Ensuring comparability of Likert-style items across different countries is a widespread challenge for authors of large-scale international surveys. Using data from the EUROGRADUATE Pilot Survey, this study employs a series of latent class analyses to explore which response patterns emerge from self-assessment of acquired and required skills of…

The multidimensional mixture data structure exists in many test (or inventory) conditions. Heterogeneity also relatively exists in populations. Still, some researchers are interested in deciding to which subpopulation a participant belongs according to the participant's factor pattern. Thus, in this study, we proposed three analysis procedures…

The research of multi-category learning behaviors is a hot issue in interactive learning environment, and there are many challenges in data statistics and relationship modeling. We select the massive learning behaviors data of multiple periods and courses and study the decision application of regression analysis. First, based on the definition of…

Longitudinal data structures are frequently encountered in a variety of disciplines in the social and behavioral sciences. Growth curve modeling offers a highly extensible framework that allows for the exploration of rich hypotheses. However, owing to the presence of interrelated sources of potential data-model misfit at multiple levels, the…

Contribution: In this article, the authors present findings and insights on the efficacy of using an educational block-based programming (BBP) environment--Blocks4DS, to teach the binary search tree (BST). Background: For a decade, BBP environments have been a hot topic in the computer science education (CSEd) community to promote interactive…

Multidimensionality and hierarchical data structure are common in assessment data. These design features, if not accounted for, can threaten the validity of the results and inferences generated from factor analysis, a method frequently employed to assess test dimensionality. In this article, we describe and demonstrate the application of the…

We present CSTutor, a sketch-based interface designed to help students understand data structures, specifically Linked Lists, Binary Search Trees, AVL Trees, and Heaps. CSTutor creates an environment that seamlessly combines a user's sketched diagram and code. In each of these data structure modes, the user can naturally sketch a data structure on…

Background: After elementary school, students in Germany are separated into different school tracks (i.e., school types) with the aim of creating homogeneous student groups in secondary school. Consequently, the development of students' reading achievement diverges across school types. Findings on this achievement gap have been criticized as…

This paper describes the role of data and task context in young children's interpretation of and reasoning about data tables. A design-based descriptive study was conducted with fourteen 5-year-old children in their first year of formal schooling. A picture storybook provided the data context for a data modelling activity that focused on…

Advances in state education data systems are helping schools understand and meet the needs of learners from early education through college and the workforce. Each state has adhered to key principles for protecting student data privacy. In the report "Lessons in Data Privacy for Education Leaders. Policy Guide," (ED625423) leading…

Using Gyeonggi Educational Panel Study data on 4051 Korean students (N = 4051; 1967 female, 2084 male) from 63 middle schools, this longitudinal study investigated the growth trajectory for second/foreign language (L2) achievement and associations with various L2 motivational factors by using a multilevel latent growth curve model in…

This paper describes a teaching method that enables students to design efficient and effective algorithms for reporting information systems applications. Adopting the general principles of transformative learning, students are immersed in a series of activities and interventions to enable learning. The activities provided opportunities for…

Learning processes often occur at a situational level. Changes in learning context have implications on how students are motivated or are able to cognitively process information. To study such situational phenomena, Experience Sampling Method (ESM) can help assess psychological variables in the moment and in context. However, data collected via…

Applying single-level statistical models to multilevel data typically produces underestimated standard errors, which may result in misleading conclusions. This study examined the impact of ignoring multilevel data structure on the estimation of item parameters and their standard errors of the Rasch, two-, and three-parameter logistic models in…

The human capital supply chain is a complex network of systems with inherent challenges to accommodating Total Learning Architecture (TLA) operability. This document covers the objective end-state for Department of Defense (DoD) learning organizations migrating to TLA compliant data and microservices. This document is organized into sections that…