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Record W6912811490 · doi:10.5281/zenodo.7246609

PARENTAL INVOLVEMENT IN MODULAR DISTANCE LEARNING AND THE HOLISTIC DEVELOPMENT OF KINDERGARTEN STUDENTS AMIDST THE PANDEMIC

2022· article· en· W6912811490 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicChild Development and Education
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)PerceptionDistance educationHolistic educationPandemicEducational attainment

Abstract

fetched live from OpenAlex

This study aimed to determine the significant relationship between the level of parental involvement in modular distance learning and kindergarten’s holistic development based on the perception of kindergarten parents amidst the pandemic. This research used descriptive correlational research with 150 selected Kindergarten parents in Bukal Sur Elementary School, Candelaria West District as respondents. It was conducted during the 4th quarter of SY 2021-2022. Results revealed that majority are married female, 30-34 years old, with high school background and below P5,000 income. They perceived parenting and learning at home very satisfactory, while collaborating, decision making, volunteering, and communicating are satisfactory. All indicators of holistic development including physical, intellectual, and emotional are very high. All variables of parental involvement are significantly interrelated to their physical, intellectual, and emotional development. When grouped according to age, sex, civil status, and monthly income, no significant differences were noted. Nevertheless, educational attainment of the respondents showed significant difference when used as a grouping factor.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.052
GPT teacher head0.306
Teacher spread0.254 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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