Louisiana State University (LSU) received an Education Innovation and Research (EIR) grant to implement its Introduction to Computational Thinking (ICT) course from fall 2019 through spring 2023. ICT is a yearlong course that builds skills in problem solving, programming, and mathematics (algebra and geometry) and is intended to improve…

This study aims to examine the conceptual understanding of middle-school 8th graders on measurement based on big ideas. To this aim, a case study was carried out with six students from a state middle school. The data were collected through semi-structured interviews with the instrument developed by the researchers and consisting of seven…

In this paper is proposed a straightforward model selection approach that indicates the most suitable count regression model based on relevant data characteristics. The proposed selection approach includes four of the most popular count regression models (i.e. Poisson, negative binomial, and respective zero-inflated frameworks). Moreover, it…

The present study proposes a Bayesian approach for estimating and testing the operation-specific learning model, a variant of the linear logistic test model that allows for the measurement of the learning that occurs during a test as a result of the repeated use of the operations involved in the items. The advantages of using a Bayesian framework…

The Math-Up Skills Tests (MUST) has been used in multiple research projects conducted by the Networking for Science Advancement (NSA) team to determine how automaticity skills (what can be done without a calculator) in arithmetic can be used to predict if students will be successful (course average = 69.5%+) in general chemistry. This study…

Researchers face many choices when conducting large-scale multisite individually randomized control trials. One of the most common quantities of interest in multisite RCTs is the overall average effect. Even this quantity is non-trivial to define and estimate. The researcher can target the average effect across individuals or sites. Furthermore,…

This study investigates the development of algorithmic thinking as a part of computational thinking skills and self-efficacy of primary school pupils using programmable robots in different instruction variants. Computational thinking is defined in the context of twenty-first century skills and describes processes involved in (re)formulating a…

Over the past 7 years, we pioneered the development of a program blending dance choreography, computer programming, and a virtual environment to teach computational thinking, broadening pathways for more diverse students. We investigated the ways in which upper elementary and middle school students creating dance performances for virtual…

When we "think like a computer scientist," we are able to systematically solve problems in different fields, create software applications that support various needs, and design artefacts that model complex systems. Abstraction is a soft skill embedded in all those endeavours, being a main cornerstone of computational thinking. Our…

There is a great deal of research about item response theory (IRT) conducted by simulations. Item and ability parameters are estimated with varying numbers of replications under different test conditions. However, it is not clear what the appropriate number of replications should be. The aim of the current study is to develop guidelines for the…

This Monte Carlo study assessed Type I error in differential item functioning analyses using Lord's chi-square (LC), Likelihood Ratio Test (LRT), and Mantel-Haenszel (MH) procedure. Two research interests were investigated: item response theory (IRT) model specification in LC and the LRT and continuity correction in the MH procedure. This study…

Performance in and perceptions of computational thinking (CT) are considered vital dimensions for comprehensively assessing CT skills of students. In this study, secondary school students' CT performance and their perceptions were examined in terms of certain variables including gender, grade level, achievement and self-efficacy.…

Vertical scaling is used to put tests of different difficulty onto a common metric. The Rasch model is often used to perform vertical scaling, despite its strict functional form. Few, if any, studies have examined anchor item choice when using the Rasch model to vertically scale data that do not fit the model. The purpose of this study was to…

The pervasiveness of Computer Science (CS) in today's digital society and the extensive use of computational methods in other sciences call for its introduction in the school curriculum. Hence, Computer Science Education is becoming more and more relevant. In CS K-12 education, computational thinking (CT) is one of the abused buzzwords: different…

As the demand for skilled data scientists has grown, university level statistics and data science courses have become more rigorous in training students to understand and utilize the tools that their future careers will likely require. However, the mechanisms to assess students' use of these tools while they are learning to use them are not well…