The VIRI (Virtual, Interactive, Real-Time, Instructor-Led) Classroom: The Impact of Blended Synchronous Online Courses on Student Performance, Engagement, and Satisfaction
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Previous research on blended course offerings focuses on the addition of asynchronous online content to an existing course. While some explore synchronous communication, few control for differences between treatment groups. This study investigates the impact of teaching a blended course, using a virtual, interactive, real-time, instructor-led (VIRI) classroom, on student engagement, performance, and satisfaction. We use an experimental design with both a control group and a treatment group. Up to 90 students in a large urban university are randomly assigned by the registrar into two sections of an introductory marketing course. Using a pre- and post-semester questionnaire, the study measures student engagement, performance, and satisfaction. There are no statistical differences in student performance between the control and treatment groups. The only student engagement factor with a statistically significant difference between groups is student interest in their courses. Compared with the control group, the treatment group appears to be more interested (+10%) in their courses at the end of the semester. Finally, fewer than 2 in 10 students express dissatisfaction with their participation in a VIRI course. Blended course offerings are increasing in importance in marketing and business education. The study provides guidance for fine-tuning the features of those course offerings by demonstrating how a VIRI classroom leverages the capabilities of technology without compromising learning outcomes.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it