Factors Enhancing Students’ Views on Artificial Intelligence


Abstract

Artificial Intelligence (AI) is now one of the most important and contemporary directions of development of science in an interdisciplinary context. The EU’s approach to artificial intelligence centres on excellence and trust, aiming to boost research and industrial capacity while ensuring safety and fundamental rights (A European approach to artificial intelligence). Strengthening the fostering excellence in AI will strengthen Europe’s potential to compete globally. Simultaneously not yet solved are a lot of challenges and issues. The problem raised in the article is to explore and analyse computer science and education students’ attitude to educational, social, and ethical aspects of AI implementation. The purpose is to discover and analyse computer science students and pedagogical attitude towards education, social-, and ethical aspects of AI implementation. Students of two faculties of the University of Silesia in Katowice, Poland, were asked to respond to a survey. They were mainly students of two specializations – Computer Science and Pedagogy. As many as 103 students have been surveyed. The Kruskal-Wallis tests were used for verification. The main issues studied were the students’ level of competence in AI, their awareness of AI applications in various areas of life and economy, and the importance of the AI field. The study also included the level of confidence towards AI and the level of anxiety towards AI. Various types of dependencies and connections between these aspects were investigated. The hypotheses were mostly confirmed. Finally, the article presents the discussion and main conclusions.


Keywords

Artificial Intelligence (AI); educational, social and ethical aspects; students of computer science and education; opinion; Kruskal-Wallis tests

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Published : 2023-10-30


Przybyła-KasperekM., Smyrnova-TrybulskaE., & KommersP. (2023). Factors Enhancing Students’ Views on Artificial Intelligence. International Journal of Research in E-Learning, 9(2), 1-42. https://doi.org/10.31261/IJREL.2023.9.2.03

Małgorzata Przybyła-Kasperek 
University of Silesia in Katowice  Poland
https://orcid.org/0000-0003-0616-9694
Eugenia Smyrnova-Trybulska  esmyrnova@us.edu.pl
University of Silesia in Katowice, Faculty of Arts and Sciences of Education  Poland
https://orcid.org/0000-0003-1227-014X
Piet Kommers 
University of Twente, Netherlands  Netherlands
https://orcid.org/0000-0002-4738-3016




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