Perceived learning environment and students' emotional experiences: A multilevel analysis of mathematics classrooms.
TL;DR: Heckhausen et al. as discussed by the authors used a multilevel approach to analyse relationships between perceived classroom environments and emotions in mathematics and found that environmental characteristics conveying control and value to the students would be related to their experience of enjoyment, anxiety, anger, and boredom in mathematics.
About: This article is published in Learning and Instruction.The article was published on 2007-10-01 and is currently open access. It has received 396 citations till now. The article focuses on the topics: Multilevel model & Boredom.
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TL;DR: In this article, the structural relationships between prior achievement, control and value beliefs, and emotions were assumed to be invariant across girls and boys in spite of hypothesized mean level differences of beliefs and emotions across genders.
Abstract: This study analyzed gender differences in achievement emotions in the domain of mathematics. Based on Pekrun’s (2000, 2006) controlvalue theory of achievement emotions, we hypothesized that there are gender differences in mathematics emotions due to the students’ different levels of control and value beliefs in mathematics, even when controlling for prior achievement. The structural relationships between prior achievement, control and value beliefs, and emotions were assumed to be invariant across girls and boys in spite of hypothesized mean level differences of beliefs and emotions across genders. The emotions and beliefs of 1,036 male and 1,017 female 5th grade students were assessed by self-report measures, and their prior mathematics achievement was assessed by academic grades. Even though girls and boys had received similar grades in mathematics, girls reported significantly less enjoyment and pride than boys, but more anxiety, hopelessness and shame. Findings suggested that the female emotional pattern was due to the girls’ low competence beliefs and domain value of mathematics, combined with their high subjective values of achievement in mathematics. Multiple-group comparisons confirmed that the structural relationships between variables were largely invariant across the genders.
413 citations
TL;DR: This article showed that conclusions about the impact of learning environments can be substantially affected by the choice of a specific centering option for the individual student ratings, and that the reliability of aggregated student ratings must be routinely assessed before these perceptions are related to outcome variables.
382 citations
TL;DR: In this paper, the authors investigated adolescents' developmental trajectories of mathematics interest and explored related effects of gender, family, and school context, finding that a downward trend of students' mathematics interest plateaued in later years, with high variability in mean levels, but little variability in the shape of the growth trajectories.
Abstract: This study investigated adolescents’ developmental trajectories of mathematics interest and explored related effects of gender, family, and school context.Latent growth curvemodelingwas usedtoanalyzelongitudinaldataofN 53,193students(51%female)fromgrades5to9fromall3 ability tracks of the German state school system. Annual assessments involved student questionnaires on interest in mathematics, perceptions of classroom characteristics (classroom values for mathematics, mathematics teacher enthusiasm), as well as parent questionnaires regarding family values for mathematics. Results indicated a downward trend of students’ mathematics interest that plateaued in later years, with high variability in mean levels, but little variability in the shape of the growth trajectories. Boys reported higher mathematics interest than girls, but similar downward growth trajectories. Students from the lowest ability track showed more favorable interest trajectories than students from the middle and highest tracks. Family values andclassroomcharacteristicswerepositivelyrelatedtowithin-personlevelsofinterestovertime and to average individual levels of interest, but not to growth parameters. Theoretical and practical implications are discussed.
365 citations
Cites background from "Perceived learning environment and ..."
...In cross-sectional analyses, class mean scores of classroom value for mathematics as measured with this scale have been shown to relate positively to student enjoyment in mathematics (Frenzel et al., 2007b; Pekrun et al., 2006)....
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...In a cross-sectional study relating aspects of classroom climate to student enjoyment in mathematics, Frenzel, Pekrun, and Goetz (2007b) reported that classaggregated student perceptions of classroom values for mathematics were significantly positively related to students’ mathematics enjoyment....
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01 Jan 2010
TL;DR: Handbook of gender research in psychology as mentioned in this paper, Handbook of gender studies in psychology, and Handbook of Gender Research in psychology (HGWR), 2011., کتابخانه دیجیتال جندی شاپور اهواز
Abstract: Handbook of gender research in psychology. , Handbook of gender research in psychology. , کتابخانه دیجیتال جندی شاپور اهواز
331 citations
TL;DR: In this article, a theoretical model linking boredom and academic achievement is proposed based on Pekrun's (2006) control-value theory of achievement emotions, the model posits that boredom and achievement reciprocally influence each other over time.
