Abstract:

Many psychologists believe that in order to achieve a high degree of motivation, those connections in the brain that lead to fears, anxieties, uncertainty, low self-esteem, and, as a consequence, to low motivation, it is necessary to destroy and create new ones that provide other behavioral stereotypes. And when there are clear instructions on how to behave in each specific situation, it is easier to change without thinking, without reflecting, without referring to your own negative experience, and believing that for life as a whole it is not so much what you think as what you feel and do. This paper proposes a method to motivate students using smart chatbot. The professionally important qualities characteristics are under discussion and the original approache is given on how to avaluate student’s skills – considering any motivation as a fuzzy set of qualities and quantities characteristics. In order to calculate the motivations estimated in this way, it is necessary to know the values and interdependencies of various primary and secondary factors inherent in one degree or another to the individual, whose motivation is evaluated and changes in the process of influence on him. Now the need to create automated systems of such smart motivation formation is becoming more and more popular among people. By smart formation, we understand the property of the system (device, program) to be capable of some independent action during the argumentation in favor of certain actions that are proposed to be performed by an individual to increase his motivation.

The main goal of this paper is to describe how the student motivation to study could be assess by the system with the basis of smart chatbot. The results of the assessment will provide possible ways to improve student's motivation. Unlike most existing systems that use standard testing, the proposed system, through dialogue with student, will provided a more detailed answer to his/her questions using semantic networks which will lead to improved accuracy and completeness of motivation assessment. The system is based on the analysis of students answers to previously prepared questions as well as his/her own questions. When parsing the answer or question, the smart chatboot will separate its negative and/or positive wording and linguistic analysis will take place in order to more accurately evaluate. Based on the investigation results, the recommendations will be presented to improve student motivation.

The technical realization is following. The chatbot is based on the linguistic analysis and document's vector matrix construction. The users' answers to questions stored in the database will be analyzed using statistical approach in order to determine relationships between the frequency certain words (terms) and emotional character of the whole answer. Then, using quasi-matrix logic, a database with a number of predefined words - markers and a set response thresholds, an analysis of the student's motivation will be carried out. Depending on the results obtained, a specific way to increase student motivation will be proposed from the database.

Acknowledgement:
The described research is been financially supported by the Ministry of Education and Science of the Russian Federation, Government Contract # 2.7782.2017/BC.

Keywords:

Student support, motivation, assessment, smart chatbot, qualities characteristics, student's skills.