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Record W3155196079 · doi:10.5539/mas.v15n3p17

Building a Self-Confidence Scale According to the Item Response Theory for High School Students in Jordan

2021· article· en· W3155196079 on OpenAlexvenueno aff
Hani Alkhaldi, Malek Alkhutaba, Mohammad Al-Dlalah

Bibliographic record

VenueModern Applied Science · 2021
Typearticle
Languageen
FieldPsychology
TopicEducation, Achievement, and Giftedness
Canadian institutionsnot available
Fundersnot available
KeywordsScale (ratio)StatisticsSample (material)Matching (statistics)PsychologyStandard deviationConfidence intervalDimension (graph theory)MathematicsSocial psychologyGeographyCartography

Abstract

fetched live from OpenAlex

This study aimed to build self-confidence for high school students in Al-Mafraq Governorate in Jordan following the Item Response Theory (IRT). The scale included its initial version (50) items. To ensure the external validity of the scale, it was reviewed by several experts. According to the experts’ feedback, some items should be deleted or modified. The final version of the scale included (44) items. The scale was further applied to an experimental sample of (310) male and female students to verify psychometricians’ characteristics. Finally, the scale was administered to a sample of (1060) male and female high school students in Al-Mafraq Governorate. Data were collected, coded, and analyzed using statistical programs (SPSS and WINSTEPS). The most important results were the following: the self-confidence measure was one-dimensional, which means it measures only a single dimension. The results further revealed identical to the partial estimation model, and the index of average matching of individuals and the external and internal items approached zero, and the standard deviation approached the correct one. The estimated values of the distinct thresholds for the scale items showed a clear discriminatory ability and the emergence of particular threshold scores on the scale. After deleting the paragraphs that did not fit the study's model, the scale's final version included 39 items. The results also showed that the transfer values of logistical capacity units were within (-2.88 -2.77), within the IRT's accepted range.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.633
Threshold uncertainty score0.557

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.022
GPT teacher head0.362
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 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

Citations2
Published2021
Admission routes1
Has abstractyes

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