The Use Of Cronbach Alpha Reliability Estimate In Research Among Students In Public Universities In Ghana.
Bibliographic record
Abstract
This study examines the use of Cronbach alpha reliability estimate in research among university students in Ghana. An exploratory research design was employed in the study. University students’ (both undergraduate and post-graduate) research works were selected from three public universities in Ghana. With the use of inclusion criteria, purposive sampling technique was used to sample 100 research works conducted by students. The sampled research works were examined to evaluate how the students used Cronbach alpha reliability estimate. It was revealed that 91% of the works properly satisfied the conditions for the use of Cronbach alpha. However, 81% of the students calculated for the alpha for multiple constructs which suggests that alpha was treated as a measure of multidimensionality instead of internal consistency. It is recommended that applied courses in research and statistics should be mounted in the various public universities in Ghana. Workshops and seminars should also be organized for both students and lecturers on the use of Cronbach alpha reliability estimate.
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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 | 0.066 | 0.179 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".