Profiling the digital readiness of higher education students for transformative online learning in the post-soviet nations of Georgia and Ukraine
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
This study profiles the digital readiness of university students in Georgia and Ukraine for fully online collaborative learning, theorized as an educational pathway to democratic transformation. The Digital Competency Profiler was used to gather data from 150 students in Georgia and 129 in Ukraine about their digital competences. The analysis grouped students into high-, medium- and low-readiness segments for 52 actions in technical, communicational, informational and computational dimensions. Findings show that large percentages of Georgian and Ukrainian students are ill-prepared for many online-learning activities, and there is generally greater readiness on mobile devices than desktops/laptops. However, large percentages of Ukrainian students appear in high-readiness segments for communicating online and using social networks. In Georgia, many students report high-readiness for technical and computational interactions. Therefore, the researchers recommend using the digital-readiness data in tandem with a well-chosen, online-learning framework to align these patterns of strengths with future educational innovation.
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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 | 0.000 |
| 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 | 0.000 |
| 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 it