Higher Education Institutions Educational Process Digitalization in the Context of the Necessity to Provide a Model for Students' Choice of Training Areas and Academic Specialties
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
The digital revolution in the Russian economy is leading to a radical change in the labour market, the emergence of new competencies, improved cooperation, increased responsibility of citizens, their ability to make independent decisions. This, in turn, is the reason for the reorganisation of the educational process, largely based on the use of IT technologies. The purpose of the paper is to solve the problem of unification of educational programmes within the framework of digitalisation of the educational process in universities. The unification of educational programmes is proposed, which ensures the conducting of the educational process without losing its quality, taking into account individual educational trajectories, as well as implementing a model for students' choice of a direction or training specialty, starting from the third year of study, and, as a result, making it possible to transfer students between educational levels up to 5 semesters, and within a level - up to 6 semesters. The unification of educational programmes is considered on the example of the Moscow Aviation Institute (National Research University). The proposed unification covers the extended groups of specialties taking into account different levels and forms of training, as well as various territorial sites (branches).
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 | 0.000 | 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 | 0.001 | 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