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Aprendizagem ativa em ótica geométrica: experimentos e demonstrações investigativas

2009· dissertation· pt· W1535707231 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typedissertation
Languagept
FieldSocial Sciences
TopicScience and Education Research
Canadian institutionsDiscovery Air (Canada)
Fundersnot available
KeywordsComprehensionMathematics educationProcess (computing)Field (mathematics)Computer sciencePsychologyMathematics

Abstract

fetched live from OpenAlex

There is nowadays consensus among the physics education researchers that the traditional teaching methods are not the most effective in promoting real engagement of the students in the teaching/learning process. Several researchers named Active Learning (AL), methods that require this engagement and research evidences indicate that this approach is the most effective, a better comprehension of the basic physics concepts is verified. However, particularly in Brazil, there are few didactic materials available using AL approaches. This works aims to fulfill this need in the field of Geometrical Optics, offering a series of tutorials (guides) for experiments and interactive demonstrations. These tutorials are based in the idea of guided investigation where the students previous beliefs are exposed and confronted with the scientific concepts. This material was applied to high school students (in public schools) and college students (science teacher preparation course of IFSC). In order to evaluate this material, written tests were performed as well as observation of classrooms.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.341
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0020.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0100.002

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 head0.102
GPT teacher head0.433
Teacher spread0.331 · 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

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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