Students face several difficulties in introductory programming courses (CS1), often leading to high dropout rates, student demotivation, and lack of interest. The literature has indicated that the adequate use of gamification might improve learning in several domains, including CS1. However, the understanding of which (and how) factors influence…

In recent years, computing education researchers have investigated the impact of problem context on students' learning and programming performance. This work continues the investigation motivated, in part, by cognitive load theory and educational research in computer science and other disciplines. The results of this study could help inform…

Objectives: We aim to understand, from a motivational perspective, how Black undergraduate women in computing make sense of their intersectional computing experiences. We examine their motivation to major in computing, their experiences as Black women in computing, and how these vary across institutional contexts. Participants: A sample of 77…

Two studies investigated change in computer science (CS) students' implicit intelligence beliefs. Across both studies, we found that the strength of incremental and entity beliefs changed across time. In Study 1, we found that incremental beliefs decreased and entity beliefs increased across the semester. Change in implicit intelligence beliefs…

Active and collaborative learning has shown considerable promise for improving student outcomes and reducing group disparities. As one common form of collaborative learning, pair programming is an adapted work practice implemented widely in higher education computing programs. In the classroom setting, it typically involves two computer science…

Software modeling is an integral practice for software engineers, especially as the complexity of software solutions increases. Unified Modeling Language (UML) is the industry standard for software modeling. however, it is often used incorrectly and misunderstood by novice software designers. This study is centered around understanding patterns of…

What if "regular" Computer Science (CS) faculty each taught elements of inclusive design in "regular" CS courses across an undergraduate curriculum? Would it affect the CS program's climate and inclusiveness to diverse students? Would it improve retention? Would students learn less CS? Would they actually learn any inclusive…

Learning to program requires perseverance, practice, and the mindset that programming skills are improved through these activities (i.e., that everyone has the potential to become good at programming). In contrast to an entity mindset, individuals with an incremental mindset believe that ability is malleable and can be improved with effort. Prior…

While computing programs in the U.S. are experiencing growth in enrollment trends, they are still grappling with matters related to retention and persistence of computing undergraduates. One construct identified by scholars as having an impact on persistence in computing is computing identity, which is shaped by constructs such as recognition,…

The change in the English computing curriculum and the shift towards computer science (CS) has been closely observed by other countries. Female participation remains a concern in most jurisdictions, but female attainment in CS is relatively unstudied. Using the English national pupil database, we analyzed all exam results (n = 5,370,064) for…

Gamification is the use of game elements in domains other than games. Gamification use is often suggested for difficult activities because it enhances users' engagement and motivation level. Due to such benefits, the use of gamification is also proposed in education environments to improve students' performance, engagement, and satisfaction.…

Several experiments on the effects of pair programming versus solo programming in the context of education have been reported in the research literature. We present a meta-analysis of these studies that accounted for 18 manuscripts with 28 independent effect sizes in the domains of programming assignments, exams, passing rates, and affective…

The computing education research literature contains a wide variety of methods that can be used to identify students who are either at risk of failing their studies or who could benefit from additional challenges. Many of these are based on machine-learning models that learn to make predictions based on previously observed data. However, in…

The number of computer science (CS) courses has been dramatically expanding in U.S. high schools (HS). In comparison with well-established courses in mathematics and science, little is known about how the decisions made by HS CS teachers regarding how and what to teach impact student performance later in introductory college CS courses. Drawing on…

We describe a method for analyzing student data from online programming exercises. Our approach uses contingency tables that combine whether or not a student answered an online exercise correctly with the number of attempts that the student made on that exercise. We use this method to explore the relationship between student performance on online…