Cluster analysis is a set of statistical methods for discovering new group/class structure when exploring data sets. This article reviews the following popular libraries/commands in the R software language for applying different types of cluster analysis: from the stats library, the kmeans, and hclust functions; the mclust library; the poLCA…

Traditionally, statistical computing courses have taught the syntax of a particular programming language or specific statistical computation methods. Since Nolan and Temple Lang's seminal paper, we have seen a greater emphasis on data wrangling, reproducible research, and visualization. This shift better prepares students for careers working with…

A version control system records changes to a file or set of files over time so that changes can be tracked and specific versions of a file can be recalled later. As such, it is an essential element of a reproducible workflow that deserves due consideration among the learning objectives of statistics courses. This article describes experiences and…

As students learn how to program, both their programming code and their understanding of it evolves over time. In this work, we present a general data-driven approach, named "Temporal-ASTNN" for modeling student learning progression in open-ended programming domains. Temporal-ASTNN combines a novel neural network model based on abstract…

This paper examines the effectiveness of programming in pairs in the Scratch environment in primary school. The motivation for tackling this issue is based on the successful use of Scratch as a learning environment for any students of programming. The analysis has shown that that programming in pairs produces better results for beginners in…

The explosive growth of the data analytics field has continued over the past decade with no signs of slowing down. Given the fast pace of technology changes and the need for IT professionals to constantly keep up with the field, it is important to analyze the job skills and knowledge required in the data analyst and business intelligence (BI)…

This research is motivated by the low ability to understand mathematical concepts possessed by prospective elementary school teacher students. This study aims to see the achievement and improvement of students' mathematical understanding abilities that use Microsoft Excel-based VBA teaching materials with those using conventional learning. This…

Many mathematics educators are not aware of a strong connection that exists between the education of computer programming and mathematics. The reason may be that they have not been exposed to computer programming. This connection is worth exploring, given the current trends of automation and Industry 4.0. Therefore, in this paper we take a closer…

Rapid advancements and emergent technologies add an additional layer of complexity to preparing computer science and information technology higher education students for entering the post pandemic job market. Knowing and predicting employers' technical skill needs is essential for shaping curriculum development to address the emergent skill gap.…

The aim of this study was to explore how the Coding as Another Language using ScratchJr (CAL-ScratchJr) curriculum, developed by Boston College's DevTech Research Group utilizing the ScratchJr app, impacted second grade students' computational thinking, coding skills, and reading comprehension. To accomplish this, the research team randomly…

In this digital ITEMS module, Nikole Gregg and Dr. Brian Leventhal discuss strategies to ensure data visualizations achieve graphical excellence. Data visualizations are commonly used by measurement professionals to communicate results to examinees, the public, educators, and other stakeholders. To do so effectively, it is important that these…

Purpose: The purpose of this paper is to examine the ways in which early adolescent programmers embed meaning in their digital media created within an online programming community called Scratch. Design/methodology/approach: The author completed an 18-month descriptive case study with 5 early adolescent participants. The research design included a…

Stan is a flexible probabilistic programming language providing full Bayesian inference through Hamiltonian Monte Carlo algorithms. The benefits of Hamiltonian Monte Carlo include improved efficiency and faster inference, when compared to other MCMC software implementations. Users can interface with Stan through a variety of computing…

The continuous technological development nowadays acts ancillary and supportively in student-centered learning, in both formal and informal education settings. Effective learning environments, such as the AppInventor software, could spark the students' interest and allow them to develop programming skills and strengthen their algorithmic…

Computer Science students need to acquire knowledge about both the hardware and software aspects of computing systems. It is necessary for them to understand how each layer interacts with one another. However, since Graphical User Interfaces have become ubiquitous, the opportunities to interact with the computer via a command prompt as part of…