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Record W2260791554

Using the Internet to Enhance Course Presentation: A Help or Hindrance to Student Learning

2014· article· en· W2260791554 on OpenAlexaff
William J. Wellington, David Hutchinson, A. J. Faria

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsThe InternetAttendancePresentation (obstetrics)PopulationBusinessMarketingPublic relationsEngineeringAdvertisingSociologyWorld Wide WebPolitical scienceComputer scienceEconomic growthMedicineEconomics
DOInot available

Abstract

fetched live from OpenAlex

ABSTRACT By the mid-1990s, the Internet came to be recognized as a powerful business tool. Publications began to emerge on building Websites. Today, the Internet is the world’s fastest growing communication technology. There are currently nearly 500 million Internet users worldwide with the greatest number of users in North America, Europe and the Asia/Pacific region. Internet penetration is well over 60 percent of the population in these areas (Lamb, Hair, McDaniel and Faria 2002).

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)0.005
metaresearch head score (Gemma)0.027
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.024
Threshold uncertainty score0.081

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.027
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0080.005
Open science0.0010.003
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0240.008

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 head0.037
GPT teacher head0.438
Teacher spread0.400 · 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 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

Citations11
Published2014
Admission routes1
Has abstractyes

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