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Record W1831519448 · doi:10.21083/ajote.v1i1.1576

Teachers’ Awareness of the Existence and the Use of Technology to Promote Children’s Literacy Instruction

2011· article· en· W1831519448 on OpenAlexvenueno aff
Ngozi Diwunma Obidike, Ngozi Anyikwa, Joy O Enemou

Bibliographic record

VenueAfrican Journal of Teacher Education · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Technology Integration
Canadian institutionsnot available
Fundersnot available
KeywordsSimple random sampleLiteracyMathematics educationGovernment (linguistics)Sample (material)School teachersData collectionPsychologyLocal government areaInformation literacyMedical educationLocal governmentPedagogyPolitical scienceSociologyMedicineSocial scienceEnvironmental health

Abstract

fetched live from OpenAlex

This paper examined the awareness of teachers of nursery and primary schools on the existence of the technological resources that could be used to support children's literacy instruction, as well as the use of such technological resources for enriching children's literacy instruction. The study was carried out in Awka Local Government Education Zone in Anambra State, Nigeria. Two (2) research questions guided the study. Five (500) nursery and primary school teachers were selected as the sample for the study using simple random sampling technique. Questionnaire was the instrument used for data collection which was analyzed using mean scores. The findings, among others, were that both the nursery and primary school teachers are able to identify the technological tools that could be used to enhance literacy instruction in children but are not aware of how such resources could be used. Suggestions for improvement were provided.

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)0.008
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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.040
GPT teacher head0.330
Teacher spread0.291 · 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

Citations7
Published2011
Admission routes1
Has abstractyes

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