A New Model of Knowledge Acquisition: Distance Education
Bibliographic record
Abstract
Taking into consideration the growing pace of globalization and the development of the technological sphere, it is significant to pay particular attention and use the ability of modern information technologies in order to significantly improve the quality and efficiency of education. Currently, the concept of distance education is gradually developing and spreading at all levels of the educational system. It involves the application of various technological achievements, such as: systems of synchronous, asynchronous, mixed acquisition of knowledge, the use of Internet platforms, multimedia solutions and the latest systems for organizing the educational process. Distance learning is the most flexible and affordable type of organization of classes. In addition, this type of learning meets the requirements of the new educational paradigm of the information society, namely: the support of open, person-oriented and continuous training of a person throughout his life; implementation of mass education of all strata of the population, regardless of their place of residence; diversifying and improving the process of acquiring knowledge by meeting the diverse needs of students from different social and demographic groups. The purpose of the article is to clarify the features of the use of distance education tools as a modern learning paradigm, their advantages and disadvantages, to study individual practical aspects of the use of distance education and to highlight the most promising directions for the development of this type of organization of the educational process. Methodology. In the course of writing the academic paper, an analytical method of working with materials was used on applying distance form of learning, as well as a questionnaire survey for practical clarification of certain aspects of distance learning from the viewpoint of its participants. Results. The viewpoint of scientists regarding the features of distance form of learning, its components, advantages and disadvantages was studied, as well as the standpoint of the participants of the educational process regarding the features of using distance education was clarified.
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.
How this classification was reachedexpand
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 | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".