One way to understand teaching is to view it as a people process rather than a presentation of knowledge. It follows that the role of an educator often extends beyond the primary subject matter and into the realm of classroom management. With this in mind, our research aimed to capture the various teaching practices, participation patterns, and communication climates that occur in virtual computer science classrooms. We sought to answer the following research questions related to virtual computer science classrooms at our institution: Who participates in virtual computer science classrooms, and is participation proportional to student demographics? Is there any correlation between the use of teaching best practices and student participation? Is there any correlation between communication climate and student participation?
To answer these questions, we designed and conducted a mixed-method content analysis study on 14 instructor-provided synchronous video lectures. We created a rubric composed of teaching best practices and supportive and defensive communication behaviors. The resulting design employed ethnographic content analysis (ECA) and quantitative content analysis (QCA) methodologies to produce contextually relevant knowledge. Correlational analysis was conducted using Kendall's tau-b correlational algorithm. Our findings suggest female participation was not proportional to student demographics, and no significant correlations between teaching practices and participation patterns were found. However, several significant correlations between communication climate and participation patterns were identified. Specifically, increased communication behaviors displaying equality were positively correlated with classroom dialogue count, unique female participants, female participation, and female first responses.
| Identifer | oai:union.ndltd.org:CALPOLY/oai:digitalcommons.calpoly.edu:theses-4190 |
| Date | 01 March 2022 |
| Creators | Krone, Jackie |
| Publisher | DigitalCommons@CalPoly |
| Source Sets | California Polytechnic State University |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Master's Theses |
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