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…

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…

For most beginners, learning computer programming is a complex undertaking. Demotivation and learned helplessness have been widely reported. In addition to the subject's complexity, low in-class involvement has been linked to poor student performance. This work introduces a novel instructional technique called Student-Driven Probe Instruction…

Block-based programming languages (BBLs) have been proposed as a way to prepare students for learning to program in more sophisticated, text-based languages, such as Java. Hybrid BBLs add the ability to view and edit the block commands in auto-generated, text-based code. We compared the use of a non-hybrid BBL (Scratch), a hybrid BBL (Pencil…

This study explores student perceptions of learning to code by evaluating AI-generated Python code. In an experimental exercise given to students in an introductory Python course at a business university, students wrote their own solutions to a Python program and then compared their solutions with AI-generated code. They evaluated both solutions…

In computer science education timely help seeking during large programming projects is essential for student success. Help-seeking in typical courses happens in office hours and through online forums. In this research, we analyze students coding activities and help requests to understand the interaction between these activities. We collected…

Coding bootcamps targeting diverse learners are increasingly popular. However, little research has focused on the student experience of these courses: what pedagogic practices make learning coding meaningful for them and why. In a previous paper, we proposed a conceptual framework outlining three dimensions of learning opportunities in relation to…

Electrochemistry is a branch of chemistry concerned with the interrelation of electrical and chemical effects, in which mathematical equations are employed to describe the fundamental principles of electrode processes and measurement methods. In this work, we present a graphical simulation that provides visual observations of dynamical behavior…

This study examined the effects of worked examples with different explanation types and novices' motivation on cognitive load, and how this subsequently influenced their programming problem-solving performance. Given the study's emphasis on both instructional approaches and learner motivation, the Cognitive Theory of Multimedia Learning served as…

Background and Context: Lopez and Lister first presented evidence for a skill hierarchy of code reading, tracing, and writing for introductory programming students. Further support for this hierarchy could help computer science educators sequence course content to best build student programming skill. Objective: This study aims to replicate a…

The COVID-19 pandemic, an unprecedented global health crisis, has not only significantly impacted public health but has also caused substantial disruptions to conventional education systems. In response to these challenges, our institution has undertaken innovative measures within the realm of education. A pivotal aspect of our response involves…

Learning computer programming is typically difficult for newcomers. Demotivation and learned helplessness have received much attention. Besides the subject's intricacy, low in-class participation has been associated with poor student achievement. This paper presents a follow-up, stage 2 study on the novel instructional technique, Student-Driven…

College-educated women in the workforce are discovering a latent interest in and aptitude for computing motivated by the prevalence of computing as an integral part of jobs in many fields as well as continued headlines about the number of unfilled, highly paid computing jobs. One of these women's choices for retraining are the so-called coding…

Background: With the increasing interdisciplinarity between computer science (CS) and other fields, a growing number of non-CS students are embracing programming. However, there is a gap in research concerning differences in programming learning between CS and non-CS students. Previous studies predominantly relied on outcome-based assessments,…

Automatically identifying struggling students learning to program can assist teachers in providing timely and focused help. This work presents a new deep-learning language model for predicting "bug-fix-time", the expected duration between when a software bug occurs and the time it will be fixed by the student. Such information can guide…