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Background
Building on the Realistic Accuracy Model, this paper explores whether it is easier for teachers to assess the achievement of some students than others. Accordingly, we suggest that certain individual characteristics of students, such as extraversion, academic self-efficacy, and conscientiousness, may guide teachers' evaluations of student achievement, resulting in more appropriate judgements and a stronger alignment of assigned grades with students' actual achievement level (as measured using standardized tests).
Aims
We examine whether extraversion, academic self-efficacy, and conscientiousness moderate the relations between teacher-assigned grades and students' standardized test scores in mathematics.
Sample
This study uses a representative sample of N = 5,919 seventh-grade students in Germany (48.8% girls; mean age: M = 12.5, SD = 0.62) who participated in a national, large-scale assessment focusing on students' academic development.
Methods
We specified structural equation models to examine the inter-relations of teacher-assigned grades with students' standardized test scores in mathematics, Big Five personality traits, and academic self-efficacy, while controlling for students' socioeconomic status, gender, and age.
Results
The correlation between teacher-assigned grades and standardized test scores in mathematics was r = .40. Teacher-assigned grades more closely related to standardized test scores when students reported higher levels of conscientiousness (beta = .05, p = .002). Students' extraversion and academic self-efficacy did not moderate the relationship between teacher-assigned grades and standardized test scores.
Conclusions
Our findings indicate that students' conscientiousness is a personality trait that seems to be important when it comes to how closely mathematics teachers align their grades to standardized test scores.
Do stereotypes strike twice?
(2019)
Stereotypes influence teachers' perception of and behaviour towards students, thus shaping students' learning opportunities. The present study investigated how 315 Australian pre-service teachers' stereotypes about giftedness and gender are related to their perception of students' intellectual ability, adjustment, and social-emotional ability, using an experimental vignette approach and controlling for social desirability in pre-service teachers' responses. Repeated-measures ANOVA showed that pre-service teachers associated giftedness with higher intellectual ability, but with less adjustment compared to average-ability students. Furthermore, pre-service teachers perceived male students as less socially and emotionally competent and less adjusted than female students. Additionally, pre-service teachers seemed to perceive female average-ability students' adjustment as most favourable compared to male average-ability students and gifted students. Findings point to discrepancies between actual characteristics of gifted female and male students and stereotypes in teachers' beliefs. Consequences of stereotyping and implications for teacher education are discussed.
Optimizing power analysis for randomized experiments: Design parameters for student achievement
(2024)
Randomized trials (RTs) are promising methodological tools to inform evidence-based reform to enhance schooling. Establishing a robust knowledge base on how to promote student achievement requires sensitive RT designs demonstrating sufficient statistical power and precision to draw conclusive and correct inferences on the effectiveness of educational programs and innovations. Proper power analysis is therefore an integral component of any informative RT on student achievement. This venture critically hinges on the availability of reasonable input variance design parameters (and their inherent uncertainties) that optimally reflect the realities around the prospective RT—precisely, its target population and outcome, possibly applied covariates, the concrete design as well as the planned analysis. However, existing compilations in this vein show far-reaching shortcomings.
The overarching endeavor of the present doctoral thesis was to substantively expand available resources devoted to tweak the planning of RTs evaluating educational interventions. At the core of this thesis is a systematic analysis of design parameters for student achievement, generating reliable and versatile compendia and developing thorough guidance to support apt power analysis to design strong RTs. To this end, the thesis at hand bundles two complementary studies which capitalize on rich data of several national probability samples from major German longitudinal large-scale assessments.
Study I applied two- and three-level latent (covariate) modeling to analyze design parameters for a wide spectrum of mathematical-scientific, verbal, and domain-general achievement outcomes. Three vital covariate sets were covered comprising (a) pretests, (b) sociodemographic characteristics, and (c) their combination. The accumulated estimates were additionally summarized in terms of normative distributions.
