Formation of professional competence of future bachelors of chemical engineering in institutions of higher education: international experience
Bibliographic record
Abstract
This article examines the experience of forming the professional competence of future bachelors of chemical engineering in institutions of higher education in countries such as Belgium, Great Britain, Canada, China, India, and Germany, with the further possibility of its introduction into domestic practice. Significant trends in the development of national education systems have been identified; innovations in chemical education in Ukraine (use of digital resources, interactive laboratory work, project-oriented learning, interdisciplinary approach) are discussed. The constant desire of foreign technical universities for innovations in student-oriented education has been clarified. The experience of Chinese researchers on reforming the teaching of "Principles of Chemical Engineering" in the context of new challenges and the conditions that will contribute to this are considered (learning objectives should meet the needs of the time; the teaching mode should be interesting, students should not be in a state of passive acceptance of chemical theoretical knowledge, after completion theoretical training, teachers should pay attention to training in experimental operation; teachers should be able to optimize the relevant content of the practical teaching of the course). Scientists from foreign countries mentioned in the article proposed the development of a reorientation of chemical education through systems thinking and listed a set of potential advantages. The natural advantages of the weighted multiplex network in mixed learning analysis are demonstrated; blended learning has been proven to provide a concrete and meaningful context for improving students' critical thinking. On the basis of the conducted research, the effectiveness of using international experience in the formation of professional competence of future bachelors of chemical and technological training for Ukrainian universities is determined, provided that the foundations are provided for designing chemistry as a "science for society", the development of reorientation of chemical education through systemic thinking, the use of blended learning to improve critical thinking students, and further implementation of new methods and technologies in education.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".