Competency-Based Assessment in Entrepreneurship Education in Kenya’s Tertiary Institutions
Bibliographic record
Abstract
Education systems worldwide are shifting to knowledge-based curricula with emphasis on the learners’ acquisition of relevant competencies. Entrepreneurship education was introduced in tertiary institutions in Kenya in 1999 to produce entrepreneurs, including preparing graduates for the world of work. However, limited studies have focused on the assessment of acquisition of such competencies, especially in entrepreneurship education. This study was designed to examine the effectiveness of assessment modes used in entrepreneurship education in imparting requisite competencies among students in tertiary institutions in the country. The study adopted a cross-sectional research design. A total of 412 students selected from three tertiary institutions were involved in the study. Data were collected using questionnaires and analysed quantitatively using descriptive and inferential statistics. The study showed that written examinations were the most commonly used mode of assessment of entrepreneurship education, followed by projects and attachment. The study revealed that there is no significant difference in the influence of the mode of assessment as adopted in the different tertiary institutions in fostering the acquisition of competencies (F Ratio<F Critical) (0.835<3.02). However, when the requisite competencies were compared, the study showed that the mode of assessment adopted enhanced acquisition of ideas and opportunities (0.313 units) and resources (0.364 units) competencies more compared to the into-action competencies (0.249 units). To enhance the acquisition of relevant competencies, the study recommends adoption of different appropriate modes of assessment in entrepreneurship education.
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 imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".