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Record W2085603187 · doi:10.5539/ibr.v7n4p92

The Impact of Demographic and Academic Characteristics on Academic Performance

2014· article· en· W2085603187 on OpenAlex
Nout M. Alhajraf, Aishah M. Alasfour

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInternational Business Research · 2014
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsnot available
Fundersnot available
KeywordsNationalityPsychologyMedical educationDescriptive statisticsAcademic achievementTest (biology)Sample (material)Academic yearMathematics educationMedicineImmigrationPolitical science

Abstract

fetched live from OpenAlex

The purpose of this study is to explore students’ demographic and academic characteristics that are associatedwith students’ academic performance during their undergraduate studies. Demographic and academiccharacteristic such as age, gender, nationality, high school major and high school GPA were studied as potentialdeterminants of academic performance. A sample of 700 students from the College of Business Studies at thePublic Authority for Applied Education was examined. Descriptive statistics, T-test and multiple regressionswere used. The results of the study reveal that students’ age, gender, high school major and high school GPA aresignificantly related to students’ academic performance. Our research has some implications. The findings revealthat student’s age, gender, high school major and high school GPA are significantly related to business students’academic performance. Interestingly, the findings highlight the positive and significant influence of sciencebackground on the academic performance of business students. This study contributes to the literature of theundergraduates business students academic performance. The findings of this study may be useful for educationsector, educators, college’s management and future researchers.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.118
Threshold uncertainty score0.433

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.136
GPT teacher head0.480
Teacher spread0.344 · 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