High School Students in the New Learning Environment: A Profile of Distance E-Learners.
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
The relative ubiquity of computer access and the rapid development of information and communication technology have profoundly impacted teaching and learning at a distance. Relatively little is currently known about the characteristics of those students who participate in distance e-learning courses at the secondary school level. In an effort to provide a better understanding of who secondary school distance e-learners are, this study utilized a logistic regression analysis to examine data from a survey of students at 35 public schools in the Eastern Canadian province of Newfoundland and Labrador. The survey sample included students who did and did not participate in distance e-learning courses. The results of the analysis suggest that secondary school distance e-learners are more likely to be females who are a) completing a demanding academic program, b) positively disposed toward school, c) not employed in a part-time job, and d) confident of their computer and reading abilities.
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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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 it