MétaCan
Menu
Back to cohort
Record W3179670196 · doi:10.1108/et-04-2020-0076

Evaluating the impact of social enterprise education on students' enterprising characteristics in the United Arab Emirates

2021· article· en· W3179670196 on OpenAlexaff
Zeinab Khansari

Bibliographic record

VenueEducation + Training · 2021
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicEntrepreneurship Studies and Influences
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsPsychologyLocus of controlHigher educationPerspective (graphical)Sample (material)PedagogyMedical educationMathematics educationPolitical scienceSocial psychologyMedicine

Abstract

fetched live from OpenAlex

Purpose This study evaluates the effectiveness of an enterprise education (social innovation and enterprise) learning programme on the enterprising characteristics among interdisciplinary undergraduate enterprise education students from a general (without considering gender) and gender-specific perspective at a higher education institution in the United Arab Emirates. Design/methodology/approach Based on a convenience sampling approach, pre- and post-surveys were distributed among 180 undergraduate students from January to April 2019. An independent-samples t-test was utilised to evaluate the impact of enterprise education on students' learning for three sample classifications, which were (1) general or gender-neutral (no gender consideration), (2) male and (3) female. Findings This study found significant improvements in the enterprising characteristics of students as a result of undertaking the learning programme in enterprise education. There was a greater improvement among female students in comparison to male students. However, contrasts in enterprising enhancement trends between female and male students were recognised. While the greatest improvement for male students were identified in their risk-taking characteristics, for female students, the risk-taking characteristic evidenced the least influence. The differences between the enterprising levels in risk-taking, and locus of control, between male and female students, were prominent post completion of the learning programme. Research limitations/implications Considering that a quantitative method of inquiry was adopted to address the dearth of research evaluating the effectiveness of our learning programmes in enterprise education (i.e. social innovation) on students' psychological traits through a gendered lens, qualitative insights could enrich the depth of the research findings. As this study was conducted on a limited number of students at a single university, the results do not claim generalisation to other contexts. Practical implications The outcomes of this research deliver valuable insights about the divergent influences of enterprise learning programmes on male and female students. The implications of the study suggest that policymakers and stakeholders should consider gender diversities when designing an effective and equitable entrepreneurship and enterprise learning programme that fosters and stimulates students' enterprising mindset and confidence for both male and female students. The implications are for academics, educational instructors and policymakers. Originality/value This study presents a literature review on the impact of entrepreneurship education by focusing on the key enterprising psychological characteristics and educational systems over the last two decades, and illustrates that most studies in the field of entrepreneurship are based on either general (gender-neutral) or gender-specified investigations. This work provides a comparison between these two perspectives in a relatively underexplored region of the UAE and demonstrates that relying solely on gender-neutral analyses hinders the opportunity to enhance and effectively harness females' entrepreneurial potential.

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)0.001
metaresearch head score (Gemma)0.002
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 score0.003
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
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 head0.077
GPT teacher head0.401
Teacher spread0.324 · 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

Citations22
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueEducation + TrainingSame topicEntrepreneurship Studies and InfluencesFrench-language works237,207