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Record W1481895794 · doi:10.18297/etd/2264

Distance education policy : a study of the SREB faculty support policy construct at four virtual college and university consortia.

2009· dissertation· en· W1481895794 on OpenAlexfundno aff
Kathleen Mackenzie

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
FundersUniversidad del AtlánticoUniversity of TampaSt. Thomas UniversityFlorida Institute of TechnologyRollins CollegeNova Southeastern UniversityUniversity of Miami
KeywordsConstruct (python library)Public relationsHigher educationPolitical scienceKnowledge managementMathematics educationPsychologyComputer science

Abstract

fetched live from OpenAlex

The present study has a three pronged purpose: one, describe how the faculty support policy construct developed by the Southern Regional Education Board (SREB) exists at four Virtual Colleges and Universities Consortia (VCU). Two, describe how VCUs degree of centralization and emphasis on business practices influences the faculty support policy construct of their respective sampled institutions. Three, search for patterns in policy characteristics across the same four VCUs accounting for their degree of centralization and emphasis on business practices. The study is among the first in-depth qualitative studies to apply SREB's faculty support policy construct to representative VCUs of the Epper and Garn taxonomy, delve into specific details of the faculty support policy construct proposed by SREB, and search for policy patterns among representative VCUs selected for the study. The study provides much needed insight that is currently missing from the literature and that should assist university leaders, policy makers, and faculty in the administration of day-to-day activities at Virtual Colleges and Universities Consortia or academic collaborations. The study design is a multiple-case study. The design facilitated obtaining better insight, description, and discovery of how the faculty support policy construct exists today at the selected VCUs, how the construct influences the operation of each VCU, and if patterns exist in faculty support characteristics among the four institutions. The design encouraged a high level and comprehensive understanding of the phenomenon under study, distance learning policy, and the development of general theoretical statements. Data gathering techniques were semi-structured phone interviews and document analysis. Study findings revealed that the SREB faculty support policy construct exists at the four sample institutions with very distinct levels of intensity. Findings also revealed that sampled VCUs degree of centralization and business practice influence some faculty support policies implemented at the sampled higher education institutions. Lastly, findings reveal that patterns exist across higher education institutions in terms of faculty support policies. While some patterns diverge from the Epper and Garn taxonomy most patterns are just expected and consistent across higher education institutions.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.017
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.115

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0170.032
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.004
Science and technology studies0.0090.005
Scholarly communication0.0060.004
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0020.000

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 head0.016
GPT teacher head0.337
Teacher spread0.321 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2009
Admission routes1
Has abstractyes

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