Big Five personality traits, attitudes towards Artificial Intelligence and the use of AI solutions in foreign language learners
Big Five personality traits, attitudes towards Artificial Intelligence and the use of AI solutions in foreign language learners
Author(s): Czesław Kiński, Bartosz Kiński, Agata PrzyborowskaSubject(s): Foreign languages learning, Educational Psychology, Personality Psychology
Published by: Uniwersytet im. Adama Mickiewicza w Poznaniu
Keywords: foreign language learning; learner personality; Big Five; Artificial Intelligence; adaptation; learner attitudes;
Summary/Abstract: The main aim of the study is to investigate the relationship between foreign language learners' Big Five personality traits and their attitudes towards Artificial Intelligence (AI), as well as to examine the connection between those attitudes and learners' use of AI-generated solutions in their foreign language education. 429 foreign language university students were asked to complete an online questionnaire. Subsequently, statistical analysis of the data was carried out to obtain results, which indicated that conscientiousness and extraversion correlated positively with positive attitudes towards AI, while agreeableness, neuroticism and intellect/imagination correlated negatively with those attitudes. Furthermore, it was found that extraversion, conscientiousness and neuroticism were positively correlated with the frequency of AI usage in foreign language learning, while intellect/imagination was negatively correlated with both the frequency of AI usage and the perceived usefulness of AI tools in foreign language learning. Finally, the study revealed an association between the frequency of AI use and the perceived usefulness of AI-generated tools, as well as a strong direct effect of the frequency of AI usage in foreign language learning on attitudes towards AI. Overall, the use of AI-generated tools appears to be more dependent on the learner's attitudes towards AI than their personality traits.
Journal: Neofilolog
- Issue Year: 65/2025
- Issue No: 1
- Page Range: 65-83
- Page Count: 19
- Language: English
