The random intercept cross-lagged panel model (RICLPM) decomposes longitudinal associations between two processes X and Y into stable between-person associations and temporal within-person changes. In a recent study, Bailey et al. demonstrated through a simulation study that the between-person variance components in the RICLPM can occur only due…

There is a longstanding debate on whether the analysis of covariance (ANCOVA) or the change score approach is more appropriate when analyzing non-experimental longitudinal data. In this article, we use a structural modeling perspective to clarify that the ANCOVA approach is based on the assumption that all relevant covariates are measured (i.e.,…

Recent developments have enabled the modeling of longitudinal assessment data in a diagnostic classification model (DCM) framework. These longitudinal DCMs were developed to provide measures of student growth on a discrete scale in the form of attribute mastery transitions, thereby supporting categorical and criterion-referenced interpretations of…

The issue of missing data raises concerns in all statistical and educational research. In this study, we focus on missing data in school-based assessment data generated by progressed high school learners (those who did not meet the promotional requirements for their current grades but were allowed to move to the next grade because of policy…

Many educational and psychological studies have shown that the development of students is generally step-by-step (i.e. ordinal development) to a specific level. This study proposed a novel longitudinal learning diagnosis model with polytomous attributes to track students' ordinal development in learning. Using the concept of polytomous attributes…

Research showed that the capacity of making simple estimations begins to develop already at the age of five, but little is known about the early development of this estimation capacity and the strategies that underly it. The current study longitudinally followed the estimation capacity and strategies of 332 children from first to second grade of…

Background: Computational thinking (CT) has emerged as a critical component of 21st-century skills, and increasing effort was seen in exploring the development of CT skills in K-12 students. Despite cumulative research on exploring students' CT acquisition and its influencing factors, learners' development of the skill over time and the underlying…

In mathematics education, researchers often contrast conceptual and procedural teaching approaches, although labels and conceptualizations often vary across studies. Prior research has extensively examined empirical relationships between the two teaching approaches and mathematics achievement. In our study, we aimed to extend this research by…

Cluster randomized control trials often incorporate a longitudinal component where, for example, students are followed over time and student outcomes are measured repeatedly. Besides examining how intervention effects induce changes in outcomes, researchers are sometimes also interested in exploring whether intervention effects on outcomes are…

Item factor analysis (IFA), also known as Multidimensional Item Response Theory (MIRT), is a general framework for specifying the functional relationship between a respondent's multiple latent traits and their response to assessment items. The key element in MIRT is the relationship between the items and the latent traits, so-called item factor…

The introduction of computing education into curricula worldwide requires multi-year assessments to evaluate the long-term impact on learning. However, no single Computational Thinking (CT) assessment spans primary school, and no group of CT assessments provides a means of transitioning between instruments. This study therefore investigated…

Problem-solving and critical thinking are associated with 21st century skills and have gained popularity as computational thinking skills in recent decades. Having such skills has become a must for all ages/grade levels. This study was conducted to examine the effects of grade level, gender, chronotype, and time on computational thinking skills.…

This study was an investigation of the use of manipulative materials in the mathematics classroom. The researcher guided students to create paper triangles, which were then used as a manipulative to calculate the sum of the interior angles of a triangle. On pre- and post-measures of quantitative data, although the data indicated a positive…

Measuring change in an educational or psychological construct over time is often achieved by repeatedly administering the same items to the same examinees over time and fitting a second-order latent growth curve model. However, latent growth modeling with full information maximum likelihood (FIML) estimation becomes computationally challenging…

Programming education consistently faces challenges in bridging theory with practice and fostering students' cognitive competencies. This 12-year longitudinal study (2011-2023) investigates an innovative competency-based teaching model in university C programming education that integrates six educational theories into a coherent framework with…