Research on mental model representations developed by programmers during parallel program comprehension is important for informing and advancing teaching methods including model-based learning and visualizations. The goals of the research presented here were to determine: how the mental models of programmers change and develop as they learn…

In the last two decades, computational thinking has gained wide relevance in international educational systems. The inclusion of this new type of thinking poses educational challenges with some underlying research questions that need to be answered to meet these challenges with quality. Thus, this study focuses on analyzing the difficulties that…

Recently, creativity has been acknowledged for its importance in improving computer science learning and attitudes. However, very little is known about how to integrate creativity in preservice teacher computing education. Toward this end, we developed a creativity-enhancement intervention in an online Creative Computing instructional module to…

A staple of many spreadsheet-based management science courses is the use of Excel for activities such as model building, sensitivity analysis, goal seeking, and Monte-Carlo simulation. What might those things look like if carried out using Python? We describe a teaching module in which Python is used to do typical Excel-based modeling and…

This paper presents a series of basic computational problems that are mathematically and/or graphically appealing, and provides an idea of places one might go in trying to understand what is happening, integrating mathematics, computation, and graphics. The real point of this paper is to make a case, through those examples, for computation as an…

Massive Open Online Courses (MOOCs) have become hugely popular recently. MOOCs can offer high-quality education for anyone interested and equalize the whole education field. Still, there are different methodologies for running MOOCs. Coming up with the most suitable methodology benefits both students and teachers. In this study, we have limited…

Real-time collaborative programming (RCP), which allows multiple programmers to work concurrently on the same codebase with changes instantly visible to all participants, has garnered considerable popularity in higher education. Despite this trend, little work has rigorously examined how undergraduates engage in collaborative programming when…

Despite the increasing use of the statistical programming language R in statistics and data analysis (SDA), its implementation in communication science education is limited. Experiences, recommendations, and a critical exchange are therefore scarce. The following contribution addresses this very gap. At the Department of Journalism and…

Large Language Model (LLM) artificial intelligence tools present a unique challenge for educators who teach programming languages. While LLMs like ChatGPT have been well documented for their ability to complete exams and create prose, there is a noticeable lack of research into their ability to solve problems using high-level programming…

Computational thinking (CT), an essential competency for comprehending and addressing intricate issues in the digital world, has been incorporated into curriculum planning as a goal for programming education. This study introduced flow design into programming curricula to investigate its impact on undergraduates 'CT skills during pair work. Two…

Predictive student models are increasingly used in learning environments due to their ability to enhance educational outcomes and support stakeholders in making informed decisions. However, predictive models can be biased and produce unfair outcomes, leading to potential discrimination against certain individuals and harmful long-term…

Background: Studies on the effectiveness of block-based environments continue to produce inconsistent results. A strong reason for this is that most studies compare environments that are not equivalent to each other or to the level of learners. Moreover, studies that present evidence of the effectiveness of block-based environments by comparing…

An essential skill for STEM undergraduates is the ability to understand the world by manipulating, visualizing, and analyzing data to make or evaluate claims. Current online debate, without peer-reviewed literature, explores which of two common R syntax environments (base R or tidyverse) is best for teaching novice R users. In an in-person…

This study explores the application of the Project-Based Learning with Gamification Model (PBLGM) through Visual Programming Language (VPL) to enhance digital competencies and problem-solving skills in learners. The PBLGM model integrates project-based learning and gamification techniques using Kodu Game Lab, aiming to develop essential…

Understanding students' learning of knowledge components (KCs) is an important educational data mining task and enables many educational applications. However, in the domain of computing education, where program exercises require students to practice many KCs simultaneously, it is a challenge to attribute their errors to specific KCs and,…