St. Petersburg State University specialists and Military Space Academy named after A. F. Mozhaisk has developed a neural network that analyzes the characteristics and preferences of groups of people learning first aid skills. This allows the instructor to choose the most effective teaching method for a specific audience.
Providing first aid is an important skill that anyone may need, because professional medical care may not always be instantaneous in an unforeseen situation. Often, at critical moments, the victim's life depends on the actions of eyewitnesses to events, and in some circumstances, knowledge of tactical medicine can save a person's life.
That is why the training of such skills in A lot of attention is being paid to Russia today. The basics of first aid are included in the curricula of schools and universities, and are also among the mandatory briefing points for employees of various organizations. However, as the researchers emphasize, effective teaching of these disciplines requires the use of simulators and dummies to demonstrate and put into practice the necessary techniques. This complicates the mass implementation of such courses. In addition, constantly updated algorithms for providing assistance often outpace the rate of retraining of teaching staff in non-core organizations.
At the same time, the key problem is the lack of motivation among the listeners. Some consider this knowledge unnecessary, while others are afraid of the sight of blood or discussing how to deal with loss of consciousness and resuscitation of another person. Therefore, an individual approach is extremely important, which will take into account the needs and, possibly, the concerns of each student.
Elena Kharitonova, Head of the Department of Fundamentals of Medical and Special Knowledge at St. Petersburg State University
According to her, even working with different groups of students requires flexibility from the teacher. Some students are actively willing to help and enthusiastically learn the practice, while others, on the contrary, experience fear and get lost during classes. Some people need realistic examples and images to understand, while others perceive information better through abstract images.
To determine which method will be most productive for a particular group, experts from St. Petersburg‑St. Petersburg State University together with colleagues from Military Space Academy named after A. F. Mozhaisky created a neural network that replaces traditional questionnaires and surveys. The algorithm promptly processes the responses of each listener and provides the teacher with a detailed portrait of the group: the students' willingness to perceive the material, their fears, expectations and individual characteristics. This helps to immediately identify educational preferences and optimally allocate resources — from the size of the audience to the available equipment — to achieve the best result.
"We conducted a study among students and cadets and found out that for most of them a combined model combining VR technologies and a simulation method would be the most effective. This format combines the advantages of virtual reality for studying theory and complex scenarios with practicing skills on dummies," explained Elena Kharitonova.
The positive effect of this approach was particularly pronounced in large groups, which significantly reduced the teacher's time spent on mastering the material by each student.
