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Record W1859793159 · doi:10.21432/t2q889

Seeking Information for School Purposes on the Internet

2003· article· en· W1859793159 on OpenAlexvenueaboutno aff
Holly Gunn, Gary Hepburn

Bibliographic record

VenueCanadian Journal of Learning and Technology · 2003
Typearticle
Languageen
FieldSocial Sciences
TopicLibrary Science and Information Literacy
Canadian institutionsnot available
Fundersnot available
KeywordsThe InternetNova scotiaInformation seekingPsychologyCurriculumInternet researchPerceptionPublic relationsMedical educationPolitical scienceWorld Wide WebPedagogySociologyComputer scienceLibrary scienceMedicine

Abstract

fetched live from OpenAlex

This paper reports the findings of a study undertaken in four Nova Scotia public schools of twelfth grade students' information seeking strategies when they use the Internet as an information source. Various Nova Scotia Department of Education curriculum documents hold high expectations of students' information seeking strategies when using the Internet for educational purposes. This study looks at whether these expectations are being realized. The results include the students' use of specific information seeking strategies, knowledge of World Wide Web Search engines, as well as how students acquired their Internet information seeking knowledge, and students' perceptions of their ability to locate information on the Internet. The results of the study have important implications for Internet education and the role of information professionals in public schools.

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)0.001
metaresearch head score (Gemma)0.004
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.103
Threshold uncertainty score0.204

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.010
GPT teacher head0.241
Teacher spread0.231 · 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

Citations14
Published2003
Admission routes2
Has abstractyes

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