may not be appropriate for analyzing COPUS data. We perform a de novo cluster analysis and compare results with the COPUS Analyzer output and identify several contrasting outcomes regarding course characterizations. Additionally, we present two ensemble clustering algorithms: 1)
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.