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Record W6893306211 · doi:10.5281/zenodo.15173374

Effectiveness of Teachers' Training and Academic Performance of Learners

2025· article· en· W6893306211 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicTechnology-Enhanced Education Studies
Canadian institutionsnot available
Fundersnot available
KeywordsTraining (meteorology)Quarter (Canadian coin)Nonprobability samplingAcademic yearPublic universityDescriptive statistics

Abstract

fetched live from OpenAlex

Training equips teachers with pedagogical techniques, knowledge, classroom management skills, and new perspectives in facilitating and supporting pupils in the teaching-learning process. This study focused on the effectiveness of teachers' training and learners' academic performance in Libona District II public schools. The gender, age, and years of experience among the respondents were determined. The type and effectiveness of teachers’ training and the overall academic performance of learners in the second quarter were assessed, and significant differences were explored. One hundred three (103) regular permanent elementary teachers were respondents to the study through a purposive sampling. A descriptive method, with content analysis, was applied utilizing a survey to gather information and data. The study yielded the following findings: the majority of teachers were females with an age range of 36 to 45 years old and more than 10 years of experience; the teachers’ training was very high; and there was a very satisfactory academic performance of grades 4 to 6 learners. Significant differences between teachers’ years of experience, ages, training, and learners' academic performance were found. When teachers grow older, they become more efficient and supported with effective training. Teachers’ age, years of experience, and training were found to influence learners' academic performance. This study recommends having sustained training that enhances pedagogical skills which are tailored to the needs and interests of teachers for the learners.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.817
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.049
GPT teacher head0.333
Teacher spread0.284 · 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
Published2025
Admission routes1
Has abstractyes

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Same venueZenodo (CERN European Organization for Nuclear Research)Same topicTechnology-Enhanced Education StudiesFrench-language works237,207