Student Success in Face-To-Face and Distance Teleclass Environments: A matter of contact?
Bibliographic record
Abstract
Learning from a distance continues to gain popularity. An influx of traditional, and even on-campus students attest to its flexibility, but are they equipped to succeed in a low-contact distance environment versus a face-to-face, on-campus environment? This research explored whether several variables including background, preparedness and self-perceptions assessed within the first week of class contributed differently to the success of students completing one-way distance teleclasses (n = 35) versus students completing the same classes in face-to-face, on-campus environments (n = 64). The distance students were less successful than face-to-face students when exam grades were examined (A, B, C versus D, F, drop). For distance learners, higher reading comprehension and scholastic competence were indicative of exam grade success. Student-initiated contact with the instructor was marginally related to distance student success. For face-to-face learners, reading comprehension, reading rate and lower athletic competence was indicative of exam grade success. Suggestions to help students decide whether distance learning is right for them and ways to support distance learners in low-contact environments are discussed.
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.
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 | 0.004 | 0.001 |
| 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 | 0.001 | 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 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".