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Record W3184634832 · doi:10.3968/12069

The Effects of Communication Technology on Education

2021· article· en· W3184634832 on OpenAlexvenueno aff
Amna Bulhoon

Bibliographic record

VenueCross-cultural communication · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicOnline and Blended Learning
Canadian institutionsnot available
Fundersnot available
KeywordsTechnological determinismTechnology educationInformation and Communications TechnologySocioeconomic statusDeterminismInformation technologyHuman lifeEngineering ethicsSociologyPublic relationsKnowledge managementEngineeringComputer scienceSocial sciencePolitical sciencePedagogyEpistemology

Abstract

fetched live from OpenAlex

The 21st century is known as the era of technology development and it covered human life. Technology makes human life easier and becomes an integral part of the day to day life. Technology is a tool for communication and information which was used all over the world and makes life more convenient for everyone. Technology advancement makes our life simpler and fast. Communication technology is important for the development of a nation or a society because it’s a way to communicate between individuals or a group of people. This researcher paper defines the role and effects of communication technology in education. The researcher applied the knowledge gap and theory determinism theory which describes that students having better socio-economic status use communication technology in education as compared to the student having low socioeconomic status. The review literature analysis identifies the role and effects of communication technology in education. Communication technology is developing our society and education but it also impacts our physical abilities. Technology is a core element of the world but individuals know how to use these technologies effectively.

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)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.057

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.002
Scholarly communication0.0050.003
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0170.001

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 head0.015
GPT teacher head0.385
Teacher spread0.370 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2021
Admission routes1
Has abstractyes

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