About

Raymond Pettit is an Associate Professor, Academic General Faculty, Teaching Track, in the Department of Computer Science at the University of Virginia. He has a background of 12 years in industry, where he wrote software for six different private companies and government research organizations. In 2004, he returned to graduate school, working as a graduate assistant while pursuing a Ph.D. He began teaching as an adjunct faculty member in 2006 and transitioned to full-time faculty positions as he completed his dissertation. In 2018, he left Abilene Christian University after 12 years to join the University of Virginia. His professional experience combines industry and academia, with a focus on computer science.

Research topics

• Computer Science
• Sociology
• Political Science
• Engineering
• Mathematics education
• Psychology
• Artificial Intelligence
• Social Science
• Pedagogy
• Public relations
• Engineering ethics
• Electrical engineering
• Human–computer interaction
• Medical education
• Data science
• Medicine

Selected publications

• An International Examination of Non-Technical Skills and Professional Dispositions in Computing -- Identifying the Present Day Academia-Industry Gap

  2025-01-22 · 4 citations

  article

  Computing graduates are frequently reported by members of industry to lack in professional dispositions and/or non-technical skills (often referred to as "soft skills"). In this work, we conduct a gap analysis of the alignment between academic preparation and industry expectations through a three-pronged study. First, a literature review explored the academic perspective of how fostering professional dispositions and non-technical skills occurs in tertiary computing education. Second, a literature review identifying industry's expectations of those dispositions and skills for entry-level computing professionals. Finally, a mixed-methods approach, combining a survey and structured interviews of computing industry professionals to identify their opinions on the relative importance of those skills and dispositions. In each of these prongs, we additionally consider whether and how Diversity, Equity, Inclusion, and Accessibility (DEIA) may have been approached and/or incorporated.

  PublisherDOI

• GenAI Integration in Upper-Level Computing Courses

  2025-06-13 · 3 citations

  article

  GenAI is playing an increasingly important role in computing courses at all levels, offering new opportunities to support teaching and learning. However, using GenAI effectively raises important concerns regarding trust, academic integrity, and broader social and ethical dimensions. This Working Group was formed to report on the current state of the art in using GenAI in upper-level computing courses to aid educators. The working group will undertake a methodological review of published work and solicit input from the computing educational community as part of the report.

  PublisherDOI

• The Rest of the Robots: Generative AI in Post-introductory Computing Education

  2025-06-27

  articleOpen access

  Generative AI (GenAI) is playing an increasingly influential role in computing education across all levels, offering new opportunities to support both teaching and learning. However, its effective integration raises critical concerns related to trust, academic integrity, and broader social and ethical implications. While substantial attention has been given to GenAI use in introductory programming courses (e.g., CS0/CS1), there remains a notable gap in research addressing its application in upper-level computing courses, such as software engineering, human-computer interaction, algorithms, operating systems, and theoretical computer science. This working group report presents two complementary studies: A systematic literature review of GenAI interventions in upper-level computing education, and a survey of computing instructors on their practices and perspectives regarding GenAI integration in these contexts. Based on the combined findings, this report presents an overview of current practice and practical guidance for computing instructors. The report is intended to inform the design of engaging, pedagogically sound, and forward-looking curricula that align with modern educational and workforce standards and expectations.

  PublisherDOI

• Performance, Workload, Emotion, and Self-Efficacy of Novice Programmers Using AI Code Generation

  2024-07-03 · 9 citations

  articleOpen access

  Artificial Intelligence-driven Development Environments (AIDEs) offer developers revolutionary computer programming assistance. There is great potential in incorporating AIDEs into Computer Science education; however, the effects of these tools should be fully examined before doing so. Here, a within-subjects study was conducted to compare the programming performance, workload, emotion, and self-efficacy of seventeen novices coding with and without use of the GitHub Copilot AIDE under time pressure. Results showed that using the AIDE significantly increased programming efficiency and reduced effort and mental workload but did not significantly impact emotion or self-efficacy. However, participants' performance improved with more experience using the AI, and their self-efficacy followed. The results suggest that students who try AIDEs will likely be tempted to use them for time-sensitive work. There is no evidence that providing AIDEs will aid struggling students, but there is a clear need for students to practice with AI to become competent and confident using it.

