Factors affecting Students Continue Intention to Use MOOCs, Benefits and Drawbacks. A Research Paper from the UAE Context
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In the twenty-first century, universities have misplaced their monopoly of the production and transmission of knowledge. They face the assignment of adapting to the needs of society, which can be summarized in three key aspects: economy, science and school development. The use of information communication technology has become the main concern for almost all educational institutions due to its cost efficiency that makes it affordable for all students regardless their economic condition and time effectiveness regardless the physical location. These magnificent advantages motivated not only educational institutions but also the ministries of education in most of the countries to adopt this technology as a key driver for socioeconomic development and illiteracy eradication. The UAE has its own agenda in adopting MOOCs in education system and at the heart of them is improve the quality of education. Despite, these advantages, many challenges still surround this vital technology. Thus, this research is a review paper on the introduction to MOOCs, its advantages and challenges and the trend for future research from the UAE perspective.
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.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it