Study II specified (manifest) single-, two-, and three-level models and referred to influential psychometric heuristics to analyze design parameters and develop concise selection guidelines for covariate (a) types of varying bandwidth-fidelity (domain-identical, cross-domain, fluid intelligence pretests; sociodemographic characteristics), (b) combinations quantifying incremental validities, and (c) time lags of 1- to 7-year-lagged pretests scrutinizing validity degradation. The estimates for various mathematical-scientific and verbal achievement outcomes were meta-analytically integrated and employed in precision simulations.
In doing so, Studies I and II addressed essential gaps identified in previous repertoires in six major dimensions: Taken together, this thesis accumulated novel design parameters and deliberate guidance for RT power analysis (1) tailored to four German student (sub)populations across the entire school career from Grade 1 to 12, (2) matched to 21 achievement (sub)domains, (3) adjusted for 11 covariate sets enriched by empirically supported guidelines, (4) adapted to six RT designs, (5) suitable for latent and manifest analysis models, (6) which were cataloged along with quantifications of their associated uncertainties. These resources are complemented by a plethora of illustrative application examples to gently direct psychological and educational researchers through pivotal steps in the process of RT design.
The striking heterogeneity of the design parameter estimates across all these dimensions constitutes the overall, joint key result of Studies I and II. Hence, this work convincingly reinforces calls for a close match between design parameters and the specific peculiarities of the target RT’s research context.
All in all, the present doctoral thesis offers a—so far unique—nuanced and extensive toolkit to optimize power analysis for sound RTs on student achievement in the German (and similar) school context. It is of utmost importance that research does not tire to spawn robust evidence on what actually works to improve schooling. With this in mind, I hope that the emerging compendia and guidance contribute to the quality and rigor of our randomized experiments in psychology and education.
The collaboration-based professional development approach Lesson Study (LS), which has its roots in the Japanese education system, has gained international recognition over the past three decades and spread quickly throughout the world. LS is a collaborative method to professional development (PD) that incorporates multiple characteristics that have been identified in the research literature as key to effective PD. Specifically, LS is a long-term process that consists of subsequent inquiry cycles, it is site-based and integrated in teachers’ practice, it encourages collaboration and reflection, places a strong emphasis on student learning, and it typically involves external experts that support the process or offer additional insights.
As LS integrates all these characteristics, it has rapidly gained international popularity since the turn of the 21st century and is currently being practiced in over 40 countries around the world. This international borrowing of the idea of LS to new national contexts has given rise to a research field that aims to investigate the effectiveness of LS on teacher learning as well as the circumstances and mechanisms that make LS effective in various settings around the world. Such research is important, as borrowing educational innovations and adapting them to new contexts can be a challenging process. Educational innovations that fail to deliver the expected outcomes tend to be abandoned prematurely and before they have been completely understood or a substantial research base has been established.
In order to prevent LS from early abandonment, Lewis and colleagues outlined three critical research needs in 2006, not long after LS was initially introduced to the United States. These research needs included (1) developing a descriptive knowledge base on LS, (2) examining the mechanisms by which teachers learn through LS, and (3) using design-based research cycles to analyze and improve LS.
This dissertation set out to take stock of the progress that has been made on these research needs over the past 20 years. The scoping review conducted for the framework of this dissertation indicates that, while a large and international knowledge base has been developed, the field has not yet produced reliable evidence of the effectiveness of LS. Based on the scoping review, this dissertation makes the case that Lewis et al.’s (2006) critical research needs should be updated. In order to do so, a number of limitations to the current knowledge base on LS need to be addressed. These limitations include (1) the frequent lack of comparable and replicable descriptions of the LS intervention in publications, (2) the incoherent use or lack of use of theoretical frameworks to explain teacher learning through LS, (3) the inconsistent use of terminology and concepts, and (4) the lack of scientific rigor in research studies and of established ways or tools to measure the effectiveness of LS.
This dissertation aims to advance the critical research needs in the field by examining the extent and nature of these limitations in three research studies. The focus of these studies lies on the LS stages of observation and reflection, as these stages have a high potential to facilitate teacher learning. The first study uses a mixed-method design to examine how teachers at German primary schools reflect critically together. The study derives a theory-based definition of critical and collaborative reflection in order to re-frame the reflection element in LS.