  PublisherDOI

• All for One and One for All - Collaboration in Computing Education: Policy, Practice, and Professional Dispositions

  2024-07-04 · 1 citations

  article

  The ITiCSE '23 final keynote raised teaching soft skills, or professional dispositions, to help students face challenges in modern programming. This project addresses helping computing students develop professional dispositions through collaborative learning (CL) since some in the industry observe entry-level engineers struggling due to their fragile professional dispositions. We are motivated to understand professional expectations from entry-level engineers and present the academia-industry gap to support practitioners and researchers in advancing CL in Computing Education, encouraging positive curricula and policy changes that promote DEIA. We will present CL practices alongside their supported professional dispositions to assist practitioners in adoption. We will present the academia-industry gap in CL for future research opportunities, helping researchers advance CL practices to integrate professional dispositions the industry expects from entry-level engineers.

  PublisherDOI

• Office Hours and Online Forum Engagement in Introductory CS Courses

  2024-10-13

  article

  This research full paper explores the connection between office hours use and online forum engagement in introductory computer science courses. Office hours (OH) and online question-and-answer (Q&A) forums provide a platform for students to interact with their classmates and instructors. We investigate the relationship between student engagement in an online discussion forum (Piazza) and utilization of office hours across 5 semesters of an introductory CS course. We explored the correlation between Piazza utilization and OH attendance, discerned disparities between in-person and online OH involvement, and analyzed the distinct approaches of men and women in engaging with course resources. We found that active Piazza users visit OH more than inactive Piazza users. More specifically, students who interact above average on Piazza in each metric observed - asks, answers, posts, and views - attend OH more than those who are below average in each metric. Additionally, students who attend OH at least once tend to post, ask, answer, and view posts on Piazza more frequently than those who have never attended OH. This indicates that above average help-seeking students on Piazza and in OH tend to engage with available resources more than those who did not seek help as often. This quantifies how often - and through which methods - students seek help. Based on prior research and our findings, we find it likely that students often begin by seeking answers on Piazza. If they find the response unsatisfactory, they then resort to OH for clarification. We also examined the modality of office hours, comparing in-person and online interactions; there is no significant statistical difference in the number of OH visits between those who attend virtually vs those who attend in person. However, online OH visits tended to take longer than in-person visits. In terms of the relationship between engagement and gender, our findings show that women visit OH more than men, both in person and online, and take longer in their OH visits. These findings emphasize the importance of course engagement resources in assisting with learning while also highlighting factors that affect engagement, such as gender, mode of engagement, and usage of other resources, giving instructors a better understanding of which populations tend to engage with specific course resources.

  PublisherDOI

• Project-Based and Assignment-Based Courses: A Study of Piazza Engagement and Gender in Online Courses

  2023-06-29 · 4 citations

  articleOpen accessSenior author

  Project-based (PB) learning has become increasingly popular in computer science education, particularly as studies have found that the teaching style better prepares students for future careers and improves learning outcomes through increased student engagement. Online forum usage is one measurable component of engagement. In order to study the impact of PB learning on online forum engagement, Piazza usage data from seven online computer science courses at a higher education institution were collected and examined. We analyzed the differences in online forum usage between PB and assignment-based (AB) learning, in addition to differences between men and women in each course type. Specifically, this study builds upon and replicates a previous study on Piazza that measured student engagement, anonymity usage, and peer parity. We found that students in PB courses were less actively engaged in online forums than students in AB courses; they were less likely to ask and answer questions on Piazza but were more likely to view posts and be logged on more days. Across both course types, students posted anonymously a similar amount as a proportion of the total number of questions and answers and experienced a proportionally similar amount of peer parity. Our findings mirror prior results on gender engagement on Piazza. Across both PB and AB courses, women were more engaged, asked and viewed more questions, posted anonymously more frequently, and were less likely to experience peer parity than men.

