2016
DOI: 10.1007/s11858-016-0827-3
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Interest development during the first year at university: do mathematical beliefs predict interest in mathematics?

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Cited by 18 publications
(8 citation statements)
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References 45 publications
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“…This decline has even occurred in innovative course designs that focused less on mathematical theory and more on mathematical thinking and problem solving (Kuklinski et al, 2018). Surprisingly, no such decline was found for future lower secondary school teachers, perhaps because their courses also included topics from mathematics education and real-life connections (Liebendörfer & Schukajlow, 2017). Students in such combined courses may see more utility value in the material, thus preventing their interest from dropping.…”
Section: Interestmentioning
confidence: 97%
“…This decline has even occurred in innovative course designs that focused less on mathematical theory and more on mathematical thinking and problem solving (Kuklinski et al, 2018). Surprisingly, no such decline was found for future lower secondary school teachers, perhaps because their courses also included topics from mathematics education and real-life connections (Liebendörfer & Schukajlow, 2017). Students in such combined courses may see more utility value in the material, thus preventing their interest from dropping.…”
Section: Interestmentioning
confidence: 97%
“…Interest is an important motivational construct that has recently gained considerable attention in mathematics education (Carmichael at al. 2017;Liebendörfer and Schukajlow 2017;Rellensmann and Schukajlow 2017;Ufer et al 2017). Interest represents a person-object relationship and is characterized by engagement and re-engagement with the content (Hidi and Renninger 2006;Krapp 2005).…”
Section: Motivationmentioning
confidence: 99%
“…• integrate traditional interindividual research strategies with intraindividual analysis to make it possible to understand both differences between students and the individual affective development of each student (Murayama et al in press); • use experimental and longitudinal study designs that make it possible to examine causal relations as well as mediational processes, moderator effects, and multiple levels of variables (see Lauerman et al 2017;Schütze et al 2017); • adapt novel assessment methods such as experience-sampling methods (Bieg et al 2017), physiological analysis, and automatic coding of emotion expression; • use analytical procedures to adequately model relations between variables within and across individual students and across multiple levels of educational institutions and systems, including statistical procedures to deal with missing data, such as multiple imputation or full information maximum likelihood (FIML) estimation (see e.g., Liebendörfer and Schukajlow 2017;Schütze et al 2017) and to deal with multi-level data structures, such as hierarchical modeling or methods to correct parameter estimates for the effects of nestedness (see e.g., Bieg et al 2017).…”
Section: Summary and Open Questionsmentioning
confidence: 99%
“…In Europe exist no consistent findings according to this specific research field. Liebendörfer and Schukajlow ( 2017 ) published results, with a small sample size (N = 92) from lower secondary school teachers, showing that students’ interest in mathematics remained stable during the first academic year in Germany. Xu et al ( 2021 ) show for students in Educational Sciences, Speech Pathology and Audiology in Belgium a decreasing of statistic interest over time by using a latent growth curve analysis for analysing data over two years.…”
Section: Interestmentioning
confidence: 99%
“…The preponderance of researchers reverts to the approaches and results of these studies. Longitudinal studies on higher education are the exception and can only be found very sporadically in this research field (Harackiewicz et al, 2002 ; Liebendörfer & Schukajlow, 2017 ).…”
Section: Introductionmentioning
confidence: 99%