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Record W4390097050 · doi:10.21271/zjhs.27.spb.10

“The effectiveness of a program based on educational games in developing the efficiency of cognitive representation of information and academic achievement motivation among students with academic learning difficulties”

2023· article· en· W4390097050 on OpenAlexaboutno aff
Baydaa Mohammed Tahir Abdulghani, Araz Hakem Radha

Bibliographic record

VenueZanco Journal of Humanity Sciences · 2023
Typearticle
Languageen
FieldPsychology
TopicPsychology of Development and Education
Canadian institutionsnot available
Fundersnot available
KeywordsMathematics educationAcademic achievementCognitionRepresentation (politics)PsychologyTest (biology)Reliability (semiconductor)Sample (material)Scale (ratio)

Abstract

fetched live from OpenAlex

The current research aims to identify the effectiveness of aprogram based on educational games for developing the efficiency of cognitive representation of information and the motivation for academic achievement among students with difficulties in academic learning. The sample consisted of (8) students were from the third and fourth grades of primary school who attended the Canadian International School - Erbil for the academic year (2021-2021). The researchers used the semi-experimental approach, and to achieve the hypotheses of the research, the researchers built a program based of (16) sessions, The researchers also adopted the scale (Ghanim, 2011) to measure the efficiency of cognitive representation of information, and the scale (Rabaya, 2018) to measure the motivation of academic achievement after extracting their validity and reliability. The data was analyzed and processed statistically using the Statistical Package for Social Sciences (SPSS). The research found: There are statistically significant differences at the level of significance (0.05) between the score ranks of the experimental group members in the efficiency of cognitive representation of information and the motivation of academic achievement between the pre and posttest and in favor of the post test. And the effectiveness of the program based on educational games.

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)0.004
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.228

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.052
GPT teacher head0.403
Teacher spread0.351 · 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 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".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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