  PublisherOA PDFDOI

• The Robots Are Here: Navigating the Generative AI Revolution in Computing Education

  2023 · 305 citations

  • Computer Science
  • Artificial Intelligence
  • Computer Science

  Recent advancements in artificial intelligence (AI) and specifically generative AI (GenAI) are threatening to fundamentally reshape computing and society. Largely driven by large language models (LLMs), many tools are now able to interpret and generate both natural language instructions and source code. These capabilities have sparked urgent questions in the computing education community around how educators should adapt their pedagogy to address the challenges and to leverage the opportunities presented by this new technology. In this working group report, we undertake a comprehensive exploration of generative AI in the context of computing education and make five significant contributions. First, we provide a detailed review of the literature on LLMs in computing education and synthesise findings from 71 primary articles, nearly 80% of which have been published in the first 8 months of 2023. Second, we report the findings of a survey of computing students and instructors from across 20 countries, capturing prevailing attitudes towards GenAI/LLMs and their use in computing education contexts. Third, to understand how pedagogy is already changing, we offer insights collected from in-depth interviews with 22 computing educators from five continents. Fourth, we use the ACM Code of Ethics to frame a discussion of ethical issues raised by the use of large language models in computing education, and we provide concrete advice for policy makers, educators, and students. Finally, we benchmark the performance of several current GenAI models/tools on various computing education datasets, and highlight the extent to which the capabilities of current models are rapidly improving.

  PublisherOA PDFDOI

• Transformed by Transformers: Navigating the AI Coding Revolution for Computing Education: An ITiCSE Working Group Conducted by Humans

  2023 · 26 citations

  • Computer Science
  • Computer Science
  • Sociology

  The recent advent of highly accurate and scalable large language models (LLMs) has taken the world by storm. From art to essays to computer code, LLMs are producing novel content that until recently was thought only humans could produce. Recent work in computing education has sought to understand the capabilities of LLMs for solving tasks such as writing code, explaining code, creating novel coding assignments, interpreting programming error messages, and more. However, these technologies continue to evolve at an astonishing rate leaving educators little time to adapt. This working group seeks to document the state-of-the-art for code generation LLMs, detail current opportunities and challenges related to their use, and present actionable approaches to integrating them into computing curricula.

  PublisherOA PDFDOI

• The Robots are Here: Navigating the Generative AI Revolution in Computing Education

  arXiv (Cornell University) · 2023-10-01 · 8 citations

  preprintOpen access

  Recent advancements in artificial intelligence (AI) are fundamentally reshaping computing, with large language models (LLMs) now effectively being able to generate and interpret source code and natural language instructions. These emergent capabilities have sparked urgent questions in the computing education community around how educators should adapt their pedagogy to address the challenges and to leverage the opportunities presented by this new technology. In this working group report, we undertake a comprehensive exploration of LLMs in the context of computing education and make five significant contributions. First, we provide a detailed review of the literature on LLMs in computing education and synthesise findings from 71 primary articles. Second, we report the findings of a survey of computing students and instructors from across 20 countries, capturing prevailing attitudes towards LLMs and their use in computing education contexts. Third, to understand how pedagogy is already changing, we offer insights collected from in-depth interviews with 22 computing educators from five continents who have already adapted their curricula and assessments. Fourth, we use the ACM Code of Ethics to frame a discussion of ethical issues raised by the use of large language models in computing education, and we provide concrete advice for policy makers, educators, and students. Finally, we benchmark the performance of LLMs on various computing education datasets, and highlight the extent to which the capabilities of current models are rapidly improving. Our aim is that this report will serve as a focal point for both researchers and practitioners who are exploring, adapting, using, and evaluating LLMs and LLM-based tools in computing classrooms.

  PublisherOA PDFDOI

Frequent coauthors

• James Prather

  Abilene Christian University

  21 shared

• Brett A. Becker

  University College Dublin

  18 shared

• Paul Denny

  Temple University

  18 shared

• Michelle Craig

  University of Toronto

  12 shared

• Tobias Kohn

  11 shared

• Juho Leinonen

  Aalto University

  11 shared

• Hieke Keuning

  11 shared

• Andrew Luxton-Reilly

  University of Auckland

  11 shared

Education

• Ph.D., Computer Science

  Texas Tech University

  2015