• Jennifer Meyer
  • Johanna Fleckenstein
  • Olaf Köller
Motivation predicts academic achievement beyond cognitive ability. Expectancy value theory (Eccles et al., 1983) is a widely accepted and powerful approach explaining academic achievement as well as educational choices and attainment. Recently, attention to the multiplicative term of expectancy and value beliefs has increased. Trautwein et al. (2012) reported a detrimental effect of high task value when expectancy beliefs were low. We aimed to replicate and extend their study by using a large, representative sample of students attending upper secondary school in the German federal state Schleswig-Holstein (N=3367). Following Trautwein et al. (2012), we applied latent interaction modelling to test whether the predictive value of expectancy value interactions differs for grades, final examinations, and standardized test scores as measures of achievement in two domains. We took the multi-dimensional structure of task value into consideration, analyzing the four components (attainment, intrinsic value, utility and cost) separately. Both a verbal and a non-verbal domain (English as a foreign language and mathematics) were investigated. Overall, the results supported those of Trautwein et al. (2012). However, our findings suggested measure- and domain-specificdifferences when using expectancy value beliefs and their interactions to predict academic achievement. Interaction terms predicted final examination results in both English and mathematics. Further, interaction effects were significant for grades in English but not mathematics. In general, effect sizes of multiplicative terms were small, especially in contrast to expectancy beliefs. Findings are discussed regarding the practical and conceptual importance of the multiplicative term in expectancy value theory applied in an educational setting.
Original languageEnglish
JournalContemporary Educational Psychology
Pages (from-to)58-74
Number of pages17
Publication statusPublished - 07.2019

    Research areas

  • Motivation, Expectancy value theory, Achievement measures, Latent interaction modelling

ID: 985363