This article compares different approaches for estimating cross-lagged effects with a cross-lagged panel design under a causal inference perspective. We distinguish between models that rely on no ...unmeasured confounding (i.e., observed covariates are sufficient to remove confounding) and latent variable-type models (e.g., random intercept cross-lagged panel model) that use parametric assumptions to adjust for unmeasured time-invariant confounding by including additional latent variables. Simulation studies confirm that the cross-lagged panel model provides biased estimates of the cross-lagged effect in the presence of unmeasured confounding. However, the simulations also show that the latent variable-type approaches strongly depend on the specific parametric assumptions, and produce biased estimates under different data-generating scenarios. Finally, we discuss the role of the longitudinal design and the limitations of assessing model fit for estimating cross-lagged effects.
Enjoyment is one of the most relevant and frequently experienced discrete emotions for both teachers and students in classroom learning contexts. Based on theories of emotion transmission between ...interaction partners, we propose a reciprocal effects model linking teachers' and students' enjoyment in class. The model suggests that there are positive reciprocal links between teachers' and students' enjoyment and that these links are mediated by teachers' and students' observations of each other's classroom behaviors. The model was tested using 3-wave longitudinal data collected across the 1st 6 months of a school year from N = 69 teachers (78% female) and their 1,643 students from Grades 5 to 10 (57% female). A multilevel structural equation model confirmed our mediation hypotheses. Teacher enjoyment at the beginning of the school year (Time 1 T1) was positively related to student perceptions of teachers' enthusiasm during teaching 4 weeks later (T2), which was positively related to student enjoyment at midterm (T3). Further, student enjoyment at T1 was positively related to teacher perceptions of their students' engagement in class at T2, which was positively related to teacher enjoyment at T3. This study is the first to provide longitudinal evidence of reciprocal emotion transmission between teachers and students. Implications for future research and teacher training are discussed.
Educational Impact and Implications Statement
Researchers, educational policymakers, and the general public agree that teachers should radiate enjoyment and thus "infect" their students with excitement about learning. However, emotional contagion in human interaction is not a one-way street. In this research, we proposed that teachers' and students' enjoyment in class are reciprocally linked via mutual social perceptions of how enthusiastic and engaged the interaction partners are. We tested our assumptions using 3-wave longitudinal data collected from approximately 70 classrooms (teachers and their students) across the first 6 months of a school year. The results fully confirmed our expectations. Our findings imply that teachers' emotional experiences in class depend on their students' emotions as much as students' emotional experiences depend on their teachers'. It thus seems that for classrooms to be enjoyable places for everyone involved, one must consider the needs and desires of both learners and teachers.
Two studies were conducted to examine gender differences in trait (habitual) versus state (momentary) mathematics anxiety in a sample of students (Study 1: N = 584; Study 2: N = 111). For trait math ...anxiety, the findings of both studies replicated previous research showing that female students report higher levels of anxiety than do male students. However, no gender differences were observed for state anxiety, as assessed using experience-sampling methods while students took a math test (Study 1) and attended math classes (Study 2). The discrepant findings for trait versus state math anxiety were partly accounted for by students' beliefs about their competence in mathematics, with female students reporting lower perceived competence than male students despite having the same average grades in math. Implications for educational practices and the assessment of anxiety are discussed.
•Students with higher interest showed higher achievement in five domains.•Students showed higher achievement in domains they were more interested in.•Interest effects were found beyond effects of ...general cognitive abilities and SES.•The effects generalized across grades and test-scores.•The relation between achievement and interest was higher in math compared to German.
We examined the incremental effect of academic interest on achievement beyond general cognitive ability and students’ background characteristics in five domains (math, German, biology, chemistry, and physics). We analyzed a nationally representative German dataset of 39,192 ninth-grade students and found a unique effect of interest over and above the other predictors across the five domains, both for class grades and standardized test scores. The effect was present between persons (in a given domain, students with higher interest showed higher achievement) and within persons (the same student showed a higher achievement in domains she/he was more interested in). The effects were stronger for grades than test scores and stronger in math than in other domains. The results emphasize the positive relation between interest and academic achievement in different domains. Furthermore, they expand the literature by emphasizing the role of the achievement measure and the domain as moderators of the interest–achievement relation and by showing that interest can predict both inter- and intraindividual variation in achievement.
With small to modest sample sizes and complex models, maximum likelihood (ML) estimation of confirmatory factor analysis (CFA) models can show serious estimation problems such as non-convergence or ...parameter estimates outside the admissible parameter space. In this article, we distinguish different Bayesian estimators that can be used to stabilize the parameter estimates of a CFA: the mode of the joint posterior distribution that is obtained from penalized maximum likelihood (PML) estimation, and the mean (EAP), median (Med), or mode (MAP) of the marginal posterior distribution that are calculated by using Markov Chain Monte Carlo (MCMC) methods. In two simulation studies, we evaluated the performance of the Bayesian estimators from a frequentist point of view. The results show that the EAP produced more accurate estimates of the latent correlation in many conditions and outperformed the other Bayesian estimators in terms of root mean squared error (RMSE). We also argue that it is often advantageous to choose a parameterization in which the main parameters of interest are bounded, and we suggest the four-parameter beta distribution as a prior distribution for loadings and correlations. Using simulated data, we show that selecting weakly informative four-parameter beta priors can further stabilize parameter estimates, even in cases when the priors were mildly misspecified. Finally, we derive recommendations and propose directions for further research.
