TY - JOUR A1 - Hoferichter, Frances A1 - Laetsch, Alexander A1 - Lazarides, Rebecca A1 - Raufelder, Diana T1 - The big-fish-little-pond effect on the four facets of academic self-concept JF - Frontiers in psychology N2 - The social context plays a decisive role in the formation of the academic self-concept (ASC) and has been widely studied as the big-fish-little-pond-effect (BFLPE). This effect describes that comparable talented students in high-achieving school settings have a lower ASC compared to equally talented students attending low-achieving settings. Past research has focused on students’ domain-specific ASC, while little is known about the relation of achievement-related classroom compositions and the various facets of ASC. Additionally, BFLPE-research has been critiqued to build its theoretical frame on social comparison theory, without providing sufficient empirical support. To address this gap, we analyzed how the single student’s social, criterial, absolute, and individual ASC relate to class-level achievement of 8th graders. Applying Multilevel Structural Equation Modeling (MLSEM) we found that all facets of ASC were significantly related to average-class achievement, while student’s social ASC revealed the strongest associated. The results reveal explicitly that average-class achievement is strongly related to social comparison processes. KW - big-fish-little-pond-effect KW - social KW - criterial KW - absolute KW - individual academic self-concept (SESSKO) KW - high-ability tracked students Y1 - 2018 U6 - https://doi.org/10.3389/fpsyg.2018.01247 SN - 1664-1078 VL - 9 PB - Frontiers Research Foundation CY - Lausanne ER - TY - JOUR A1 - Lazarides, Rebecca A1 - Viljaranta, Jaana A1 - Aunola, Kaisa A1 - Nurmi, Jari-Erik T1 - Teacher ability evaluation and changes in elementary student profiles of motivation and performance in mathematics JF - Learning and individual differences N2 - The aim of this person-centered study is to identify the profiles of interest value, self-concept, and performance in the domain of mathematics among elementary school students and to examine the stability and changes in these profiles from grade 1 to grade 2. Teacher-reported evaluations of students' mathematical ability and gender were examined as predictors of changes in the student profiles. The sample consisted of 237 students (46.8% girls). The latent profile analysis identified four profiles: 1) low levels of interest value, medium levels of self-concept and performance; 2) low levels of interest value, self-concept and performance; 3) high levels of interest value, self-concept and performance; 4) low levels of self-concept and performance, and medium interest value. Boys and students whose teachers evaluated their abilities as high compared to others were less likely to change from profiles with high levels of interest value or self-concept to profiles with low levels of these factors. KW - Interest value KW - Self-concept KW - Performance KW - Latent profile analysis; Y1 - 2018 U6 - https://doi.org/10.1016/j.lindif.2018.08.010 SN - 1041-6080 SN - 1873-3425 VL - 67 SP - 245 EP - 258 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Lazarides, Rebecca A1 - Dietrich, Julia A1 - Taskinen, Paeivi H. T1 - Stability and change in students' motivational profiles in mathematics classrooms BT - The role of perceived teaching JF - Teaching and teacher education : an international journal of research and studies N2 - Person-centered research has shown that individuals can be assigned to different motivational profiles, but only scattered studies have addressed motivational profiles in specific domains. We investigated the stability and change in motivational profiles in mathematics classrooms and examined how perceived teaching predicted changes in profile membership. Data for this study stemmed from the PISA-I Plus study (N=6020). Latent profile analysis identified four motivational patterns: Medium, Low, High and Highly confident, hardly interested. Stability in profiles from grade 9 to 10 was typical. Instructional clarity and teaching for meaning predicted changes in profile membership. KW - motivation in mathematics KW - Latent profile analysis KW - Expectancy-value theory KW - Instructional quality KW - Adolescence Y1 - 2018 U6 - https://doi.org/10.1016/j.tate.2018.12.016 SN - 0742-051X VL - 79 SP - 164 EP - 175 PB - Elsevier CY - Oxford ER -