The second study, a systematic review of 129 articles on LS, assess how transparent research articles are in reporting how teachers observed and reflected together. In addition, it is investigated whether these articles provide any kind of theorization for the stages of observation and reflection.
The third study proposes a conceptual model for the field of LS that is based on existing models of continuous professional development and research findings on team effectiveness and collaboration. The model describes the dimensions of input, mediating mechanisms, and outcomes in order to provide a conceptual grid to teachers’ continuous professional development through LS.
The impact of individual differences in cognitive skills and socioeconomic background on key educational, occupational, and health outcomes, as well as the mechanisms underlying inequalities in these outcomes across the lifespan, are two central questions in lifespan psychology. The contextual embeddedness of such questions in ontogenetic (i.e., individual, age-related) and historical time is a key element of lifespan psychological theoretical frameworks such as the HIstorical changes in DEvelopmental COntexts (HIDECO) framework (Drewelies et al., 2019). Because the dimension of time is also a crucial part of empirical research designs examining developmental change, a third central question in research on lifespan development is how the timing and spacing of observations in longitudinal studies might affect parameter estimates of substantive phenomena. To address these questions in the present doctoral thesis, I applied innovative state-of-the-art methodology including static and dynamic longitudinal modeling approaches, used data from multiple international panel studies, and systematically simulated data based on empirical panel characteristics, in three empirical studies.
The first study of this dissertation, Study I, examined the importance of adolescent intelligence (IQ), grade point average (GPA), and parental socioeconomic status (pSES) for adult educational, occupational, and health outcomes over ontogenetic and historical time. To examine the possible impact of historical changes in the 20th century on the relationships between adolescent characteristics and key adult life outcomes, the study capitalized on data from two representative US cohort studies, the National Longitudinal Surveys of Youth 1979 and 1997, whose participants were born in the late 1960s and 1980s, respectively. Adolescent IQ, GPA, and pSES were positively associated with adult educational attainment, wage levels, and mental and physical health. Across historical time, the influence of IQ and pSES for educational, occupational, and health outcomes remained approximately the same, whereas GPA gained in importance over time for individuals born in the 1980s.
The second study of this dissertation, Study II, aimed to examine strict cumulative advantage (CA) processes as possible mechanisms underlying individual differences and inequality in wage development across the lifespan. It proposed dynamic structural equation models (DSEM) as a versatile statistical framework for operationalizing and empirically testing strict CA processes in research on wages and wage dynamics (i.e., wage levels and growth rates). Drawing on longitudinal representative data from the US National Longitudinal Survey of Youth 1979, the study modeled wage levels and growth rates across 38 years. Only 0.5 % of the sample revealed strict CA processes and explosive wage growth (autoregressive coefficients AR > 1), with the majority of individuals following logarithmic wage trajectories across the lifespan. Adolescent intelligence (IQ) and adult highest educational level explained substantial heterogeneity in initial wage levels and long-term wage growth rates over time.
The third study of this dissertation, Study III, investigated the role of observation timing variability in the estimation of non-experimental intervention effects in panel data. Although longitudinal studies often aim at equally spaced intervals between their measurement occasions, this goal is hardly ever met. Drawing on continuous time dynamic structural equation models, the study examines the –seemingly counterintuitive – potential benefits of measurement intervals that vary both within and between participants (often called individually varying time intervals, IVTs) in a panel study. It illustrates the method by modeling the effect of the transition from primary to secondary school on students’ academic motivation using empirical data from the German National Educational Panel Study (NEPS). Results of a simulation study based on this real-life example reveal that individual variation in time intervals can indeed benefit the estimation precision and recovery of the true intervention effect parameters.
This study investigates the relationship between teacher quality and teachers’ engagement in professional development (PD) activities using data on 229 German secondary school mathematics teachers. We assessed different aspects of teacher quality (e.g. professional knowledge, instructional quality) using a variety of measures, including standardised tests of teachers’ content knowledge, to determine what characteristics are associated with high participation in PD. The results show that teachers with higher scores for teacher quality variables take part in more content-focused PD than teachers with lower scores for these variables. This suggests that teacher learning may be subject to a Matthew effect, whereby more proficient teachers benefit more from PD than less proficient teachers.
