The use of instructional technology in poultry science curricula in the United States and Canada: 2. Factors contributing to the use of instructional technology
Bibliographic record
Abstract
This paper describes a study conducted in recognition of the increasingly widespread use of computers and the importance of exposure to instructional technology (IT) in all aspects of the poultry science curriculum. The study consisted of the distribution and analysis of two cross-sectional surveys. One survey was sent to departments to obtain profiles of poultry science degree programs and the availability of IT and general support for its use. The second survey was sent to faculty to obtain individual profiles of IT use and of factors which may influence IT use. Herein are reported the results and analysis of those factors that are thought to contribute to or limit the diffusion of these media among poultry science faculty. Analysis consisted of descriptive statistics and contingency table comparisons using Likelihood Ratio chi-square. Factors that appear to be most important to faculty use of IT are availability of desired IT equipment, access to adequate expert assistance, availability of knowledgeable peers willing to share their experience and expertise, and exposure to concrete examples and ideas of how to use IT. All of these factors contribute to another important factor in participation and adoption: making it as easy as possible for faculty to learn and to use advanced IT methods.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.010 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".