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Record W2157774095 · doi:10.5539/jel.v2n4p102

Lecturers’ Perception of Strategies for Enhancing Business Education Research in Tertiary Institutions in Nigeria

2013· article· en· W2157774095 on OpenAlexvenueno aff
James Okoro

Bibliographic record

VenueJournal of Education and Learning · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicAfrican Education and Politics
Canadian institutionsnot available
Fundersnot available
KeywordsTest (biology)PsychologyNull hypothesisPerceptionBusiness educationHigher educationQualitative researchMedical educationPedagogyMathematics educationSociologyPolitical scienceSocial scienceMedicine

Abstract

fetched live from OpenAlex

Business education programme seems to have been faced with inadequate qualitative research in tertiaryinstitution in Nigeria. The study therefore, assessed the strategies for enhancing Business Education research.Two research questions and six hypotheses guided the study. A 66 item questionnaire was administered to 164colleges of education and 109 lecturers of universities in South South Nigeria making a total of 273 lecturers.The research questions were answered using mean and while z-test was used to test the null hypotheses. Thefindings revealed that the inability of students to source current literature, poor knowledge of researchprocedures by supervisors, poor knowledge of research procedures by students are some of the constraintsaffecting business education research. The findings also revealed that students’ ability to source current literature,knowledge of research procedures by supervisors and knowledge of research procedure by students can enhancebusiness education research. It was recommended that regular workshops and seminars should be organized forlecturers and students on how to supervise and write projects respectively; researchers should ensure that qualityinformation is generated from the study being investigated.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.151
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.060
GPT teacher head0.438
Teacher spread0.377 · 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
Published2013
Admission routes1
Has abstractyes

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