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Record W2802156632 · doi:10.19173/irrodl.v19i2.3460

Online Course Enrollment in Community College and Degree Completion: The Tipping Point

2018· article· en· W2802156632 on OpenAlexvenueno aff
Peter Shea, Temi Bidjerano

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsCourseworkCommunity collegeTipping point (physics)Medical educationPsychologyEducational attainmentDistance educationPopulationAcademic achievementQuality (philosophy)Mathematics educationLearning communityAt-risk studentsMedicineDemographySociologyPolitical scienceEngineering

Abstract

fetched live from OpenAlex

Recent research indicates that certain students are at risk of lower levels of academic performance in online settings when compared to peers who study only in the classroom. Community college students have been a population of particular concern. In this paper, we hypothesize that online course load and institutional quality may impact outcomes for such students at risk for lower levels of degree attainment. Using comprehensive data from the 30 community colleges (n=45,557) of the State University of New York (SUNY), we conducted a state-wide study to examine whether there is a “tipping point” at which online course load becomes problematic for community college learners seeking to attain a degree through a mix of online and face-to-face coursework. We also test the conjecture that some institutions may excel at supporting online learner success among more at risk populations who choose online study. Results indicate that community college students who take more than 40% of their courses online begin to lose the benefits of enhanced degree completion conferred through a mix of online and face-to-face enrollment. Moderating variables are also identified and discussed.

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)0.017
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.782

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0170.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.183
GPT teacher head0.500
Teacher spread0.317 · 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 designNot applicable
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

Citations40
Published2018
Admission routes1
Has abstractyes

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