Student Awareness and Use of Rubrics in Online Classes
Bibliographic record
Abstract
The design, development and deployment of online instruction has become standard practice. The focus of the study was on student perceptions of course rubrics and not on the rubrics, themselves, or the instructors. In order to improve student engagement online we conducted an exploratory study of the awareness and perceptions of course rubrics. Fifty graduate students completed an online survey at the end of the semester about their awareness and perceptions of course rubrics. All students reported that they were aware that course rubrics existed. They indicated that they had learned about this information through the course syllabus, professor announcements via email and posts to LMS. Most students reported reviewing rubrics prior to submitting an assignment. One of the key findings from this study was that students see rubrics as a mechanism for scaffolding their performance, and thus, instructors need to focus more effort on designing rubrics to accomplish more than student assessment.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".