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Record W1749176719 · doi:10.5539/ies.v8n10p163

Homeschool in Malaysia: A Foresight Study

2015· article· en· W1749176719 on OpenAlexvenueno aff
Ng Kim-Soon, Abd Rahman Ahmad, Muhammad Ibrahim Bin Sulaiman, Ng Mei Xin Sirisa

Bibliographic record

VenueInternational Education Studies · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicDiverse Education Studies and Reforms
Canadian institutionsnot available
FundersUniversiti Tun Hussein Onn Malaysia
KeywordsSyllabusMainstreamHome educationCurriculumChristian ministrySociologyPedagogyPsychologyMedical educationPolitical scienceMedicine

Abstract

fetched live from OpenAlex

Homeschooling in Malaysia is a form of alternative education that emphasizes quality education based on moral values and beliefs while strengthening family bonds. This alternative form of education is being practiced by a growing number of families in Malaysia. As such, the Ministry of Education has given the green light for intending parents who wish to homeschool their children to do so with prior permission from the Ministry. Local parents homeschool their children for various reasons. This study was undertaken to foresight the trends of parents who homeschool their children in Malaysia. A mixed approach was used in this study. The data collected was analyzed by using impact uncertainty analysis to foresight homeschool in Malaysia. Data was collected from 30 parents who homeschool in Malaysia and 4 of them were also interviewed. Parent left mainstream schooling is mainly due to inadequate curriculum or syllabus, social issues among students, an adverse school environment and conflicting values in the mainstream’s schools. The key drivers of homeschool in Malaysia are social issues among students and the education syllabus offered. This research work foresighted the drivers of homeschooling and provided possible scenarios of future of homeschool in Malaysia. Discussion and recommendations 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)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.037
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.003
Open science0.0000.001
Research integrity0.0000.001
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 head0.133
GPT teacher head0.462
Teacher spread0.329 · 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 designQualitative
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

Citations5
Published2015
Admission routes1
Has abstractyes

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