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Record W2125955908

Capturing Urban Middle School Students' Voices on the Use of Science Inquiry in their Classrooms

2009· article· en· W2125955908 on OpenAlexvenueno aff
Irene U. Osisioma, Chidiebere R. Onyia

Bibliographic record

VenueInternational Education Studies · 2009
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsLikert scalePerceptionPsychologyMathematics educationDispositionMiddle levelRelevance (law)Science educationSurvey researchPedagogyKnowledge levelSocial psychologyApplied psychologyDevelopmental psychology
DOInot available

Abstract

fetched live from OpenAlex

The present study seeks to explore middle school students’ perception of the kind of science instruction going on in their classrooms and its relevance to their daily lives outside the classroom. Data were collected using a five point Likert type survey instrument that was administered to 262 middle school (Grades 6, 7& 8) students in six middle schools in Southern California. This instrument consisted of demographic information and thirty six statements organized in clusters to elicit responses on a number of statements about students’ 1) their emotional disposition toward science, 2) perception of and understanding of the usefulness of science, and 3) emotional disposition towards science inquiry and their perceptions of their teacher’s use of inquiry-based instruction in their classrooms. Results revealed that generally, students’ percentage responses were low for all the three research questions even though they were high for specific survey statements for the three clusters of survey statements. Suggestions were made for future research on the topic.

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)0.006
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.143
Threshold uncertainty score0.666

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.370
GPT teacher head0.498
Teacher spread0.128 · 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.

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

Citations1
Published2009
Admission routes1
Has abstractyes

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