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Profile of the prospective teachers response to the development of scientific communication skills through physics learning

2019· article· en· W2921840450 on OpenAlexaff
Edward Erwin, Nuryani Rustaman, Harry Firman, Taufik Ramlan Ramalis

Bibliographic record

VenueJournal of Physics Conference Series · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsEncana (Canada)
Fundersnot available
KeywordsMathematics educationPhysicsPsychology

Abstract

fetched live from OpenAlex

This article discusses the profiles of prospective physics teacher responses to the development of scientific communication skills through physics learning. Data were collected using questionnaires and interviews to strengthen the data obtained through questionnaires, data were analyzed descriptively. The results show that prospective physics teachers who have already joined the Teaching practice/Field Experience Program 2 (FEP 2) or who are currently following FEP 1, generally argues that the development of scientific communication skills can be conducted through subject matter learning, especially physics learning. Some prospective teachers give an anomalous response to some statements on the questionnaire, for example they agreed on the statement that the source of physics learning is sufficient from teacher's explanation, students do not need to read textbooks, not yet need to read scientific articles and scientific reports. Based on these findings prospective physics teachers should need to develop their's good understanding of the aspects to be learned in developing scientific communication skills, as well as their ability in transferring or developing scientific communication skill integrated within physics learning need to be assessed.

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)0.003
metaresearch head score (Gemma)0.001
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 score0.431
Threshold uncertainty score0.540

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 head0.052
GPT teacher head0.361
Teacher spread0.309 · 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

Citations3
Published2019
Admission routes1
Has abstractyes

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