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Record W1519961202 · doi:10.5430/wje.v5n3p99

Lecturers’ Perception of Constraints Facing the Teaching of Entrepreneurship Education in Colleges of Education in South South Nigeria

2015· article· en· W1519961202 on OpenAlexvenueno aff
James Okoro

Bibliographic record

VenueWorld Journal of Education · 2015
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican Education and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsCronbach's alphaEntrepreneurshipTest (biology)Entrepreneurship educationPsychologyPopulationMedical educationSample (material)Mathematics educationWelfarePerceptionLikert scalePedagogySociologyPolitical scienceMedicinePsychometrics

Abstract

fetched live from OpenAlex

The study investigated the constraints facing the teaching of entrepreneurship education in colleges of education inSouth South Nigeria. A research question was raised and three hypotheses were formulated for the study. Adescriptive survey design was used for the study. The population which also served as sample comprised 206Business Education lecturers. The researcher used a questionnaire which has 24 items. The content and face of theinstrument was validated by experts in business education and measurement and evaluation. The questionnaire has areliability value of 0.92 using Cronbach alpha. Mean score and standard deviation were used to answer the researchquestion while t-test was used to test the hypothesis at 0.05 level of significance. The findings are ineffectivemonitoring, ineffective evaluation, insufficient time, poor welfare package and inadequate teaching facilities aresome of the constraints facing the teaching of entrepreneurship education in colleges of education. It was, therefore,recommended that adequate teaching facilities should be provided by the school authorities to enhance qualityteaching of entrepreneurship education. Adequate teachers should also be employed by school authorities.

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)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.285
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
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)0.0000.000

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 head0.034
GPT teacher head0.351
Teacher spread0.317 · 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 designQualitative
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

Citations1
Published2015
Admission routes1
Has abstractyes

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