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Record W2295598272 · doi:10.5430/ijhe.v5n2p82

A Conceptual and Procedural Research on the Hierarchical Structure of Mathematics Emerging in the Minds of University Students: An Example of Limit-Continuity-Integral-Derivative

2016· article· en· W2295598272 on OpenAlexvenueno aff
Arif Dane, Ömer Faruk Çetin, Fatih Baş, Meryem Özturan Sağırlı

Bibliographic record

VenueInternational Journal of Higher Education · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicMathematics Education and Teaching Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPerspective (graphical)Limit (mathematics)Mathematics educationConceptual frameworkMathematicsPsychologyEpistemologyGeometry

Abstract

fetched live from OpenAlex

In this present study, it was aimed to investigate whether the hierarchical structure of mathematics emerged in university students’ minds or not, considering the concepts of limit, continuity derivative and integral from the perspective of students in the department of secondary school mathematics teacher training and the department of mathematics in the faculty of science and letters. The study, designed with the case study methodology, was carried out with 100 participants. Data were collected with the research group via a survey form including totally five questions; one of which is conceptual the other four are operational and analysed with the descriptive analysis. From the results of the research, it was found out that the participants could not learn the concepts of limit-continuity-derivative-integral conceptually and could not constitute the hierarchical structures among these concepts in their minds. Nevertheless, it was determined that the participants learned the procedural knowledge of each concept independent from the other. From these results, it can be recommended that placing activities emphasizing on the relationships among the concepts in teaching the concepts should be applied more.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.458
Threshold uncertainty score0.175

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.097
GPT teacher head0.437
Teacher spread0.340 · 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 designTheoretical or conceptual
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

Citations7
Published2016
Admission routes1
Has abstractyes

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