Influence of Fieldwork on the Preparedness of Food Technology and Bioengineering students for the Job Market: A Case study of EAPI Student Skills Enhancement Program
Bibliographic record
Abstract
This study aimed at evaluating the influence of fieldwork on the professional and personal skills among Food Technology and Bioengineering (FTB) students of Makerere University. The data was obtained from 40 respondents from three FTB programs (Food Science and Technology, Human Nutrition, and Agricultural Engineering). A semi-structured electronic questionnaire was used to collect the data. The questionnaire comprised of Part 1: Student biography, Part II: Participation in the EAPI student skills enhancement program, Part III: Professional skills, and Part IV: Personal growth. Part I and II consisted of closed-ended questions while Part III and Part IV were evaluated on a 5-point Likert scale (1- Strongly disagree and 5 – Strongly Agree). Descriptive analysis was used to evaluate the student demographic information and participation in the student enhancement program. The reliability of the Likert scale for professional development and personal growth was determined using the Cronbach’s alpha index. The study results indicated that 60% (n=40) of the respondents better understood their career goals through fieldwork, 83% (n=40) increased their skills and knowledge in performing particular tasks, 55% (n=40) changed their attitude and feelings about self and others, while 75% (n=40) had the opportunity to apply theoretical concepts to the actual work environment. Fieldwork stimulated the FTB students’ interest in the field of food processing, mindset change especially concerning job creation, conduct, and prospects. The study findings explain the need to adjust the mode of knowledge delivery and dispensation at the Higher Education Institutions to reduce the rate of unemployment and improve the employability of students.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".