Debugging compiler errors is essential to programming and can be challenging for novice programmers. In introductory computer science courses, challenging errors can discourage students. One reason these errors are difficult to resolve is that most ...

Collaborative learning has demonstrated benefits for girls in computer science [7] and this may be a way to help address the gender gap in CS. Research indicates that while collaborating, boys often express more individualistic ideas whereas girls tend ...

While much attention has focused on promoting computational thinking in K-12 CS education, much less attention has been paid to the equally significant dimension of what it means to identify with the discipline. Previous approaches to CS identity have ...

Programming is increasingly being taught in statistics modules across various departments, where the focus is on wrangling data in languages like Python and R. Graphical aids as applied to this domain is an empirically untried approach. My research ...

Timely feedback is essential for students to learn and improve their performance. However, it is hard for computing instructors to provide real-time feedback for every student, particularly during homework or online classes. While researchers have put ...

Dynamically adaptive Parsons problems are pieces of code that must be ordered and indented correctly. Performance on prior problems determines the difficulty of subsequent ones. These problems comprise an adaptive learning system that dynamically adapts ...

Prior work suggests that novice programmers are greatly impacted by the feedback provided by their programming environments. While some research has examined the impact of feedback on student learning in programming, there is no work (to our knowledge) ...

Metacognition and self-regulation are popular areas of interest in programming education, and they have been extensively researched outside of computing. While computing education researchers should draw upon this prior work, programming education is ...

Machine learning systems are increasingly a part of everyday life, and often used to make critical and possibly harmful decisions that affect stakeholders of the models. Those affected need enough literacy to advocate for themselves when models make ...