Newcastle-Ottawa Quality assessment scale.
Bibliographic record
Abstract
<div> Background Academic success is a measure of students’ ability to attain their educational objectives, often assessed through regular evaluations or examinations. To establish effective policies and programs that align with academic accomplishments, conducting comprehensive data analysis is pivotal. Hence, this systematic review aimed to synthesize the factors impeding the academic achievements of Ethiopian students in higher education. Methods A comprehensive review was conducted on studies involving Ethiopian university students from 2013 to 2022. The review encompassed 24 papers that were gathered from different databases like PubMed, Google Scholar, African Journals Online, Scopus, and Web of Science. Results The findings of this research revealed that inadequate classroom environments, experiencing dysmenorrhea, and engaging in excessive social media usage were all linked to a decline in academic performance. Conversely, adopting healthy sleep habits, achieving high scores in entrance exams, and avoiding recent substance abuse were all factors positively influencing academic success. In addition, there was a positive correlation between academic excellence and being a health science college student and age range of 20 to 24 years old. Conclusion To enhance academic performance, it is crucial to address the negative factors identified, such as inadequate classroom environments, dysmenorrhea, and excessive social media usage, while promoting positive factors like healthy sleep habits, high scores in exams, and avoiding substance abuse. Additionally, being a health science college student and belonging to the age range of 20 to 24 were found to be associated with academic excellence. </div>
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.214 | 0.004 |
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; both teacher heads agree on what is shown here.
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".