Synergistic Effects of Expectancy and Value on Homework Engagement: The Case for a Within-Person Perspective

Changes in Academic Self-efficacy and Value and Crossover of Burnout Among Adolescent Students: A Two-wave Longitudinal Study

Previous research has identified the crossover of burnout among spouses or colleagues in workplaces, but little is known about how burnout crosses over from one student to another. This two-wave longitudinal study examined the mediating effects of changes in academic self-efficacy and value in the crossover of burnout among adolescent students based on the Expectancy-Value Theory. Data were collected from 2346 Chinese high school students (Mage = 15.60, S = 0.82; 44.16% boys) over a period of 3 months. The results reveal that after controlling for T1 student burnout, T1 friend burnout negatively predicts T1-T2 changes in academic self-efficacy and value (intrinsic value, attachment value, and utility value), which in turn negatively predict T2 student burnout. Thus, changes in academic self-efficacy and value completely mediate the crossover of burnout among adolescent students. These findings highlight the importance of taking into account the decline of academic motivation in understanding the crossover of burnout.

Motivational profiles of kindergarten teachers in minority areas of China and their association with outcomes

Academic discourses regarding teacher motivation have been on-going for decades for those who teach in ethnic minority areas. Yet research findings failed to provide a consistent conclusion regarding if kindergarten teachers’ motivation pattern would vary based on a case-to-case scenario. Therefore, further studies are needed to probe the motivation patterns among this population. The study firstly examined kindergarten teachers’ motivational profiles based on Expectancy Value Theory (EVT), and then examined how teachers’ motivation related to outcome variables (work engagement, workplace wellbeing, and retention intention). Participants included 1,199 kindergarten teachers from ethnic minority areas in China. Latent profile analysis identified three motivation profiles for teachers: low value-high cost (profile 1), moderate all (profile 2), and high value-low cost (profile 3). Teacher with different motivation profiles had significant differences in work engagement, workplace wellbeing, and retention intention. In addition, chain mediation analysis revealed that work engagement and workplace wellbeing mediated the relationship between motivation profiles and retention intention. The implications of the findings for study are discussed.

Conscientiousness and Cognitive Ability as Predictors of Academic Achievement: Evidence of Synergistic Effects From Integrative Data Analysis

Cognitive ability is the most powerful predictor of academic achievement. However, increasing attention is being paid to the role of personality traits in students’ academic achievement. Results indicate incremental effects beyond cognitive ability, especially for conscientiousness. Investigating the interplay of conscientiousness and cognitive ability can increase understanding of students’ academic achievement and learning. This study examined whether there are interaction effects of a synergistic or compensatory nature. We applied the approach of integrative data analysis, using four highly powered data sets with a total of 18,637 upper secondary school students in Germany to investigate this research question across four different achievement measures and three educational domains (i.e., school subjects). We used an integrative approach and pooled the results across the four samples to obtain an average estimate of the hypothesized interaction effects. Findings support a small synergistic interaction, indicating that conscientiousness moderates the association between cognitive ability and achievement. This means conscientiousness can enhance the positive effects of cognitive ability. In conclusion, results highlight the role of the type of academic measure used and the domain investigated in understanding how personality and achievement are related, providing evidence of the interplay between effort-related traits such as conscientiousness and cognitive ability.

Is it still worth it? Applying expectancy-value theory to investigate the intraindividual motivational process of forming intentions to drop out from university

The intraindividual process of study dropout, from forming dropout intention to deregistration, is of motivational nature. Yet typical studies investigate interindividual differences, which do not inform about intraindividual processes. Our study focused on the intraindividual process of forming dropout intention, and applied expectancy-value theory to analyze its motivational underpinnings. To expand research, we considered associations of intraindividual deviations in expectancy, intrinsic value, attainment value, utility value, and cost to intraindividual deviations in dropout intention. A total of 326 undergraduate students of law and mathematics rated motivational variables and dropout intention three times from semester start to the final exam period. Multilevel regression analyses revealed that intraindividual changes in intrinsic value, attainment, and cost, but not in expectancy and utility, related to intraindividual changes in dropout intention. Further, we considered students’ demographics as moderators. Only age moderated the association between intrinsic value and dropout intention. Our results stress the crucial role of certain value components, including cost, for emerging dropout intention.

Understanding behavioural engagement and achievement: The roles of teaching practices and student sense of competence and task value

BACKGROUND

Different teaching practices, such as autonomy support and structure, provide students with a positive learning context supporting their engagement, which can operate through their underlying motivation, including sense of competence and task value.

AIMS

This study aims at investigating the best configuration (unique or synergistic) between autonomy support and structure to support student behavioural engagement, including compliance, participation, and misbehaviour, and reading achievement. A second objective is to assess students' sense of competence and task value as mediators linking teaching practices to student engagement and achievement.

