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Record W1566377997

The impact of student style differences and motivation on learning outcomes in management education: an international inquiry

2014· article· en· W1566377997 on OpenAlexaboutno aff
Eva Cools, Karlien Vanderheyden, Kristin Backhaus

Bibliographic record

VenueReflecting education · 2014
Typearticle
Languageen
FieldPsychology
TopicLearning Styles and Cognitive Differences
Canadian institutionsnot available
Fundersnot available
KeywordsLearning stylesCognitive styleConstructiveStyle (visual arts)PsychologyManagement stylesCognitionHigher educationMathematics educationMechanism (biology)PedagogyPolitical scienceComputer scienceProcess (computing)Public relations
DOInot available

Abstract

fetched live from OpenAlex

The present study aims to provide further insights regarding the impact of students’ cognitive styles, learning styles, and motivation on learning outcomes in higher education. We studied 322 management and MBA students from two business schools, respectively in Belgium (n = 244) and Canada (n = 78). As hypothesized, the effect of cognitive styles and learning styles on academic achievement was mediated through the intervening mechanism of motivation. This research extends the education and styles literature by investigating the combined impact of individual style differences and intervening mechanisms on student learning outcomes across two different cultures. Moreover, it contributes to educational practice in higher education by providing relevant insights to stimulate the design of constructive student-centred learning environments.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.068
GPT teacher head0.470
Teacher spread0.403 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2014
Admission routes1
Has abstractyes

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