Natural category learning is important in science education. One strategy that has been empirically supported for enhancing category learning is testing, which facilitates not only the learning of previously studied information (backward testing effect) but also the learning of newly studied information (forward testing effect). However, in…

This article provides a process to carefully evaluate the suitability of a content domain for which diagnostic classification models (DCMs) could be applicable and then optimized steps for constructing a test blueprint for applying DCMs and a real-life example illustrating this process. The content domains were carefully evaluated using a set of…

Electricity and magnetism are fundamental areas of physics and are integral to science curricula at various educational levels. However, this area has been reported to contain several concepts that students find challenging, leading to perspectives that diverge from scientifically accepted views. This study examines the errors made by physics…

Learning style (LS), either visual or verbal, has become debatable in the f ield of education vis-à-vis its relation to student success. However, it remains a valuable research theme for improving learning activities in the teaching of highly visual science fields, including biology, physics, and chemistry. Previous studies have primarily focused…

The revised two-factor Study Process Questionnaire and the Approaches and Study Skills Inventory for Students are two instruments commonly used to measure student learning approach. Although they are designed to measure similar constructs, it is unclear whether the metrics they provide differ in terms of their real-world classification of learning…

We propose new methods for identifying and classifying aberrant response patterns (ARPs) by means of functional data analysis. These methods take the person response function (PRF) of an individual and compare it with the pattern that would correspond to a generic individual of the same ability according to the item-person response surface. ARPs…

This paper introduces an approach that uses latent class analysis to identify cut scores (LCA-CS) and categorize respondents based on context scales derived from largescale assessments like PIRLS, TIMSS, and NAEP. Context scales use Likert scale items to measure latent constructs of interest and classify respondents into meaningful ordered…

The study aims to reveal students' mental models and perceptions regarding the concept of the celestial bodies, for instance, earth, sun, and moon. This research study was conducted as a case study focusing on qualitative data. This study also has used a sample formed of 5th-grade students, in the 2018-2019 academic year; the target sample is…

This article presents a latent class model for multilevel data to identify latent subgroups and estimate heterogeneous treatment effects. Unlike sequential approaches that partition data first and then estimate average treatment effects (ATEs) within classes, we employ a Bayesian procedure to jointly estimate mixing probability, selection, and…

Purpose: Researchers discovered that when students were given the opportunity to change their answers, a majority changed their responses from incorrect to correct, and this change often increased the overall test results. What prompts students to modify their answers? This study aims to examine the modification of scientific reasoning test, with…

Understanding genetics is one of the most significant learning difficulties faced by students. To improve teaching genetics and the students' representational competence within the classroom have been proposed using multiple representations. This study presents an analysis of representational levels used by high school students learning Mendelian…

Understanding whether or not different types of students master various attributes can aid future learning remediation. In this study, two-level diagnostic classification models (DCMs) were developed to represent the probabilistic relationship between external latent classes and attribute mastery patterns. Furthermore, variational Bayesian (VB)…

The goal of the present work is to extend an online reaction categorization task as a research instrument to a formative assessment tool of students' knowledge organization for organic chemistry reactions. Herein, we report our findings from administering the task with undergraduate students in Organic Chemistry II, at a large, research intensive…

Scoring procedures for many rater-mediated performance assessments include score resolution procedures in which a third rater adjudicates discrepancies between two raters' ratings of the same performance. There are numerous approaches for calculating resolved scores that involve different combinations of the original and third ratings. Using data…

Educational Data Mining (EDM) is an important tool in the field of classification of educational data that helps researchers and education planners analyse and model available educational data for specific needs such as developing educational strategies. Trends International Mathematics and Science Study (TIMSS) which is a notable study in…