The aim of this study was to determine the predispositions of the studied groups of students to work in the IT sector. The basis for predisposition assessment was their voluntary self-assessment of certain preferences, which are related to the theory of multiple intelligences of Professor Gardner. The study was conducted on a reference group of IT sector employees, assuming that they will be the model, to which the results of the study will be related. The method used to obtain data about the students’ predispositions was a test carried out in an auditorium mode or online. More than 500 students from several countries were surveyed and interesting statistical material was obtained allowing for comparison between groups. The most important result was to find a way to sort the students into groups in order from most similar in their aptitude to the market pattern to least. This made it possible to determine the boundary beyond which students could be considered selected for a job in the IT sector. Statistical hypotheses about the similarity of the student groups to the reference group were verified. The results were both positive, confirming that a large percentage of students have predispositions to work in the IT market, and less promising. The authors are convinced that the method can be applied all over the world, as they examined groups in very diverse countries, taking into account, for example, location, education system, culture or religion.
The aim of the article is to determine in the studied groups the multiple intelligence distribution defined in the 1980s by Howard Gardner. The research was conducted in three groups of respondents. The first study group was first-year students of computer science, the second was master (2nd degree) students, educationally 4 years older than the first group. Their intelligence distributions were compared with the intelligence distributions of the third group – graduates of the same university, the same field of study after several years of work in positions consistent with their education. Participants filled one of the multiple intelligence tests selected by answering 24 questions. A group of approximately 110 students and approximately 40 IT employees were examined. As there were statistically justified differences in several significant sub intelligences, a discussion was held on the forms of educational impact on student development paths. The research was carried out in conditions of full voluntary participation in the test and on the basis of self-assessment according to questions suggested in one of the online sources. According to the authors, the results seem interesting, although surprising.