Longitudinal item response data often exhibit two types of measurement noninvariance: the noninvariance of item parameters between subject groups and that of item parameters across multiple time points. This study proposes a comprehensive approach to the simultaneous modeling of both types of measurement noninvariance in terms of longitudinal item…

Parallel process latent growth curve mediation models (PP-LGCMMs) are frequently used to longitudinally investigate the mediation effects of treatment on the level and change of outcome through the level and change of mediator. An important but often violated assumption in empirical PP-LGCMM analysis is the absence of omitted confounders of the…

Parallel process latent growth curve mediation models (PP-LGCMMs) are frequently used to longitudinally investigate the mediation effects of treatment on the level and change of outcome through the level and change of mediator. An important but often violated assumption in empirical PP-LGCMM analysis is the absence of omitted confounders of the…

This study introduced Satir Growth Model (SGM) into career intervention to enhance Chinese college freshmen's career adaptability. The effect of SGM-based career intervention was examined by the randomised controlled trial design. Results indicated that the experimental group experienced a significant increase in career exploration and career…

This study proposes transformation functions and matrices between coefficients in the original and reparameterized parameter spaces for an existing linear-linear piecewise model to derive the interpretable coefficients directly related to the underlying change pattern. Additionally, the study extends the existing model to allow individual…

Assessing student achievement over multiple years is complicated by students' memberships in shifting upper-level nesting structures. These structures are manifested in (1) annual matriculation to different classrooms and (2) mobility between schools. Failure to model these shifting upper-level nesting structures may bias the inferences…

The purpose of this research note is to introduce a latent growth curve reconstruction approach based on the Tabu search algorithm. The approach algorithmically enables researchers to optimally determine at both the individual and the group levels the order of the polynomial needed to represent the latent growth curve model. The procedure is…

General pedagogical knowledge (GPK) is regarded as a central component of the competence that teachers acquire during university teacher education. However, existing research on GPK typically uses only one or two measurement points to assess development and identify influencing factors. The present study draws on an annual survey of pre-service…

The ubiquity of formal education in modern nations is often accompanied by an assumption that students' motivation for learning is innate and self-sustaining. The latter is true for most children in domains (e.g., language) that are universal and have a deep evolutionary history, but this does not extend to learning in evolutionarily novel domains…

Medical educators and programs are deeply interested in understanding and projecting the longitudinal developmental trajectories of medical students after these students are matriculated into medical schools so appropriate resources and interventions can be provided to support students' learning and progression during the process. As students have…

The computational model of school achievement represents a novel approach to theorizing school achievement, conceptualizing educational interventions as modifications to students' learning curves. By modeling the process and products of educational achievement simultaneously, this tool addresses several unresolved questions in educational…

Students that classify as having growth mindsets rather than fixed mindsets enjoy greater academic success. This finding has been repeated in a variety of contexts and encourages teachers and researchers to develop growth mindsets in students. However, neutral and negative conclusions from some mindset intervention studies raise questions about…

Growth mixture models (GMMs) are a popular method to identify latent classes of growth trajectories. One shortcoming of GMMs is nonconvergence, which often leads researchers to apply covariance equality constraints to simplify estimation, though this may be a dubious assumption. Alternative model specifications have been proposed to reduce…

The latent growth model (LGM) is a popular tool in the social and behavioral sciences to study development processes of continuous and discrete outcome variables. A special case are frequency measurements of behaviors or events, such as doctor visits per month or crimes committed per year. Probability distributions for such outcomes include the…

This article examines the role of the Great Depression in shaping the intergenerational mobility of some of the most upwardly mobile cohorts of the twentieth century. Using newly linked census and vital records from the Longitudinal, Intergenerational Family Electronic Micro-database, we examine the occupational and educational mobility of more…