MULTI-LEVEL PLANNING THEORETICAL MODEL: A PROPOSED FRAMEWORK FOR DESIGNING ADULT EDUCATION PROGRAMS FROM THE PERSPECTIVES OF ADULT EDUCATION PROFESSIONALS
Bibliographic record
Abstract
This grounded theory research aims to generate a theoretical model by developing frameworks for designing adult education courses and trainings in higher education institutions (HEI) in an Asian country through the perspective and experiences of adult learners. Using purposive sampling, the participants were 13 HEI middle managers who were sent to the University of Toronto in Canada to be trained on how to meet the emerging needs of adult education professionals. The participants were asked to write down their reflection based on guide questions that asked about their insights regarding the success and challenges they encountered during their two-week adult education training. The data were analyzed using Glaser and Strauss’s (1967) model of grounded theory analysis that includes theoretical sampling, constant comparison, and theoretical sensitivity. The findings of the study generated a multi-level theoretical framework, an iterative process from the conceptual stage to the evaluation stage of an adult education program, that will assist HEIs in crafting sustainable adult education programs that exemplify best practices from the academe, industries, and businesses. The model will be useful for HEIs who are looking for innovative adult education models.
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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 | 0.014 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.004 | 0.011 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".