Profiling secondary school students in mathematics and German language arts using learning-relevant cognitive and motivational-affective characteristics. (June 2021)

• Record Type: Journal Article
• Authors: Kosel, Christian; Wolter, Ilka; Seidel, Tina
• Is Part Of: Learning and instruction. Volume 73(2021)
• Publication Date: 2021-06
• Subjects: Student characteristics -- Academic achievement -- Latent profile analysis -- Person-centered research -- Individual differences; Learning -- Periodicals; Teaching -- Periodicals; Apprentissage -- Périodiques; Enseignement -- Périodiques; Learning; Teaching; Periodicals; Electronic journals; 370.1
• DOI: 10.1016/j.learninstruc.2020.101434
• Languages: English
• ISSNs: 0959-4752

Abstract

Abstract: This study aims to investigate how learning-relevant cognitive and motivational-affective characteristics, such as pre-knowledge and interest, are intrapersonally connected within students. This person-centered research thereby adds to prior findings by simultaneously analyzing student profiles in the domains of mathematics and German language arts on all school tracks within the German secondary school system. In a subsample of the German National Educational Panel Study involving 10, 025 ninth-grade students, a latent profile analysis is conducted to identify student profiles. The results reveal five student profiles in German language arts (strong, struggling [motivation], struggling [cognitive], over, - underestimating) and five student profiles in mathematics (strong, struggling, over, - underestimating, average-uninterested). One of the student profiles, the underestimating student profile, is found most frequently in both domains (Ø32%). Students from higher school tracks, and especially females, are most often allocated to an underestimating profile in both domains. Lastly, the results indicate domain-specific student profiles. Highlights: Five latent student profiles are found in mathematics and language arts. The 'underestimating' student profile is found most frequently in both domains. Females are more frequently profiled as underestimating students. The higher the school track, the more students tend to underestimate themselves.