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Record W1530803324

Dynamic Computer Analogies and Conceptions of Chemical Equilibrium

2009· article· en· W1530803324 on OpenAlexaff
Vania Chan, Samia Khan

Bibliographic record

VenueDiscovery Research Portal (University of Dundee) · 2009
Typearticle
Languageen
FieldEngineering
TopicProcess Optimization and Integration
Canadian institutionsUniversity of British ColumbiaSimon Fraser University
Fundersnot available
KeywordsComputer scienceEpistemologyMathematical economicsMathematicsPhilosophy
DOInot available

Abstract

fetched live from OpenAlex

A computer simulation program that utilizes a dynamic analogy to represent Le Chatelier's Principle was studied to investigate how the analogy contributed to students' conceptions of chemical equilibrium. 46 Grade 12 Chemistry students interacted with the simulation and participated in 3 assessments. Statistical analysis of pre and posttests suggested that students strongly held a misconception that the non-favored reaction rate decreases when the favored reaction rate increases and the dynamic analogy of a weigh scale had the potential to reinforce the misconception. Analysis of molecular drawings revealed notable patterns in how the motion, distribution and ratio of molecules are perceived. Other findings on conceptual gains and the analogy are discussed. The implication of this study for educators and developers is that dynamic analogies can assist students, but limitations of the analogy should be discussed and cues in the simulation could assist with mappings to the target domain.

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)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.003
Scholarly communication0.0030.003
Open science0.0010.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.021
GPT teacher head0.270
Teacher spread0.248 · 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 designNot applicable
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
Published2009
Admission routes1
Has abstractyes

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