Do Dissection‐ and Prosection‐based Laboratories Offer Comparable Learning Experiences? An Exploration of Student Learning in Two Laboratory Cohorts at the University of Guelph
Bibliographic record
Abstract
Historically, human anatomy has been taught using lectures and dissection‐based (DI) cadaver laboratories. However, many institutions face challenges such as limited financial resources, inadequate cadaver availability, and curricular time constraints that limit the use of DI laboratories. Consequently, prosection‐based (PRO) environments have been favoured as less resource‐intensive alternatives to DI. The benefits and drawbacks of using either DI or PRO have been debated for decades; however, since most institutions employ only one of these instructional environments, direct quantitative comparisons are rarely available. The University of Guelph offers a comprehensive human anatomy course in the third‐year of the Human Kinetics and Biomedical Science undergraduate degree programs that includes both DI and PRO cohorts. All students attend the same lectures and complete the same examinations, but are enrolled in either a DI or PRO laboratory. PRO students learn from the donors dissected by their DI peers, and therefore witness a ‘slow reveal’ of structures throughout the course. In the present study, course experience (CE), student approach to learning (SAL), and course performance, were compared between students enrolled in DI (n = 147) and PRO (n = 44). CE was measured using the course experience questionnaire (CEQ), preferred (p‐) and contextual (c‐) deep (DA) and surface (SA) learning approaches were measured using the revised two‐factor study process questionnaire (R‐SPQ‐2F), and grades on laboratory tests (LT), written tests (WT), and in‐laboratory oral assessments (LOA) were analyzed alongside final course grades as performance outcomes. No significant differences in scores on any CEQ subscale were found between students in DI or PRO ( p > 0.05). There was no significant main effect of laboratory type on SAL [ F (1,189) = 0.119, p = 0.731, partial η 2 = 0.001], but PRO students reported significantly lower cSA scores than pSA scores [ F (1,43) = 5.89, p = 0.020, partial η 2 = 0.120] and DI students had significantly higher cDA scores than pDA scores [ F (1,146) = 21.55, p < 0.0005, partial η 2 = 0.129]. Furthermore, the main effect of SAL type indicated that both groups adopted significantly higher DA scores than SA scores [DA = 34.95 ± 0.494, SA = 23.06 ± 0.480, F (1,189) = 181.54, p < 0.0005, partial η 2 = 0.490]. Multiple linear regression (MLR) analyses with demographic data, preferred SAL scores, and CEQ subscale scores as covariates revealed that although laboratory type did not significantly influence the prediction of cSA scores ( p = 0.413), participation in DI was positively associated with cDA score (β = 1.474 ± 0.724, p = 0.043). There were no significant differences in grades on LTs or WTs between DI and PRO students at p ≤ 0.05; however, DI students performed significantly better on LOAs than PRO students (DI = 91.96% ± 0.357, PRO = 87.09% ± 0.829, p < 0.0005) and had higher resulting final grades (β = 1.842 ± 0.885, p = 0.039). These findings suggest that DI and PRO laboratories both foster stronger DA than SA to learning, thus PRO may serve as an acceptable method of human anatomy instruction at institutions with limited resources. However, DI may better promote skills used in oral assessment such as communication, teamwork, and problem‐solving. This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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 | 0.001 | 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".