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Record W1921770501 · doi:10.19173/irrodl.v1i2.18

Online Delivery of Programmes: A case study of IGNOU

2001· article· en· W1921770501 on OpenAlexvenueno aff
Ramesh C. Sharma

Bibliographic record

VenueThe International Review of Research in Open and Distributed Learning · 2001
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsDistance educationBachelorInformation technologySpace (punctuation)Engineering managementPublic relationsPolitical scienceComputer scienceSociologyPedagogyEngineering

Abstract

fetched live from OpenAlex

Online education is the most exciting segment in the Indian IT space. A host of e-education sites continue to enter the market with focused offerings, linking up students and teachers, almost on a daily basis. This is happening because the new medium seeks to supplement -- not replace -- traditional teaching-learning methodologies. Keeping in view the global and in country/domestic market changes, India has to play a vital role in terms of software exports, skilled manpower support, and online education. With India currently in the midst of a "dotcom" wave, Indira Ghandi National Open University (IGNOU) has taken the initiative in launching online in January 2000 two of its educational computer programmes. In July 2000 it launched twenty capsule courses (each comprising three courses) in different specialization areas of management [http://www.ignou.com/index.htm]. Each of these capsules addresses one specific functional or specialization area, one basic course pertaining to that specialization and a project course. The Bachelor of Information Technology and Advanced Diploma in Information Technology programmes are offered through a Virtual Campus Initiative (VCI). Management Programme capsule courses are offered through Project MEIDS (Management Education through Interactive Delivery Systems).

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)0.007
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.706
Threshold uncertainty score0.988

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.143
GPT teacher head0.511
Teacher spread0.368 · 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 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

Citations23
Published2001
Admission routes1
Has abstractyes

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