J 2024

Digital competences of social work degree students: an exploratory study based on a survey utilizing a triangulated voluntary sample

KYTKA, Lukáš

Basic information

Original name

Digital competences of social work degree students: an exploratory study based on a survey utilizing a triangulated voluntary sample

Authors

KYTKA, Lukáš

Edition

SOCIAL WORK EDUCATION, ENGLAND, ROUTLEDGE JOURNALS, TAYLOR & FRANCIS LTD, 2024, 0261-5479

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

50901 Other social sciences

Country of publisher

United Kingdom of Great Britain and Northern Ireland

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

Impact factor

Impact factor: 1.800 in 2022

Organization unit

Faculty of Social Studies

Keywords in English

DigComp; digital competence; digital literacy; information literacy; ICT literacy; e-social work; university students

Tags

International impact, Reviewed
Změněno: 8/8/2024 16:25, Mgr. Lukáš Kytka

Abstract

V originále

In various countries, the digital competences of social work students are inadequately addressed within existing curricular frameworks. Addressing this gap necessitates a more nuanced understanding of the prevailing digital competence trends among these students, though the methodology for such measurement remains ambiguous. This study investigates the applicability of the DigComp 2.2 model for gauging the digital competence levels of social work students. Employing a predominantly quantitative-exploratory approach, data were gathered in the Czech Republic and Slovakia through a 22-item questionnaire designed to assess the five digital competence areas outlined in the DigComp v2.2 framework (N = 151). The analysis revealed a spectrum of competence levels, ranging from insufficient to relatively high across different areas. These findings were benchmarked against the only other known study utilizing the DigComp model on the social work student demographic, which employed the model in a relatively less rigorous manner, showing considerable alignment. Based on these insights, recommendations for enhancing future research methodologies are proposed.