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Record W7034584402

Výuka hry geocaching v rámci volnočasových aktivit žáků na základních školách

2014· dissertation· en· W7034584402 on OpenAlexaboutno aff

Bibliographic record

VenueDigital Repository (National Repository of Grey Literature) · 2014
Typedissertation
Languageen
FieldSocial Sciences
TopicEducation, Innovation and Language Studies
Canadian institutionsnot available
Fundersnot available
KeywordsLeisure timeQuarter (Canadian coin)Sample (material)Intervention (counseling)Physical activitySpare timeDuration (music)Leisure activityWork (physics)School teachers
DOInot available

Abstract

fetched live from OpenAlex

Title: Teaching the game of geocaching as a leisure activity at elementary schools Objectives: The objective of this thesis is to promote the game of geocaching as an organised school activity for pupils of upper primary schools. To offer participants the activity they will learn to use in their free time. Methods: The research sample consisted of 32 students from upper primary schools in Prague 4 and Prague 9. There was a pedagogical worker in each group who was helping the students with four theoretical and practical lessons for one month. A questionnaire survey and interview with teachers were used as methods for obtaining data. The questionnaire was presented to the participants before the start of the project and then again one month after its completion. The interview with teachers was carried out only after the intervention. Results: The results of this thesis show that the project participants would like to participate in the game of geocaching in the future. Overall, about a quarter of those surveyed go in for geocaching in their free time, but only 6 % of them were devoted to it after the intervention. Due to the effect of the intervention programme, no demonstrable change of the measured values, obtained from the participants after the project completion, has occurred. Keywords: GPS,...

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.696
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0020.002
Open science0.0010.000
Research integrity0.0010.001
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 head0.011
GPT teacher head0.306
Teacher spread0.296 · 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
GenreOther

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
Published2014
Admission routes1
Has abstractyes

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