The Impact of Contact Sessions and Discussion Forums on the Academic Performance of Open Distance Learning Students
Bibliographic record
Abstract
This study investigated the impact of face-to-face contact sessions and online discussion forums on the academic performance of students at an Open Distance Learning (ODL) university (N = 1,015). t-Tests for independent samples indicated that students who attended a written assignment preparation contact session performed significantly better in the written assignment than those students who did not attend this contact session [t(813) = 4.64, p = 0.00]; students who attended an examination preparation contact session did not perform significantly better in the examination than those students who did not attend this contact session [t(892) = 1.12, p = 0.26]; while students who used an online discussion forum performed significantly better in the final examination than those students who did not use this forum [t(1,013) = 4.04, p = 0.00]. Reasons for these mixed results are subsequently discussed. The study also found that the attendance of contact sessions and the utilisation of an online discussion forum by students were extremely low, and possible reasons for this are also given. Implications for the use of contact sessions and online discussion forums to improve the academic performance of ODL students are also 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 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 | 0.003 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".