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Record W7005775458

Shifts in Students Attitudes toward an Integrated Math and Physics Curriculum

2015· article· en· W7005775458 on OpenAlexaboutno aff

Bibliographic record

VenueScholarship@Western (Western University) · 2015
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell Image Analysis Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumContext (archaeology)Physics educationPhysical scienceMathematical sciencesScience educationMathematics curriculumCalculus (dental)
DOInot available

Abstract

fetched live from OpenAlex

In September of 2012, the University of Guelph launched a new first year introductory math and physics course. The Integrated Physical Science (IPS) course was designed to replace the traditional first year calculus and physics courses. The intent was that combining these courses would allow learning across these two disciplines to be mutually supportive. The content typical of first-year physical and mathematical sciences is fully retained with the math enhanced in support of some physics topics. The integration of schedules allows for a just-in-time approach to the provision of necessary mathematical tools needed to solve problems in physics, while simultaneously providing context to the mathematical concepts. An attitudinal survey was conducted on two cohorts of students who have been through the IPS course and one cohort of students who went through a standard program of separate first year math and physics courses. The two IPS cohorts were compared to the non-IPS students to inquire as to whether groups had a significant difference in attitudes along several categories. The preliminary results show indications that IPS students have a more positive and sophisticated attitude towards their first year undergraduate experience. This initiative is an exciting opportunity to enhance first-year science education and growth within our existing programs.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.063
GPT teacher head0.346
Teacher spread0.283 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2015
Admission routes1
Has abstractyes

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