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Record W7055882724

Educational Television in Canada – A Case Study of Instructional Television at Carleton University and the Independent Learning
\nCentre of TV, Ontario

2003· article· en· W7055882724 on OpenAlexaboutno aff

Bibliographic record

VenueMyPrints@UOM (Mysore University Library) · 2003
Typearticle
Languageen
FieldEngineering
TopicParticle accelerators and beam dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsEducational televisionFlexibility (engineering)Interactive televisionDistance educationCable televisionChannel (broadcasting)Intervention (counseling)Period (music)Core (optical fiber)
DOInot available

Abstract

fetched live from OpenAlex

The intervention of technology in education besides enhancing learning experience has also solved many shortcomings of traditional method of teaching. This paper examines the initiative of Carleton University, Canada to use instructional television- ITV to support open learning and conventional classroom teaching. In this interactive learning system students are provided with an option to take ITV as well as on campus courses as core and elective subjects. The course content, credit and method of teaching are the full equivalent of courses offered on-campus. There is a greater degree of flexibility in the courses. The students residing in Ottawa can gain access to televised course through cable ITV 65, which is an independent cable channel transmitted from ITV centre of Carleton University. There is ‘tapes-to-you-service’ offered to enrolled students who do not have access to the local cable channel. The course lecture tapes are loaned to students for a specified period of time each semester.

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)0.003
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: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.112
Threshold uncertainty score0.810

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.006
Science and technology studies0.0310.005
Scholarly communication0.0040.001
Open science0.0020.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0060.000

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 head0.004
GPT teacher head0.147
Teacher spread0.143 · 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

Citations0
Published2003
Admission routes1
Has abstractyes

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