Why is self-study so effective?
Last reviewed: 16.10.2021
All iLive content is medically reviewed or fact checked to ensure as much factual accuracy as possible.
We have strict sourcing guidelines and only link to reputable media sites, academic research institutions and, whenever possible, medically peer reviewed studies. Note that the numbers in parentheses ([1], [2], etc.) are clickable links to these studies.
If you feel that any of our content is inaccurate, out-of-date, or otherwise questionable, please select it and press Ctrl + Enter.
In recent years, teachers have paid more attention to practical exercises, laboratory experiments and student research. This is due to the fact that students learn the material much better if they have the ability to control the intensity of obtaining knowledge independently.
Self-directed training had time to prove itself from the positive side, however, the reasons for this phenomenon are poorly understood.
Some scientists suggest that self-directed learning is effective due to the person's motivation to learn. However, in order to identify the relationship between self-directed learning and cognitive processes, in particular memory and attention processes, specialists do not have enough data.
Douglas Markant and Todd Gurekis, scientists from New York University, tried to investigate the reasons for the effectiveness of this process of studying the material. They came to the study of this kind of learning from the computational and cognitive point of view.
Specialists put forward several hypotheses as to why self-directed learning has advantages over other types of material mastering.
Self-directed and independent comprehension of information helps a person to optimize his experience and concentrate on studying materials that we have not yet grasped. In addition, the nature of self-directed learning allows you to keep the information you have studied for a long period of time.
However, this kind of training is not always effective. A person can make mistakes in making a decision about the information that he is going to study. The reason for this may be cognitive errors.
Researchers note that the basis for studying how people evaluate various sources of information, as well as assess the data that they are looking for, can be the computational models that are commonly used in machine learning studies.
Analysis using machine learning techniques can help in determining the negative and positive moments of self-directed learning.
A joint study, which includes an assessment of this type of comprehension of information in terms of cognitive and computational processes, will help experts understand the essence of the processes that are the basis of independent, self-directed learning.
Also, scientists hope that through the understanding of these processes, it will be possible to develop auxiliary methods for independent study of the material.