Mixed methods student evaluation of an online systemic human anatomy course with laboratory
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
A fully online section of an existing face-to-face (F2F) systemic human anatomy course with a prosection laboratory was offered for the first time in 2012-2013. Lectures for F2F students (N = 365) were broadcast in both live and archived format to online students (N = 40) using virtual classroom software. Laboratories were delivered online by a teaching assistant who manipulated 3D computer models in the virtual classroom environment. An exploratory sequential mixed methods approach was undertaken to determine the most important deciding factors that drive students' preferences for a given format and then to generate theory on the strengths and weaknesses of the online format. Students (20 online; 310 F2F) volunteered to participate in a crossover period of one week to expose them to the course section in which they were not originally registered. Open ended interviews (20 online; 20 F2F) and quantitative surveys (270 F2F) were conducted following a crossover. Students valued pace control, schedule, and location flexibility of learning from archived materials and being assessed online. In the online laboratory they had difficulty using the 3D models and preferred the unique and hands-on experiences of cadaveric specimens. The F2F environment was conducive to learning in both lecture and laboratory because students felt more engaged by instructors in person and were less distracted by their surroundings. These results suggest the need to improve the online experience by increasing the quality of student-instructor communication and in turn student-content interaction with the 3D models. Anat Sci Educ 9: 272-285. © 2015 American Association of Anatomists.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 it