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Record W2485316889 · doi:10.5539/jel.v5n4p34

Interdisciplinary Curriculum Empowers Cognitive Advancement to Solve Real Life Problems

2016· article· en· W2485316889 on OpenAlexvenueno aff
Noha M. Al Husni, Naim El Rouadi

Bibliographic record

VenueJournal of Education and Learning · 2016
Typearticle
Languageen
FieldPsychology
TopicInnovative Teaching and Learning Methods
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumCognitionMathematics educationPsychologyCurriculum developmentCognitive skillControl (management)PedagogyComputer science

Abstract

fetched live from OpenAlex

<p>Interdisciplinary curriculum supports cognitive development through well planned lessons at early age. This article focuses on a specific experimental study done in 2010 on Grade 7 learners in a Lebanese private school to aid them in empowering their skills and competencies to solve a real life problem. The objective of this experimental study is to prepare students for Grade 10 to create the necessary chemistry between learners and Physics as a discipline. The problematic can be stated as: The synergy of teachers’ team work to design an interdisciplinary curriculum implementing ICT in classrooms facilitates the transfer and construction of knowledge and scaffolds learners with necessary skills and competencies from an early age to solve physics problems. The results were very optimistic showing 57% development of the study group members in comparison with only 10% for the control group members. Further studies are necessary on larger samples and for longer duration to expose learners to different topics and trace the effect of interdisciplinary curriculum after 4 years.</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)0.002
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.804
Threshold uncertainty score0.605

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 science0.0000.000
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 head0.029
GPT teacher head0.426
Teacher spread0.397 · 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 designOther design
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
Published2016
Admission routes1
Has abstractyes

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