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Record W2612699083 · doi:10.5539/jel.v6n3p299

Middle Grade Students’ Concept Images of Algebraic Concepts

2017· article· en· W2612699083 on OpenAlexvenueno aff
Reyhan Tekin-Sitrava

Bibliographic record

VenueJournal of Education and Learning · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicMathematics Education and Teaching Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationPerspective (graphical)Algebraic numberTerm (time)PsychologyConcept learningSampling (signal processing)Algebra over a fieldComputer scienceMathematicsArtificial intelligencePure mathematics

Abstract

fetched live from OpenAlex

This study investigates middle school students’ concept images of algebraic concepts which are term, constant term, variable, and coefficient. Also, the study aimed to explore their performances in defining these concepts correctly. A phenomenological method was used to support methodological perspective and to reveal the findings of the study. Twenty seven 7th grade students completed a questionnaire, which aims to assess students’ concept images of the algebraic concepts. Twelve of them were selected for semi-structured interviews on the basis of purposeful sampling method to clarify and expand on their responses to the questionnaire. The data was analyzed via the content analysis approach. The analysis of the data indicated that students have various concept images of basic algebraic concepts. More interestingly, this study showed that although students’ performances on defining the algebraic concepts were above 50% for each concept, 7th grade students’ concept images of the algebraic concepts is not so strong for learning algebra conceptually.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.331
Threshold uncertainty score0.492

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
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 head0.054
GPT teacher head0.445
Teacher spread0.391 · 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 designQualitative
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

Citations15
Published2017
Admission routes1
Has abstractyes

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