SAMPLE

The samples included 1,666 7th-grade students and their 85 teachers. Students answered questionnaires and tests at the beginning and the end of the school year.

METHODS

Students' perceptions of the use of autonomy support and structure by their Language Arts teacher were aggregated at the classroom level. Students rated their sense of competence and task value in Language Arts class. Twice during the school year, they also reported three facets of their behavioural engagement (compliance, participation, and misbehaviour) and answered a reading comprehension test. Multilevel path analyses using Mplus7 allowed accounting for the nested structure of data.

RESULTS

Student sense of competence mediated the association of student classroom-aggregated perceptions of teacher structure and autonomy support with self-reported participation in the classroom. Task value mediated the association between both teaching practices and student misbehaviour and compliance, as reported by students. Sense of competence was directly associated with later reading achievement, but the indirect effect of teaching practices was not significant. We found no significant interaction (synergistic effect) between teacher autonomy support and structure.

CONCLUSION

Student classroom-aggregated perception of teacher autonomy support and structure is important to nurture behavioural engagement. However, we found no extra benefit of combining these two dimensions of teaching practices. The processes linking these teaching practices to the three facets of student behavioural engagement were different. As such, to support the various aspects of student engagement, the actions of teachers, as reported by their students, should tap into the mechanisms that are most strongly related to each type of behaviour.

Individual Precursors of Student Homework Behavioral Engagement: The Role of Intrinsic Motivation, Perceived Homework Utility and Homework Attitude

Currently, the concept of engagement is crucial in the field of learning and school achievement. It is a multidimensional concept (e.g., behavioral, emotional, and cognitive dimensions) that has been widely used as a theoretical framework to explain the processes of school engagement and dropout. However, this conceptual framework has been scarcely used in the field of homework. The aim of the present study was to analyze the role of intrinsic motivation, perceived homework utility, and personal homework attitude as precursors of student homework engagement (behavioral engagement) and, at the same time, how such engagement is the precursor of academic achievement. Seven hundred and thirty students of Compulsory Secondary Education (CSE) (7th to 10th grade) from fourteen schools northern Spain participated. A structural equation model was elaborated on which intrinsic motivation, perceived utility and attitude were observed variables, and student engagement (time spent on homework, time management, and amount of teacher-assigned homework done) and academic achievement (Mathematics, Spanish Language, English Language, and Social Science) were latent variables. The results reveal that (i) intrinsic motivation is a powerful precursor of student behavioral engagement (also perceived utility and attitude, although to a lesser extent), and (ii) academic achievement is closely linked to the level of student engagement, qualifying the results of many of the previous studies conducted from a task-centered perspective (as opposed to a person-centered perspective).

Pre-service teachers' perceived value of general pedagogical knowledge for practice: Relations with epistemic beliefs and source beliefs

Pre-service teachers tend to devalue general pedagogical knowledge (GPK) as a valid source for deriving successful teaching practices. The present study investigated beliefs about knowledge sources and epistemic beliefs as predictors for students’ perceived value of GPK. Three pre-registered hypotheses were tested. We expected beliefs that GPK originates from scientific sources to entail a devaluation of GPK (Hypothesis 1). Concerning epistemic beliefs, we expected absolute beliefs to positively, and multiplistic beliefs to negatively predict pre-service teachers’ perceived practical value of GPK (Hypothesis 2). Finally, we expected relationships between epistemic beliefs and pre-service teachers’ perceived practical value of GPK to be confounded by epistemic trustworthiness, perceived topic-specific consistency and topic-specific familiarity (Hypothesis 3). In a study using a split plot design, 365 pre-service teachers were presented with four texts on different educational research topics. For each topic, three text versions were constructed. Even though they were invariant in content, these versions varied in a way that the results were allegedly generated by a practitioner, an expert or by means of a scientific study. Unexpectedly, results showed that research findings allegedly generated by means of a scientific study were associated with a higher perceived value of (topic-specific) GPK for practice (Hypothesis 1). As expected, the perceived value of GPK for practice was predicted by topic-specific multiplism and domain-specific absolutism (Hypothesis 2). These predictive effects were confounded by expertise evaluations of the source and the consistency of prior beliefs with the presented research results (Hypothesis 3). In summary, our results suggest that source beliefs might not be responsible for the devaluation of GPK, but that beliefs on the nature and structure of GPK (i.e., epistemic beliefs) might play an even more important role in this respect. Implications for research and practice are discussed.

