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Record W4312415817 · doi:10.46827/ejse.v8i3.4363

THE EFFECTIVENESS OF CONCRETE-REPRESENTATIONAL-ABSTRACT INSTRUCTION STRATEGIES IN THE INSTRUCTION OF FRACTIONS TO STUDENTS WITH LEARNING DISABILITIES

2022· article· en· W4312415817 on OpenAlexaboutno aff
Hasan Hüseyin Yıldırım, Ahmet Yıkmış

Bibliographic record

VenueEuropean Journal of Special Education Research · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicEducation Practices and Challenges
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationPsychologyGeneralizationQuarter (Canadian coin)Identification (biology)Learning disabilityPedagogyDevelopmental psychologyMathematics

Abstract

fetched live from OpenAlex

The present study aimed to determine the effectiveness of the concrete-representational-abstract instruction strategies employed in the direct instruction of fractions to students with learning disabilities. Furthermore, the generalization of the instruction to different settings and tools, the follow-up data for one and three weeks after the instruction, and the social validity data based on the views of the mothers on concrete-representational-abstract instruction strategies were analyzed. In the study, the inter-behavioral multiple probe model with a probe stage, a single-subject research model, was employed. The dependent variable was the level of identification of proper, half and quarter fractions by the participating students in the study, while the independent variable was the concrete-representational-abstract introduction strategies implemented with the direct instruction method. The study was conducted with three male students with learning disabilities, who resided in Izmir and attended an inclusive primary school. The study findings demonstrated that the concrete-representational-abstract instruction strategies were effective in the instruction of proper, half and quarter fractions to the students with learning disabilities, these skills acquired by the students could be permanent for one to three weeks after the instruction, and all students could generalize these skills to various settings and instruments, and the views of the mothers on concrete-representational-abstract instruction strategies were positive.<p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0968/a.php" alt="Hit counter" /></p>

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)0.007
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.320
Threshold uncertainty score0.750

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.089
GPT teacher head0.406
Teacher spread0.317 · 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

Citations2
Published2022
Admission routes1
Has abstractyes

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