Adult Participation in Self-Directed Learning Programs
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
This paper attempts to explain the various concepts related to self-directed learning and also the various theories and models regarding adult participation and also non-participation in self-directed learning programs. Because of the extensive amount of previous literature and research findings dealing with self-directed learning, it is necessary to synthesize the relevant literature so that it can be useful as a basis for this and also for further research in this field. Conceptualization of self-directed learning will be reviewed in the wider and broader perspective. Also reviewed will be the development of self-directed learning, the definitions and characteristics of self-directed learning. Different conceptualization and factors contributing to adult participation in self-directed learning will be touched. In order to design an instrument and to develop a conceptual model, which adequately reflects those factors that have been reasonably determined to be relevant, it is felt that there was a need to identify those variables or factors, reported in earlier studies, which have been found to be significantly associated with adult participation in self-directed learning.
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 | 0.000 | 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