MétaCan
Menu
Back to cohort
Record W3197269877

E- Education: A future trend in education

2019· article· en· W3197269877 on OpenAlexaboutno aff
Sonu Grewal

Bibliographic record

VenueInternational journal of applied research · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsAtmosphere (unit)Quarter (Canadian coin)Ideal (ethics)PedagogyPsychologySociologyMathematics educationPublic relationsPolitical scienceHistoryGeography
DOInot available

Abstract

fetched live from OpenAlex

In last quarter of the 20th century Science and Technology has triggered great changes in the world. Today we are living in the world of information revolution where the E-learning plays a fundamental role in creating an atmosphere of awareness among masses. E- Learning brings learning to people, not people to learning. The major focus of teacher education programme is to produce effective and ideal teachers who can mould future generations of the nation according to the goals and ambitions of society. It is necessary to bring a change in the viewpoint that teacher is to impart the knowledge and the textbooks are the sources of knowledge. Now, the teacher is to create an atmosphere through personal involvement and the importance of firsthand experience requires to be duly recognized. Electronic and web - learning are playing vital role to educational issues, educational policies and strategies relevant to education. E-learning is helpful in two ways – one, students can learn from E - learning, and second, they can give their views through E-media. The role of teacher education has never been limited to the acquisition of knowledge and the development of skills, but is also an important influence on the development of values.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.923
Threshold uncertainty score0.913

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.454
Teacher spread0.426 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

Explore more

Same venueInternational journal of applied researchSame topicOnline and Blended LearningFrench-language works237,207