This study aims to suggest a generalized class of estimators for population proportion under simple random sampling, which uses auxiliary attributes. The bias and MSEs are considered derived to the first degree approximation. The validity of the suggested and existing estimators is assessed via an empirical investigation. The performance of…

Measuring opportunities to learn (OTL) is crucial for evaluating education quality and equity, but obtaining accurate and comprehensive OTL data at a large scale remains challenging. We attempt to address this issue by investigating measurement concerns in data collection and sampling. With the primary goal of estimating group-level OTLs for large…

The multistage testing (MST) design has been gaining attention and popularity in educational assessments. For testing programs that have small test-taker samples, it is challenging to calibrate new items to replenish the item pool. In the current research, we used the item pools from an operational MST program to illustrate how research studies…

Not knowing the population size is a common problem in data-limited contexts. Drawing on work in Sierra Leone, this short take outlines a four-step solution to this problem: (1) estimate the population size using expert interviews; (2) verify estimates using interviews with participants sampled; (3) triangulate using secondary data; and (4)…

Interrupted time series (ITS) studies are frequently used to examine the impact of population-level interventions or exposures. Systematic reviews with meta-analyses including ITS designs may inform public health and policy decision-making. Re-analysis of ITS may be required for inclusion in meta-analysis. While publications of ITS rarely provide…

The cross-classified data structure is ubiquitous in education, psychology, and health outcome sciences. In these areas, assessment instruments that are made up of multiple items are frequently used to measure latent constructs. The presence of both the cross-classified structure and multivariate categorical outcomes leads to the so-called…

In response to the problem of inaccurate classification of big data information in traditional English teaching ability evaluation algorithms, this paper proposes an English teaching ability estimation algorithm based on big data fuzzy K-means clustering. Firstly, the article establishes a constraint parameter index analysis model. Secondly,…

Obtaining reliable and timely estimates of migration flows is critical for advancing the migration theory and guiding policy decisions, but it remains a challenge. Digital data provide granular information on time and space, but do not draw from representative samples of the population, leading to biased estimates. We propose a method for…

This article presents a novel digital method of capturing finger-based gestures on touchscreen devices for the purpose of exploring tracing gestures in educational research. Given that tracing has been found to support cognition, learning, and problem solving in educational settings, data related to the performance of these gestures are…

With the advent of physiological computing systems, new avenues are emerging for the field of learning analytics related to the potential integration of physiological data. To this end, we developed a physiological computing infrastructure to collect physiological data, surveys, and browsing behavior data to capture students' learning journey in…

Recent years have witnessed an increasing emphasis on integrating computational thinking into school curriculums. This study deals with suggesting a course model including data collection tools for evaluating teachers' pedagogical content knowledge in teaching computational thinking via teaching robot programming. Taking the advantages of virtual…

Background: This study describes a method for harmonizing data collected with different tools to compute a rating of compliance with national recommendations for school physical activity (PA) and nutrition environments. Methods: We reviewed questionnaire items from 84 elementary schools that participated in the Childhood Obesity Research…

The use of data to explain natural phenomena has been a core feature of science education, and science educators continue to call for an increased emphasis on teaching data practices. This mixed methods design-based research study adds to the growing body of research on data practices in science by explaining the learning trends of science…

This article aims to present a first approximation of the conceptual field of measures of central tendency (MCT), grounded in the theory of conceptual fields. We propose six situations according to type of variable, data presentation (raw or grouped) and amount of data. We revisit specific situations for the mean and exemplify several…

The aim of the present study was to investigate the properties of paper-and-pencil data collection instruments developed to measure Computational Thinking (CT) based on several variables. Thus, keywords were identified and used in searches conducted in various databases. The outcomes of the search were analyzed based on the inclusion/exclusion…