How Can Primary Teachers Become Effective Entrepreneurship Educators? Insights from the ALLFA Learning Journey Model
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
Entrepreneurship education is increasingly emphasized in primary schools, yet many teachers are not adequately prepared to effectively cultivate students’ entrepreneurial skills. This study investigated primary teachers’ professional development needs for promoting entrepreneurial characteristics among students and developed a tailored learning journey model to address those needs. A mixed-method approach was employed, including a survey of 467 primary teachers in Bangkok, Thailand, and focus group interviews to gather in-depth insights. Results indicated high overall development needs, especially in designing entrepreneurship-oriented learning activities, integrating technology to enhance learning, and understanding entrepreneurial traits. No significant differences in needs were found across teacher demographics. In response to these findings, a five-stage teacher learning journey model—termed ALLFA (Awaring, Learning, Linking, Facilitating, Assessing)—was formulated to guide educators in effectively fostering entrepreneurship in the classroom. This model provides a structured framework for ongoing, flexible teacher training in entrepreneurship education. Overall, the study contributes to the field of entrepreneurship education and teacher development by identifying key competency gaps and presenting the ALLFA model as an actionable framework, with implications for teacher training policy and future research on student outcomes.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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