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Record W2521213183 · doi:10.5539/ijel.v6n5p43

The Implementation of Mother Tongue-Based Multilingual Education: Seeing It from the Stakeholders’ Perspective

2016· article· en· W2521213183 on OpenAlexvenueno aff
John N. Cabansag

Bibliographic record

VenueInternational Journal of English Linguistics · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMultilingual Education and Policy
Canadian institutionsnot available
Fundersnot available
KeywordsGrassrootsGovernment (linguistics)Perspective (graphical)Local governmentOrder (exchange)First languageICTSPolitical sciencePsychologyPublic relationsSociologyBusinessMedicinePublic administrationComputer scienceInformation and Communications Technology

Abstract

fetched live from OpenAlex

<p>Mother Tongue Based-Multilingual Education (MTB-MLE) has carved its niche as a practical and effective approach in the educational landscape. It offers a plausible framework for preparing coming generations to become better adaptive and even rich contributors in the globalized and intercultural world. The gate to the new millennium has brought great zeal in and at the same time contestations around this educational alternative.</p><p>This study examined the stakeholders’ perspective on the implementation of MTB-MLE as a pedagogical approach. The stakeholders’ perspective were explored and analyzed through the results of the different focus group discussions among teachers, pupils, parents, local school board, parents-teachers and community association, non-government organization and local government unit.</p><p>Results from this study indicate four main benefits of MTB-MLE, namely: expressing better ideas, building self-confidence, better retention, and promoting friendly environment.</p><p>Meanwhile, the challenges which hinder the implementation of MTB-MLE are grouped into four significant themes: multilingual environment, difficulty in translation, inadequacy of instructional materials, and mandatory compliance to the Department of Education (DepEd) order.</p><p>The significance of the results of this study points out important actions the program can benefit Filipino pupils. Notably, a system that emanated from the higher authorities in which grassroots sector were not consulted, the Department of Education (DepEd) order should be executed by an interface between the higher level management and the local stakeholders. Involving them can undoubtedly contribute in the success of MTB-MLE.</p>

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)0.067
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.763
Threshold uncertainty score0.941

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.067
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.077
GPT teacher head0.465
Teacher spread0.388 · 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.

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

Citations22
Published2016
Admission routes1
Has abstractyes

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