Author:
Malach Josef,Vicherková Dana,Chmura Milan,Švrčinová Veronika
Abstract
Achievement motivation is an important prerequisite for students’ engagement, overcoming study difficulties and, ultimately, successful completion of their studies. The aim of this study is to find out the current level of performance motivation of the population of students of engineering high schools, to compare its level with the standard for high school population and to find out whether there is a relationship between its level and choice. Two questionnaires were used in the research. The first was the School Achievement Motivation Questionnaire for Pupils (Hrabal, Pavelková, 2011). The theory of achievement motivation is then based on the concept of independence of the need for successful performance and the need to avoid failure. The resulting orientation of a person in a performance situation then depends on the predominance of one or the other tendency. The second questionnaire was focused on finding personal data, questions of school choice, satisfaction with school choice. The research was carried out at the beginning of 2020 and the sample consisted of over 900 students. Main results of the study: First, in the component of performance motivation NACH (need to achieve) the performance motivation of the group is statistically different from the group norm. In the NAF (the need to avoid failure) component, the results are statistically identical. Second, schools do not differ in the results for the NACH component, but differ in the NAF component. Third, in both components, the value of performance motivation for beginners and for final years in both components is significantly different from other years. Fourth, the student's statement on the choice of study at an engineering school as a primary choice is not related to the values of NACH and NAF. Fifth, the level of student's achievement motivation in both components is related to the student's idea of studying.
Publisher
PIAP - Industrial Research Institute for Automation and Measurements
Subject
Artificial Intelligence,Signal Processing,Control and Systems Engineering
Cited by
1 articles.
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