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Mathematical Thinking: Teachers Perceptions and Students Performance

2011· article· en· W1848033462 on OpenAlexvenueno aff
Mamoon M. Mubark

Bibliographic record

VenueCanadian social science · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and Critical Thinking Development
Canadian institutionsnot available
Fundersnot available
KeywordsHumanitiesLogical reasoningMathematics educationComputer sciencePsychologyEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

This paper was investigated the teachers rating of the six different aspects of mathematical thinking developed by the researcher: Searching for patterns , Induction, Deduction, symbolism, Logical thinking and Mathematical proof in relation to level of importance, level of difficulty, and time spent in teaching each aspect. This paper was also aimed to examine any possible consistencies and inconsistencies between teacher opinions about the level of importance of mathematical thinking aspects to mathematics achievement, level of difficulty and test data collected. Also, it was examined if the students were familiar with solving specific problems (such as rice problem) logical ways like searching for patterns rather than more traditional approaches and if they also applying the fourth step in problem solving according to Polya, (1990) (i.e., looking back (a checking the answer)). Key words: Mathematical thinking; Teacher perceptions; Students performance Resume Ce document a etudie la notation des six aspects differents de la pensee mathematique des enseignants developpe par le chercheur: la recherche de modeles, a induction, deduction, le symbolisme, la pensee logique et mathematique la preuve par rapport au niveau d'importance, le niveau de difficulte et le temps passe dans l'enseignement de chaque aspect. Ce document visait egalement a examiner toute consistances et des incoherences eventuelles entre les opinions des enseignants sur le niveau d'importance des aspects la pensee mathematique a la reussite en mathematiques, niveau de difficulte et les donnees recueillies lors des essais. En outre, il a ete examine si les eleves ont ete familiarises avec la resolution de problemes specifiques (tels que les problemes du riz) facons logiques, tels que la recherche de modeles plutot que des approches plus traditionnelles, et si ils ont egalement l'application de la quatrieme etape dans la resolution de problemes en fonction de Polya, (1990) (a savoir, en regardant en arriere (une verification de la reponse)). Mots cles: Pensee mathematique; Les perceptions des enseignants et le rendement des etudiants

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)0.003
metaresearch head score (Gemma)0.013
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.049
GPT teacher head0.341
Teacher spread0.292 · 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".

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Citations1
Published2011
Admission routes1
Has abstractyes

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