MétaCan
Menu
Back to cohort
Record W2505275903 · doi:10.5539/ies.v9n8p19

Investigating University Students’ Preferences to Science Communication Skills: A Case of Prospective Science Teacher in Indonesia

2016· article· en· W2505275903 on OpenAlexvenueno aff
Nadi Suprapto, Chih-Hsiung Ku

Bibliographic record

VenueInternational Education Studies · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsCronbach's alphaPsychologyIndonesianMathematics educationExploratory factor analysisPreferencePedagogyDevelopmental psychologyPsychometricsMathematics

Abstract

fetched live from OpenAlex

<p class="apa">The purpose of this study was to investigate Indonesian university students’ preferences to science communication skills. Data collected from 251 students who were majoring in science education program. The Learning Preferences to Science Communication (LPSC) questionnaire was developed with Indonesian language and validated through an exploratory factor analysis (EFA) of participants’ responses. The differences between student levels were also explored for their significance using ANOVA test in order to draw a clear line among different learning preferences. The results indicated that, <em>first</em>, the instrument used in this study had satisfactory in validity and reliability. The construct validities of the LPSC were vary from .48 and .83 and explained 64.54% of the variance. Overall, the Cronbach alpha coefficient of the instrument was .91. <em>Second</em>, university students as prospective teacher in junior and freshman level performed higher preference in visual (V) and aural (A) than others. Moreover, senior student depicted higher confident in read or write (R/W) than junior and sophomore level. However, university student in sophomore level performed less confident in both visual and aural. <em>Third</em>, the results also showed the significant intra-relationships among dimensions of learning preferences. The implications delineated contribute to the improvement of science teacher education program in Indonesia.</p>

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)0.002
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.117
Threshold uncertainty score0.858

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.002
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 head0.062
GPT teacher head0.441
Teacher spread0.379 · 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 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

Citations8
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueInternational Education StudiesSame topicEducation and Critical Thinking DevelopmentFrench-language works237,207