A Cost-Benefit Analysis of Teaching and Learning Technology in a Faculty of Pharmaceutical Sciences
Bibliographic record
Abstract
<b>Objective.</b> To conduct a cost-benefit analysis (CBA) of investment in teaching and learning technology (TLT) by a college of pharmacy in a large, research-intensive university in Canada. <b>Methods.</b> Document analysis was used to determine the goals and objectives of the university and college for TLT use. Semi-structured interviews were conducted with faculty members to understand their perspectives on the value of technology for teaching and learning, their metrics to assess value, and an estimate of social value using a willingness to pay (WTP) exercise. A CBA was used to compare the social value against the cost of the investment in TLT. <b>Results.</b> Twenty-one faculty members participated in semi-structured interviews. National, university, and college goals for TLT were diffuse and nonspecific in terms of the intended use or the metrics by which implementation and impacts on the quality of teaching could be assessed. The mean WTP for this technology was Can$4.38M and the cost of investment was Can$4.25M. The primary analysis showed a small positive net benefit of the investment (Can$134,456), although this difference was not significant. All dollar figures are given in Canadian dollars (CAD). <b>Conclusion.</b> The college’s monetary investment in TLT was approximately equal to the social value placed on TLT by faculty users. Conducting a CBA on technology can bring greater understanding among faculty members of the college’s curriculum and pedagogical practices as well as financial decision-making. Greater clarity about the goals and objectives for TLT could help to maximize the value of investment in this area.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".