MétaCan
Menu
Back to cohort
Record W4391734410 · doi:10.53935/jomw.v2021i2.149

A Comparative Analysis of Some Multiple Intelligences of IT Students

2021· article· en· W4391734410 on OpenAlex
Qiang Huang, Matthew M. Davis, R Harris

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Management World · 2021
Typearticle
Languageen
FieldPsychology
TopicEmotional Intelligence and Performance
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMathematics educationTheory of multiple intelligencesPsychologyComputer science

Abstract

fetched live from OpenAlex

Information management (IM) is a vital skill set in the area of knowledge and capability that should be possessed by IT professionals. However, the existing educational programs in academic institutions tend to overlook this aspect of training but focus instead on IT capabilities. This study aims at performing a comparative analysis on some multiple intelligences (emotional intelligence, social intelligence and cultural intelligence) of IT/IM students in international scale. The evaluative instrument was reviewed by the scholars in information management research domain and further examined in pre-test interviews prior to the formal administering of the questionnaires to students in the three countries. According to the results of analysis, the differences in emotional intelligence and social intelligence of subjects are significant. However, there is no significant difference in cultural intelligence and emotional intelligence. The findings of this investigation will contribute toward the formulation of future educational programs and selection of IT personnel by corporations when dealing with cross-cultural education and employment.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.098
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.102
GPT teacher head0.433
Teacher spread0.331 · 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