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Record W2104214874 · doi:10.5539/ies.v6n4p236

What Do Children Learn at Swedish Preschools?

2013· article· en· W2104214874 on OpenAlexvenueno aff
Lisbeth Lindström

Bibliographic record

VenueInternational Education Studies · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEarly Childhood Education and Development
Canadian institutionsnot available
Fundersnot available
KeywordsInclusion (mineral)PerceptionPsychologyCitizenshipPreschool educationPedagogyCitizenship educationEntrepreneurshipDevelopmental psychologyMathematics educationSocial psychologyPolitical science

Abstract

fetched live from OpenAlex

The purposes of this research are, first, to make visible, examine, and illuminate preschool teachers’ perception of what children enrolled in preschools learn and how they learn it; and second, to highlight and illuminate what abilities preschool teachers perceive that children can develop during their stay at preschools. As a theoretical framework, theories of entrepreneurship education and citizenship education are used. The research was conducted using a questionnaire sent out to thirteen local municipalities in the county of Norrbotten in the north of Sweden. The results showed a thoroughgoing positive response from the respondents to almost all of the statements presented in the questionnaire. The positive responses that the preschool teachers and other staff gave to the statements in the questionnaire can be an important platform for the development of active citizenship, although these positive responses still need to be critically analysed and further investigated.Based on the research results, it is argued that the relationship between entrepreneurship education and citizenship education is a close one and that it is possible for one to lend itself to the other and strengthen the development of individual´s skills for inclusion in society from very early ages.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.003

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 head0.033
GPT teacher head0.382
Teacher spread0.349 · 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; both teacher heads agree on what is shown here.

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

Citations11
Published2013
Admission routes1
Has abstractyes

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