Assessment of the effectiveness of internet-based distance learning through the VClass e-Education platform
Bibliographic record
Abstract
This study assesses the effectiveness of internet-based distance learning (IBDL) through the VClass live e-education platform. The research examines (1) the effectiveness of IBDL for regular and distance students and (2) the distance students’ experience of VClass in the IBDL course entitled Computer Programming 1. The study employed the common definitions of evaluation to attain useful statistical results. The measurement instruments used were test scores and questionnaires. The sample consisted of 59 first-year undergraduate students, most of whom were studying computer information systems at Rajamangala University of Technology Lanna Chiang Mai in Thailand. The results revealed that distance students engaged in learning behavior only occasionally but that the effectiveness of learning was the same for distance and regular students. Moreover, the provided computer-mediated communications (CMC) (e.g., live chat, email, and discussion board) were sparingly used, primarily by male distance students. Distance students, regular students, the instructor, and the tutor agreed to use a social networking site, Facebook, rather than the provided CMC during the course. The evaluation results produce useful information that is applicable for developing and improving IBDL practices.
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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 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".