Trends In Learner Characteristics And Program Related Experiences Associated With Two Off-Campus Agriculture Degree Programs
Bibliographic record
Abstract
Iowa State University began offering an off-campus master of agriculture (M.Ag.) degree in 1979 and an off-campus B.S. degree in 1991. The major for both degree programs is Professional Agriculture. In the fall of 1993, a follow-up study was conducted to evaluate the programs and to gain an understanding of the off-campus learning experience. Seven years later, another follow-up study was conducted. Data were obtained from 46 of 53 persons who graduated by fall 1993 and from 34 of 54 persons who graduated from spring 1994 to spring 2001. When compared to 1993 respondents, a smaller proportion of 2001 respondents were male and employed in farming. A greater proportion of 2001 respondents were employed in agribusiness and "other" occupations. Graduates in both follow-up studies took about five and three quarter years to complete their programs, but respondents in 2001 traveled to campus more often for reasons associated with their degree program. Year 2001 respondents perceived thirteen challenges to off-campus study as less significant than 1993 respondents. Respondents in 2001 perceived they had significantly greater access to instructors and that instructors understood their needs more than did respondents in 1993. The two most significant challenges faced by graduates in both studies were the limited number of course offerings and the difficulty in balancing school, personal, and work responsibilities.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".