Interactive Learning as Means of Formation of Future Teachers’ Readiness for Self-education
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 problem under study is relevant due to an increased role of future teachers’ self-education as a factor of his competitiveness and effective self-realization in the conditions of global paradigm of lifelong education and the necessity of designing educational technologies for formation of future teachers’ readiness during his study at the university. The aim of the article is to study the effectiveness of interactive learning technologies in the practice of training future teachers as a means of forming their readiness for professional self-education. Main approaches to the study of this problem are the system and the activity approach, implemented in the process of formation of readiness of the future teachers for professional self-education at a modern university. Analysis of the results presented in this paper suggests that the use of the system application and methodically based combination of a variety of interactive learning technologies in the training of future teachers has a positive impact on the formation of all the components of readiness of future teachers for professional self-education (motivational, value, cognitive, activity, reflexive). The article may be useful for university teachers implementing training of future teachers.
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 | 0.002 | 0.001 |
| 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) | 0.000 | 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