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Record W2947402112 · doi:10.5430/jct.v8n2p32

Utility of Metric Conversion for Success in Introductory College Science Courses

2019· article· en· W2947402112 on OpenAlexvenueno aff
Sonali Raje

Bibliographic record

VenueJournal of Curriculum and Teaching · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicScience Education and Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationMetric systemMetric (unit)Next Generation Science StandardsBridge (graph theory)Common coreComputer scienceCore (optical fiber)PsychologyScience educationEngineeringMedicine

Abstract

fetched live from OpenAlex

Cross-connections between the sciences and mathematics are emphasized through the Next Generation ScienceStandards and the Common Core State Standards in the United States. One topic that is a common bridge betweenmath and science is the concept of measurement and unit conversions in the metric/English system. This article usesa mixed-methods research design attempt to highlight the significance of this topic to demonstrate scientific literacyand for preparing students to be college ready. An analysis of content from college level introductory physicalscience textbooks, middle and high school math and science teacher surveys, clinical interviews and college studentsurveysare used to show how this critical concept may not be getting the attention it deserves in the US schoolsystems. Furthermore, the critical need to have specific questions related to this topic on standardized stateassessments has been suggested. The results indicate the need to reify this topic more extensively over the schoolyears, especially since the metric system of measurement is not a part of daily life in the United States.

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)0.007
metaresearch head score (Gemma)0.002
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 score0.243
Threshold uncertainty score0.234

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.025
GPT teacher head0.380
Teacher spread0.355 · 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

Citations4
Published2019
Admission routes1
Has abstractyes

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