Using wise interventions to motivate deliberate practice

Deliberate practice leads to world-class excellence across domains. In the current investigation, we examined whether psychologically "wise" interventions targeting expectancies and values-stock antecedents of ordinary effortful behaviors-could motivate nonexperts to engage in deliberate practice and improve their achievement. As a preliminary, we developed and validated a novel task measure of deliberate practice and confirmed its association with (a) expectancy-value beliefs, and (b) achievement in the nonexpert setting (Study 1). Next, across 4 longitudinal, randomized-controlled, field experiments, we intervened. Among lower-achievers, wise deliberate practice interventions improved math performance for 5th and 6th graders (Study 2), end-of-semester grades for undergraduates (Study 3), and end-of-quarter grades for 6th graders (Study 4); the same pattern of results emerged in end-of-quarter grades for 7th graders (Study 5). Following the intervention, expectancy-value beliefs and deliberate practice improved for 1 month (Study 4), but not 4 (Study 5). Treatment proved beneficial over and above 2 control conditions: 1 that taught standard study skills (Studies 2 and 3), and 1 that discussed deep interests, generalized motivation, and high achievement (Studies 4 and 5). Collectively, these findings provide preliminary support for the heretofore untested hypothesis that deliberate practice submits to the same laws that govern typical forms of effortful behavior, and that wise interventions that tap into these laws can spur short-term gains in adaptive beliefs, deliberate practice, and objectively measured achievement. (PsycINFO Database Record

The Standardization of Linear and Nonlinear Effects in Direct and Indirect Applications of Structural Equation Mixture Models for Normal and Nonnormal Data

The application of mixture models to flexibly estimate linear and nonlinear effects in the SEM framework has received increasing attention (e.g., Jedidi et al., 1997b; Bauer, 2005; Muthén and Asparouhov, 2009; Wall et al., 2012; Kelava and Brandt, 2014; Muthén and Asparouhov, 2014). The advantage of mixture models is that unobserved subgroups with class-specific relationships can be extracted (direct application), or that the mixtures can be used as a statistical tool to approximate nonnormal (latent) distributions (indirect application). Here, we provide a general standardization procedure for linear and nonlinear interaction and quadratic effects in mixture models. The procedure can also be applied to multiple group models or to single class models with nonlinear effects like LMS (Klein and Moosbrugger, 2000). We show that it is necessary to take nonnormality of the data into account for a correct standardization. We present an empirical example from education science applying the proposed procedure.

A general non-linear multilevel structural equation mixture model

In the past 2 decades latent variable modeling has become a standard tool in the social sciences. In the same time period, traditional linear structural equation models have been extended to include non-linear interaction and quadratic effects (e.g., Klein and Moosbrugger, 2000), and multilevel modeling (Rabe-Hesketh et al., 2004). We present a general non-linear multilevel structural equation mixture model (GNM-SEMM) that combines recent semiparametric non-linear structural equation models (Kelava and Nagengast, 2012; Kelava et al., 2014) with multilevel structural equation mixture models (Muthén and Asparouhov, 2009) for clustered and non-normally distributed data. The proposed approach allows for semiparametric relationships at the within and at the between levels. We present examples from the educational science to illustrate different submodels from the general framework.

Analyzing average and conditional effects with multigroup multilevel structural equation models

Conventionally, multilevel analysis of covariance (ML-ANCOVA) has been the recommended approach for analyzing treatment effects in quasi-experimental multilevel designs with treatment application at the cluster-level. In this paper, we introduce the generalized ML-ANCOVA with linear effect functions that identifies average and conditional treatment effects in the presence of treatment-covariate interactions. We show how the generalized ML-ANCOVA model can be estimated with multigroup multilevel structural equation models that offer considerable advantages compared to traditional ML-ANCOVA. The proposed model takes into account measurement error in the covariates, sampling error in contextual covariates, treatment-covariate interactions, and stochastic predictors. We illustrate the implementation of ML-ANCOVA with an example from educational effectiveness research where we estimate average and conditional effects of early transition to secondary schooling on reading comprehension.

Evaluation of model fit in nonlinear multilevel structural equation modeling

Evaluating model fit in nonlinear multilevel structural equation models (MSEM) presents a challenge as no adequate test statistic is available. Nevertheless, using a product indicator approach a likelihood ratio test for linear models is provided which may also be useful for nonlinear MSEM. The main problem with nonlinear models is that product variables are non-normally distributed. Although robust test statistics have been developed for linear SEM to ensure valid results under the condition of non-normality, they have not yet been investigated for nonlinear MSEM. In a Monte Carlo study, the performance of the robust likelihood ratio test was investigated for models with single-level latent interaction effects using the unconstrained product indicator approach. As overall model fit evaluation has a potential limitation in detecting the lack of fit at a single level even for linear models, level-specific model fit evaluation was also investigated using partially saturated models. Four population models were considered: a model with interaction effects at both levels, an interaction effect at the within-group level, an interaction effect at the between-group level, and a model with no interaction effects at both levels. For these models the number of groups, predictor correlation, and model misspecification was varied. The results indicate that the robust test statistic performed sufficiently well. Advantages of level-specific model fit evaluation for the detection of model misfit are demonstrated.