Generative AI is a disruptive technology that has the potential to transform many aspects of how computer science is taught. Like previous innovations such as high-level programming languages and block-based programming languages, generative AI lowers the technical expertise necessary to create working programs, bringing the power of computation…

Automatic program repair (APR) tools are valuable for students to assist them with debugging tasks since program repair captures the code modification to make a buggy program pass the given test-suite. However, the process of manually generating catalogs of code modifications is intricate and time-consuming. This article proposes contextual error…

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…

Mastery-based assignments typically provide students with multiple opportunities to improve their performance, but getting students to take advantage of these opportunities is difficult. We report on the implementation of a two-part series of nudges designed to improve students' engagement with and performance on mastery-based assignments in…

Background and Context. Computing is considered a fundamental skill for civic engagement, self-expression, and employment opportunity. Despite this, there exist significant equity gaps in post-secondary computing enrollment and retention. Specifically, in the California State University (CSU) system, which serves close to half a million…

Background and Context: Considerable numbers of Computer science (CS) undergraduate majors struggle in Theory of Computation (ToC) courses, which strengthen bimodality beliefs of student performance. Reasons for students struggling are assumed to be manifold but substantial ground is based on studies providing singular insights into this matter.…

This paper focuses on a historically understudied area in computing education: attending to students' *design thinking* in university-level introductory programming courses. I offer an account of one student--"Rebecca"--and her experiences and code from a second-semester course on programming concepts for engineers. Using data from both…

All students studying Computer Science (CS) deserve to have their basic psychological need for belonging satisfied. In this dissertation, I present two studies of belonging among CS students at the University of Washington-Paul G. Allen School of Computer Science and Engineering. In the first study, my collaborators implemented a resubmission…

This paper describes an introductory biology course for undergraduates that heavily incorporates quantitative problem solving in activities and homework assignments. The course is broken up into a series of units, each organized around a motivating biological question or theme. Homework assignments address the theme or question, and typically…

This paper introduces a teaching process to develop students' problem-solving and programming efficacy in an introductory computer programming course. The proposed teaching practice provides step-by-step guidelines on using worked-out examples of code to demonstrate the applications of programming concepts. These coding demonstrations explicitly…

Controlling complexity through the use of abstractions is a critical part of problem solving in programming. Thus, becoming proficient with procedural and data abstraction through the use of user-defined functions is important. Properly using functions for abstraction involves a number of other core concepts, such as parameter passing, scope and…

Teaching introductory programming courses to university students who come from a varied set of academic and non-academic backgrounds is challenging. Students who are learning programming for the first time can become easily discouraged leading to procrastination that subsequently can have an unfavorable effect on their learning outcomes, and…

Knowledge tracing (KT) models are a popular approach for predicting students' future performance at practice problems using their prior attempts. Though many innovations have been made in KT, most models including the state-of-the-art Deep KT (DKT) mainly leverage each student's response either as correct or incorrect, ignoring its content. In…

This paper presents field-tested improvements over an 11-year period of a large-scale "Introduction to Information Systems" core business school course and provides a framework for implementation. Engagement and learning in large-scale courses can prove challenging, especially when the class is a requirement within a business school's…

This is an experience paper that describes methods of student assessment in introductory- and intermediate-level computing courses. The paper explains the need for alternate methods in the evaluation of out-of-class programming assignments and enumerates several options that have been incorporated into freshman- and sophomore-level courses. I show…