This study examines the feasibility and potential advantages of using large language models, in particular GPT-4o, to perform partial credit grading of large numbers of student written responses to introductory level physics problems. Students were instructed to write down verbal explanations of their reasoning process when solving one conceptual…

Physics problem-solving ability is among the crucial skills physics students require as it enhances their conceptual understanding and develops their abilities for real-world problem-solving. This study employed a descriptive design to investigate the physics problem-solving skills of Senior-Five physics students from Rwandan secondary schools.…

This paper extends existing work on teacher weighting in student-centered surveys by looking into aspects of practical implementation of deriving and using weights for teacher-centered analysis in the Trends in International Mathematics and Science Study (TIMSS) and the Progress in International Reading Literacy Study (PIRLS). The formal…

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…

New MAP® Growth™ assessments are being developed that administer items more closely matched to the grade level of the student. However, MAP Growth items are calibrated with samples that typically consist of students from a variety of grades, including the target grade to which an item is aligned. While this choice of calibration sample is…

The finite population correction (FPC) factor is often used to adjust variance estimators for survey data sampled from a finite population without replacement. As a replicated resampling approach, the jackknife approach is usually implemented without the FPC factor incorporated in its variance estimates. A paradigm is proposed to compare the…

There has been increasing interest in exploring heterogeneous treatment effects using machine learning (ML) methods such as causal forests, Bayesian additive regression trees, and targeted maximum likelihood estimation. However, there is little work on applying these methods to estimate treatment effects in latent classes defined by…

In this paper, we applied a number of clustering algorithms on pretest data collected from 264 high-school students. Students took the pre-test at the beginning of a 5-week experiment in which they interacted with an intelligent tutoring system. The primary goal of this work is to identify clusters of students exhibiting similar knowledge…

Computational thinking (CT) is one of the systematic tools in problem solving and widely accepted as an important skill in the 21st century. This study aimed to identify the effectiveness of the Chemistry Computational Thinking (CT-CHEM) Module on achievement in chemistry. This study also employed a quasi-experimental design with the participation…

Assessment items are commonly field tested prior to operational use to observe statistical item properties such as difficulty. Item parameter estimates from field testing may be used to assign scores via pre-equating or computer adaptive designs. This study examined differences between item difficulty estimates based on field test and operational…

On the basis of the results of two prior studies at the US Naval Academy (USNA), which described the choice of study resources and the self-reported learning approaches of students of differing achievement levels, the current investigation examines how students of differing achievement levels in general chemistry actually solve multiple-choice…

This rejoinder keeps the original focus on statistical computing pertaining to the correlation of student achievement between mathematics and science from the Trend in Mathematics and Science Study (TIMSS). Albeit the availability of student performance data in TIMSS and the emphasis of the inter-subject connection in the Next Generation Science…

With integrated curricula and multidisciplinary assessments becoming more prevalent in medical education, there is a continued need for educational research to explore the advantages, consequences, and challenges of integration practices. This retrospective analysis investigated the number of items needed to reliably assess anatomical knowledge in…

A primary purpose of cognitive diagnosis models (CDMs) is to classify examinees based on their attribute patterns. The Q-matrix (Tatsuoka, 1985), a common component of all CDMs, specifies the relationship between the set of required dichotomous attributes and the test items. Since a Q-matrix is often developed by content-knowledge experts and can…

Experimental work in the research of astronomical phenomena is often difficult or even impossible because of long-lasting processes or too distant objects and correspondingly too expensive equipment. In this paper, we present an example of observation of the Moon, which is our nearest astronomic object and therefore does not require professional…