Lecturers’ Perception of Strategies for Enhancing Business Education Research in Tertiary Institutions in Nigeria
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.018 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".