Background: Students' self-concept of ability is an important predictor of their achievement emotions. However, little is known about how learning environments affect these interrelations.
Aims: Referring to Pekrun's control-value theory, this study investigated whether teacher-reported teaching quality at the classroom level would moderate the relation between student-level mathematics self-concept at the beginning of the school year and students' achievement emotions at the middle of the school year.
Sample: Data of 807 ninth and tenth graders (53.4% girls) and their mathematics teachers (58.1% male) were analysed.
Method: Students and teachers completed questionnaires at the beginning of the school year and at the middle of the school year. Multi-level modelling and cross-level interaction analyses were used to examine the longitudinal relations between self-concept, teacher-perceived teaching quality, and achievement emotions as well as potential interaction effects.
Results: Mathematics self-concept significantly and positively related to enjoyment in mathematics and negatively related to anxiety. Teacher-reported structuredness decreased students' anxiety. Mathematics self-concept only had a significant and positive effect on students' enjoyment at high levels of teacher-reported cognitive activation and at high levels of structuredness.
Conclusions: High teaching quality can be seen as a resource that strengthens the positive relations between academic self-concept and positive achievement emotions.
While the role of and consequences of being a bystander to face-to-face bullying has received some attention in the literature, to date, little is known about the effects of being a bystander to cyberbullying. It is also unknown how empathy might impact the negative consequences associated with being a bystander of cyberbullying. The present study focused on examining the longitudinal association between bystander of cyberbullying depression, and anxiety, and the moderating role of empathy in the relationship between bystander of cyberbullying and subsequent depression and anxiety. There were 1,090 adolescents (M-age = 12.19; 50% female) from the United States included at Time 1, and they completed questionnaires on empathy, cyberbullying roles (bystander, perpetrator, victim), depression, and anxiety. One year later, at Time 2, 1,067 adolescents (M-age = 13.76; 51% female) completed questionnaires on depression and anxiety. Results revealed a positive association between bystander of cyberbullying and depression and anxiety. Further, empathy moderated the positive relationship between bystander of cyberbullying and depression, but not for anxiety. Implications for intervention and prevention programs are discussed.
The purpose of the present study was to examine the moderation of parental mediation in the longitudinal association between being a bystander of cyberbullying and cyberbullying perpetration and cyberbullying victimization. Participants were 1067 7th and 8th graders between 12 and 15 years old (51% female) from six middle schools in predominantly middle-class neighborhoods in the Midwestern United States. Increases in being bystanders of cyberbullying was related positively to restrictive and instructive parental mediation. Restrictive parental mediation was related positively to Time 2 (T2) cyberbullying victimization, while instructive parental mediation was negatively related to T2 cyberbullying perpetration and victimization. Restrictive parental mediation was a moderator in the association between bystanders of cyberbullying and T2 cyberbullying victimization. Increases in restrictive parental mediation strengthened the positive relationship between these variables. In addition, instructive mediation moderated the association between bystanders of cyberbullying and T2 cyberbullying victimization such that increases in this form of parental mediation strategy weakened the association between bystanders of cyberbullying and T2 cyberbullying victimization. The current findings indicate a need for parents to be aware of how they can impact adolescents’ involvement in cyberbullying as bullies and victims. In addition, greater attention should be given to developing parental intervention programs that focus on the role of parents in helping to mitigate adolescents’ likelihood of cyberbullying involvement.
Recently, interest in collecting and mining large sets of educational data on student background and performance to conduct research on learning and instruction has developed as an area generally referred to as learning analytics. Higher education leaders are recognising the value of learning analytics for improving not only learning and teaching but also the entire educational arena. However, theoretical concepts and empirical evidence need to be generated within the fast evolving field of learning analytics. In this paper, we introduce a holistic learning analytics framework. Based on this framework, student, learning, and curriculum profiles have been developed which include relevant static and dynamic parameters for facilitating the learning analytics framework. Based on the theoretical model, an empirical study was conducted to empirically validate the parameters included in the student profile. The paper concludes with practical implications and issues for future research.