Students evaluate their achievement in a specific domain in relation to their achievement in other domains and form their self-concepts accordingly. These comparison processes have been termed ...dimensional comparisons and shown to be an important source of academic self-concepts in addition to social and temporal comparisons. Research on the internal/external frame of reference model (I/E model) has frequently found negative effects of students' achievement on their academic self-concept between different scholastic domains (mathematics and the language of instruction) that are interpreted as contrast effects of dimensional comparisons. There is mixed evidence with regard to whether negative contrast effects or positive assimilation effects occur when students compare their achievement in domains that are more similar. In this study, we extended the original I/E model with 3 science domains (biology, chemistry, and physics). Using structural equation modeling, we analyzed the domain-specific self-concepts, grades, and test scores of a representative sample of 9th-grade students in Germany (N = 20,050) across 5 domains. Mathematics, physics, and chemistry showed contrast effects to German, whereas small assimilation effects were found between mathematics, physics, and chemistry. This effect pattern was present for both grades and test scores. Achievement in mathematics and the language of instruction affected self-concepts in the sciences, whereas achievement in the sciences had no effect on self-concepts in other subjects. The results support the hypotheses derived from dimensional comparison theory that both contrast and assimilation effects can result from dimensional comparisons and that the 3 science subjects are affected differentially by these comparisons.
Digital tests make it possible to identify student effort by means of response times, specifically, unrealistically fast responses that are defined as rapid-guessing behavior (RGB). In this study, we ...used latent class and growth curve models to examine (1) how student characteristics …) are related to the onset point of RGB and its development over the course of a test session .... Further, we examined (2) the extent to which repeated ratings of task enjoyment … are related to the onset and the development of RGB over the course of the test. For this purpose, we analyzed data from … students from fifth and sixth grades in Germany …. … The results show that students’ gender was not significantly related to RGB but that students’ school type (which is known to be closely related to academic abilities in the German school system), general cognitive abilities, and their working-memory capacity were significant predictors of an early RGB onset and a stronger RGB increase across testing time. Students’ initial rating of task enjoyment was associated with RGB, but only a decline in students’ task enjoyment was predictive of earlier RGB onset. Overall, non-academic-school attendance was the most powerful predictor of RGB, together with students’ working-memory capacity. The present findings add to the concern that there is an unfortunate relation between students’ test-effort investment and their academic and general cognitive abilities. This challenges basic assumptions about motivation-filtering procedures and may threaten a valid interpretation of results from large-scale testing programs that rely on school-type comparisons. (Orig.).
Amino acid analysis, commonly done by acid hydrolysis of proteins and HPLC analysis, faces one major problem: incomplete hydrolysis of stable amino acids and degradation of unstable amino acids are ...causing amino acid losses. As a result, amino acid recovery of unknown samples cannot be estimated. Some methods have been reported for correction of these factors in the past. This paper shows an improved and integrated method to overcome this problem by using stillage as an exemplary unknown sample material. Amino acid recovery from an unknown sample can be estimated by standard addition of a known protein. If the sample does not cause matrix effects during amino acid hydrolysis, recoveries of the standard protein are transferable to the sample. If the sample does cause matrix effects correction of amino acid losses can instead be done by determination of hydrolysis kinetics. Therefore, first order kinetics were used for amino acids that undergo degradation during hydrolysis. For all stable amino acids higher order kinetics were used, a novel approach to determine hydrolysis kinetics. The presented method can be a helpful tool for scientists who want to optimize amino acid analysis of a particular biomass substrate.
One major aim of international large-scale assessments (ILSA) like PISA is to monitor changes in student performance over time. To accomplish this task, a set of common items (i.e., link items) is ...repeatedly administered in each assessment. Linking methods based on item response theory (IRT) models are used to align the results from the different assessments on a common scale. This work employs the one-parameter logistic (1PL) and the two-parameter logistic (2PL) IRT models as scaling models for dichotomous item response data. The present article discusses different types of trend estimates in country means and standard deviations for countries in ILSA. These types differ in three aspects. First, the trend can be assessed by an indirect or direct linking approach for linking a country’s performance at an international metric. Second, the linking for the trend estimation can rely on either all items or only the link items. Third, item parameters can be assumed to be invariant or noninvariant across countries. It is shown that the most often employed trend estimation methods of original trends and marginal trends can be conceived as particular cases of indirect and direct linking approaches, respectively. Through a simulation study and analytical derivations, it is demonstrated that trend estimates using a direct linking approach and those that rely on only link items outperformed alternatives for the 1PL model with uniform country differential item functioning (DIF) and the 2PL model with uniform and nonuniform country DIF. We also illustrated the performance of the different scaling models for assessing the PISA trend from PISA 2006 to PISA 2009 in the cognitive domains of reading, mathematics, and science. In this empirical application, linking errors based on jackknifing testlets were utilized that adequately quantify DIF effects in the uncertainty of trend estimates.
In this study, the authors investigated the longitudinal interplay between personality and achievement and the effect of family cohesion on relative change in personality and achievement in ...adolescence. Using longitudinal data from the National Educational Panel Study ..., the authors estimated latent cross-lagged panel models that included personality traits, different achievement indicators, and family cohesion. There were three main findings. First, the authors replicated previous cross-sectional personality-achievement associations. Second, after accounting for covariates and stability effects, all personality traits (except agreeableness) were related to change in at least one achievement indicator. Third, student-rated family cohesion was associated with better grades (in German) 2 years later but showed no effects on personality change. The findings demonstrate that, when explored longitudinally, personality shows only small effects on achievement change and vice versa in adolescence. the authors emphasize the need for further research to disentangle the specific processes behind these associations. (Orig.).
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