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Record W2146836334 · doi:10.5032/jae.2005.04002

Trends In Learner Characteristics And Program Related Experiences Associated With Two Off-Campus Agriculture Degree Programs

2005· article· en· W2146836334 on OpenAlexaboutno aff
Gregory J. Miller, W. Wade Miller

Bibliographic record

VenueJournal of Agricultural Education · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicDiverse Educational Innovations Studies
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Medical educationPsychologyAgricultureGeographyMedicine

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score0.238

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.027
GPT teacher head0.277
Teacher spread0.249 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2005
Admission routes1
Has abstractyes

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