The Level of Readiness of Refrigeration and Air Conditioning Program Students in Facing Online Learning during COVID-19 Pandemic
Bibliographic record
Abstract
The spread of Covid-19 has affected the education sector in Malaysia. The closure of higher educational institutions due to the Covid-19 pandemic has affected the structure of learning and teaching, from physical learning and teaching methods in institutions to fully online learning and teaching. The main objective of this study was to study the level of readiness of Refrigeration and Air Conditioning Program Refrigeration and Air Conditioning Program Program students in facing online learning during the Covid-19 pandemic. This study uses a quantitative approach with descriptive research designs and survey methods. the instrument used in this study was a questionnaire that has been distributed to the respondents for their feedback. The population involved in this study is 111 students in Faculty of Technical and Vocational Education, Universiti Tun Hussein Onn Malaysia (UTHM. The data obtained was analyzed using IBM Statistic SPSS software version 23. Results of data analysis indicated that the mean score for the attitude of the participating students is 3.36, whereas the mean scores for the aspects of the motivation, knowledge of existing technology, and internet access were recorded as 3.66, 3.86, and 3.77 respectively. In conclusion, the level of readiness of students of Refrigeration and Air Conditioning Program in facing online learning is at a moderate level.
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 | 0.001 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".