Use of problem-based learning in the teaching and learning of horticultural production
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose: Problem-based learning (PBL), a relatively novel teaching and learning process in horticulture, was investigated. Proper application of PBL can potentially create a learning context that enhances student learning. Design/Methodology/Approach: Students worked on two complex ill-structured problems: (1) to produce fresh baby greens for a 4-week catering event and (2) to produce seedlings for a grower. Data collected were analyzed by the concurrent method and presented as case studies. Findings: Students developed positive attitudes through active engagement. Their presentations and reports demonstrated leadership roles, critical thinking and conflict management. Practical professional, social and affective skills were developed through production of 5 kg baby greens, and 2500 vegetable seedlings. Successes and limitations were identified. Theoretical Implication: The quality of the PBL problem is critical for the stimulation and elaboration of prior knowledge, development of epistemic curiosity and the relevant semantic framework. These are motivators that inspire effective learning. Practical Implication: Cognitive and emotional intelligence skills are realized by trusting the PBL process, identifying enhancers and inhibitors. Enhancement of creativity, social and employability skills manifest through challenges that help to develop for the ‘whole’. Originality/Value: In the horticulture industry, stakeholders interact with each other and the agro-ecological system. Consequently, competencies in production and emotional intelligence are invaluable.
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.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 it