A Chaid Tree approach to motivation and academic performance in second language learning
Alfonso Abad Mancheño,
Roberto Sánchez-Cabrero and
Ana Cristina León Mejía
International Journal of Innovation and Learning, 2023, vol. 33, issue 1, 120-136
Abstract:
The findings of a study on the importance of affective motivation in learning a second language are presented in this article (L2). The study included 171 US university students who studied Spanish, German, Italian, or Japanese as a second language. The Dörnyei motivating model was used to create an online questionnaire, and the Chaid Tree predictive model outlined the most important variables that influence the Motivation to continue studying a second language. The findings show that the variables 'projection of intended effort' and 'ideal self' is both positively and significantly connected to students' academic achievement and their intent to enrol in future foreign language programs. The deontic self, or ought-to-self, on the other hand, had no significant correlation with any of the other factors studied. There were no significant differences in gender in the cross-sectional analysis of age and gender, but there was a negative and significant link between age and academic achievement, as well as a positive and significant association between age and predicted effort.
Keywords: motivation; foreign language learning; ideal self; ought-to-self; age; gender. (search for similar items in EconPapers)
Date: 2023
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.inderscience.com/link.php?id=127949 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:ids:ijilea:v:33:y:2023:i:1:p:120-136
Access Statistics for this article
More articles in International Journal of Innovation and Learning from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().