Socio-Demographical Variables as Predictors of Academic Self-Directedness
Bibliographic record
Abstract
This study explores whether a range of socio-demographical factors predict adult learner self-directedness in the context of South African open and distance e-learning higher education (ODeLHE). We observe significant differences between socio-demographical groups in the sub-dimensions of the Adult Learner Self-Directedness Scale. The study advances a theory on adult learner self-directedness in ODeLHE contexts. Educators should consider learners’ support practices, particularly in the cases of women, Black Africans, and younger cohorts. ODeLHE practices should also consider learners’ high school grades and proficiency in English, their library access, number of modules they are enrolled in, and who they support financially as factors influencing their level of self-directedness. Such considerations can be used to address the need for the translation of knowledge into policies and activities that improve educational opportunities for students.
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How this classification was reachedexpand
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 | 0.006 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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 teacher head, 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".