Abstract: A theoretical model linking boredom and academic achievement is proposed. Based on Pekrun’s (2006) control-value theory of achievement emotions, the model posits that boredom and achievement reciprocally influence each other over time. Data from a longitudinal study with college students (N = 424) were used to examine the hypothesized effects. The study involved 5 assessments of students’ boredom and test performance during a university course spanning an entire academic year. Structural equation modeling was used to examine effects of boredom on achievement, and vice versa. The results show that boredom had consistently negative effects on subsequent performance, and performance had consistently negative effects on subsequent boredom, while controlling for students’ gender, age, interest, intrinsic motivation, and prior achievement. These results provide robust evidence for the proposed links between boredom and achievement and support systems-theoretical perspectives on the dynamics of emotions and achievement. From a broader educational perspective, the findings imply that researchers and practitioners alike should focus attention on boredom as an important, yet often overlooked, academic emotion.
255 citations
References
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Book•
03 Mar 1992TL;DR: The Logic of Hierarchical Linear Models (LMLM) as discussed by the authors is a general framework for estimating and hypothesis testing for hierarchical linear models, and it has been used in many applications.
Abstract: Introduction The Logic of Hierarchical Linear Models Principles of Estimation and Hypothesis Testing for Hierarchical Linear Models An Illustration Applications in Organizational Research Applications in the Study of Individual Change Applications in Meta-Analysis and Other Cases Where Level-1 Variances are Known Three-Level Models Assessing the Adequacy of Hierarchical Models Technical Appendix
23,126 citations
TL;DR: This chapter discusses Hierarchical Linear Models in Applications, Applications in Organizational Research, and Applications in the Study of Individual Change Applications in Meta-Analysis and Other Cases Where Level-1 Variances are Known.
19,282 citations
Book•
01 Apr 2002
TL;DR: This work focuses on the development of a single model for Multilevel Regression, which has been shown to provide good predictive power in relation to both the number of cases and the severity of the cases.
Abstract: 1. Introduction to Multilevel Analysis. 2. The Basic Two-Level Regression Model. 3. Estimation and Hypothesis Testing in Multilevel Regression. 4. Some Important Methodological and Statistical Issues. 5. Analyzing Longitudinal Data. 6. The Multilevel Generalized Linear Model for Dichotomous Data and Proportions. 7. The Multilevel Generalized Linear Model for Categorical and Count Data. 8. Multilevel Survival Analysis. 9. Cross-classified Multilevel Models. 10. Multivariate Multilevel Regression Models. 11. The Multilevel Approach to Meta-Analysis. 12. Sample Sizes and Power Analysis in Multilevel Regression. 13. Advanced Issues in Estimation and Testing. 14. Multilevel Factor Models. 15. Multilevel Path Models. 16. Latent Curve Models.
5,395 citations
"Perceived learning environment and ..." refers methods in this paper
...Since our sample was adequately large (both individuals and groups), we derived these correlations using Muthén’s pseudo-balanced approach to the scaled between-group covariance matrix (see Hox, 2002, p. 228; and Muthén, 2004, p. 44ff)....
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Book•
01 Jan 1986
TL;DR: For a long time, the authors have had the gnawing desire to convey the broad motivational significance of the attributional conception that I have espoused and to present fully the argument that this framework has earned a rightful place alongside other leading theories of motivation.
Abstract: For a long time I have had the gnawing desire to convey the broad motivational sig nificance of the attributional conception that I have espoused and to present fully the argument that this framework has earned a rightful place alongside other leading theories of motivation. Furthermore, recent investigations have yielded insights into the attributional determinants of affect, thus providing the impetus to embark upon a detailed discussion of emotion and to elucidate the relation between emotion and motivation from an attributional perspective. The presentation of a unified theory of motivation and emotion is the goal of this book. My more specific aims in the chapters to follow are to: 1) Outline the basic princi ples that I believe characterize an adequate theory of motivation; 2) Convey what I perceive to be the conceptual contributions of the perspective advocated by my col leagues and me; 3) Summarize the empirical relations, reach some definitive con clusions, and point out the more equivocal empirical associations based on hypotheses derived from our particular attribution theory; and 4) Clarify questions that have been raised about this conception and provide new material for still further scrutiny. In so doing, the building blocks (if any) laid down by the attributional con ception will be readily identified and unknown juries of present and future peers can then better determine the value of this scientific product."
4,327 citations
"Perceived learning environment and ..." refers background in this paper
...Yet, with the exception of test anxiety (e.g., Zeidner, 1998) and Weiner’s research on attributional antecedents of achievement-related emotions (e.g., Weiner, 1986 ), educational research has paid comparatively little regard to emotions, in particular to positive emotions (see Pekrun, Goetz, Titz, & Perry, 2002a)....
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...…with the exception of test anxiety (e.g., Zeidner, 1998) and Weiner’s research on attributional antecedents of achievement-related emotions (e.g., Weiner, 1986), educational research has paid comparatively little regard to emotions, in particular to positive emotions (see Pekrun, Goetz, Titz, &…...
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4,163 citations