PECULIARITIES OF ONLINE CALCULATORS USAGE DURING DISTANCE LEARNING AT SUMY STATE UNIVERSITY AMONG 5TH YEAR STUDENTS OF MEDICAL INSTITUTE
Bibliographic record
Abstract
Introduction. Situation in Ukraine nowadays stimulates teachers to provide distance learning during practical classes. A lot of foreign students are able to do calculation online. It is reasonable to ask them about advantages and disadvantages of such method for further improvement of study process. The aim is the determination of peculiarities of using online calculators among fifth year medical students. Materials and Methods. We included 60 fifth year foreign medical students who studied online during 2021 year (the main group) and 54 students who learned internal medicine offline during 2019 (the control group) in our trial. Questionnaires were given to all of them at the last class of internal medicine. Most participants (54) from the main group and all participants from the control group have answered about the peculiarities of using online calculators during the process of study, advantages and disadvantages of such method. The results were analyzed by Microsoft Excel and GraphPad Prism. Results. During distance learning of internal medicine at Sumy State University, the number of 5th year students who evaluated results online increased from 12 (22,2 %) to 44 (81,5 %). 46 subjects from the main group (85 %) used online calculators for cardiology, 32 (59 %) – for nephrology and 22 (39 %) – for rheumatology. A big percent of participants from the main (81.5 %) group and the control (50 %) group planned to use online calculators in their future professional activities. In the opinion of most participants from the main group (81.5 %), the main benefit was fast evaluation, which helped to save time. About quarter of them (24 %) decided that such method made learning easier and more effective. A fifth part of students (20 %) determined that more accurate calculation was the most important advantage. Conclusions. During distance learning of internal medicine at Sumy State University, the number of students who did online calculation increased by four times which showed that teachers widely provided the method. In the opinion of majority of foreign students, dependence of internet connection was the main disadvantage of online calculators, while the benefits of this method were: fast, more accurate evaluation, making learning easier and effective.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".