The Development of Reflective Undergraduate Students: Assessing the Educational Benefits of Reflective Learning Logs in Entrepreneurship Module
Bibliographic record
Abstract
The objective of this paper is to analyze written reflections on learning log of among the third and final year students undertaking an entrepreneurship module. Data was collected in the form of written reflection taken from the learning log of 140 students from 3 classes. At the end of the collection only 136 students’ responses were managed to be collected given 4 students failed to hand in the learning log. A thematic approach was utilized to present the reflections of the students and all data was recorded in a verbatim format. Findings show that most students have never written a reflective log or essay in the formative assessment. As a consequence, they had difficulty in writing the reflection when being requested to do so. This has resulted in their reflection being written descriptively which lacks in critical analysis and deep thinking. The results of this investigation have strongly suggested the need to urgently develop among the students the skills in writing reflectively as they go through the process of higher education which be useful in molding their future professional and entrepreneurial behavior as when they entered the job market which requires a critical reasoning ability. The limitation and future were discussed.
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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 | 0.022 | 0.125 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.003 |
| 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".