A Method of Selecting Computer Science Students for the IT Market Based on Their Predispositions Resulting from Multiple Intelligence

Autor/inn/en	Wilinski, Antoni; Skulysh, Mariia; M. K., Arti; Bach-Dabrowska, Irena; Agbeyangi, Abayomi O.; Zahra, Hina; Krason, Hubert; Dobska, Jolanta; Kupracz, Lukasz
Titel	A Method of Selecting Computer Science Students for the IT Market Based on Their Predispositions Resulting from Multiple Intelligence
Quelle	In: Informatics in Education, 21 (2022) 4, S.733-767 (35 Seiten)Infoseite zur Zeitschrift PDF als Volltext kostenfreie Datei Verfügbarkeit
Zusatzinformation	ORCID (Wilinski, Antoni) ORCID (Skulysh, Mariia) ORCID (M. K., Arti) ORCID (Bach-Dabrowska, Irena) ORCID (Agbeyangi, Abayomi O.) ORCID (Zahra, Hina) ORCID (Kupracz, Lukasz)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1648-5831
Schlagwörter	Admission Criteria; Computer Science Education; Information Technology; Multiple Intelligences; Personality; Profiles; Aptitude; Labor Market; Employment Potential; Foreign Countries; Ukraine; Poland; India; Pakistan; Nigeria + Suchen Sie Ihr Suchwort? Admission; Admission procedures; Zulassungsbedingung; Zulassungsverfahren; Zulassung; Computer science lessons; Informatikunterricht; Informationstechnologie; Intelligenz (Psy); Personalität; Charakterisierung; Profilanalyse; Eignung; Labour market; Arbeitsmarkt; Arbeitsmarktbezogene Qualifikation; Beschäftigungsfähigkeit; Ausland; Polen; Indien
Abstract	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. (As Provided).
Anmerkungen	Vilnius University Institute of Mathematics and Informatics, Lithuanian Academy of Sciences. Akademjos str. 4, Vilnius LT 08663 Lithuania. Tel: +37-5-21-09300; Fax: +37-5-27-29209; e-mail: info@mii.vu.lt; Web site: https://infedu.vu.lt/journal/INFEDU
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01