The Impact of Distance Education on Learning Outcome in Computer Skills Course in Prince Sattam bin Abdulaziz University: An Experimental Study
Bibliographic record
Abstract
The present study aimed to explore the impact of distance education on the learning outcome of students in computer skills course in Prince Sattam bin Abdulaziz University in Al-Sulail, Saudi Arabia. In this study, the learning outcome is represented in the students’ academic achievement. The researcher adopted an experimental approach. He selected a sample consisting from 80 male students from 4 sections of a computer skills course. Those students were divided equally into control and experimental groups. The members of the control group were taught through adopting a face-to-face instructional approach. They attended 4 face-to-face lectures. The members of the experimental group were taught online through using the Blackboard system. The researcher used a pre-test and a post-test for assessing students’ academic achievement. SPSS program was used. It was found that both groups share similar levels of computer literacy. It was found that distance education has a significant positive impact on students’ academic achievement in the computer skills course. The researcher recommends adding online instructional activities to the curricula used in Saudi universities.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".