SIGCSE 2025

Computer science education is evolving rapidly. With AI reshaping how students learn and traditional pedagogical practices sometimes feeling disconnected from real-world applications, educators are searching for better ways to engage students. At SIGCSE 2025, I’m collaborating with colleagues to explore three key areas: hands-on learning with robotics, the role of teaching assistants (TAs), and making quantum programming more accessible.

In one project, I teamed up with fellow SCI instructor Melinda McDaniel to rethink how we teach introductory programming. Instead of just writing code in isolation, students programmed robots to navigate obstacles and simulate delivery routes, helping them develop systems-level thinking. This hands-on approach goes beyond coding; it builds confidence, curiosity, and the ability to troubleshoot in complex, unpredictable scenarios. Compared to students doing traditional web development labs, those in the robotics group showed more confidence in their coding skills and a better understanding of systems thinking. Plus, they had fun—some even recorded their robots in action to share with friends.

On another front, in a collaboration between Georgia State University and Georgia Tech, we’ve been studying the evolving role of Teaching Assistants (TAs) in computer science education. By surveying TAs at both institutions, we explored how they support students beyond grading and technical assistance. Our findings highlight that TAs often act as mentors and motivators, bridging the gap between students and faculty. As AI becomes more integrated into education, this research underscores the critical human element of teaching and the importance of well-trained, engaged TAs.

Finally, I’ve been working with Austin Adams and others on making quantum computing more approachable. Most introductory quantum courses rely heavily on complex math and physics notation, which can discourage students. We’re proposing a quantum-focused CS1 course using Qwerty, a Python-based language developed by Austin and Thomas Conte. This approach allows students to experiment with quantum concepts from day one, helping them build intuition before tackling formal notation.

Across all these projects, the common theme is making computer science education more engaging, accessible, and practical. Whether it’s through hands-on robotics, stronger TA support, or simplifying quantum programming, my SIGCSE work is about giving students better ways to learn, and making sure they feel supported along the way.

Teaching Assistants (TAs) play a major role in students’ experiences of a course. TAs may grade student work, design assignments, or run office hours, among other tasks to help the instructor. Especially in large classes, students may only have direct interaction with their TAs. Given this vital role, our research team wanted to know: how do TAs themselves perceive their job?

While most TAs who responded to our survey of Computer Science TAs (CSTAs) reported grading as a component of their job, there were also more humanistic components of their role that resonated with them.

Some connected with being in a “helping” role, such as one participant who partially described a part of their job to “make [the students] feel cared for.” Others connected with being an “inspirer,” such as one who said, “I also see myself as someone who lights the spark to become excited about computer science.” Still others connected with the idea of being a “bridger,” or someone who can connect the perspectives of both the students and the instructor, such as the participant who stated, “understanding the students’ struggles is much easier for someone who has taken the class or equivalent.”

Rather than focusing solely on the administrative tasks, the CSTAs in our survey also described how important their personal relationships with their students can be, such as being in a role where they can inspire students. Particularly with the rise of generative AI, we want to emphasize these more humanistic elements of a TA job which cannot be replaced by a machine.

I’ll be co-presenting two AI applications closely tied to my work as associate dean for undergraduate education. One project, “Scaling Academic Decision-Making with NLP: Automating Transfer Credit Evaluations,” addresses the challenges of manually evaluating transfer credit requests in our large undergraduate program. We trained LLMs on a diverse set of syllabi from various CS departments, applying techniques like chain-of-thought reasoning and reflection agents. Our results demonstrate that LLMs can effectively and accurately help automate a significant portion of these evaluations, reducing the workload on admissions staff and improving consistency. This work suggests broader applications of NLP for automating other manual, evaluation-based processes, both within and beyond computing programs. My collaborators for this project are Nimisha Roy (SCI faculty and lead) and Huaijin Tu (undergraduate researcher).

The second project, “Empowering Future Software Engineers: Integrating AI Tools into Advanced CS Curriculum,” explores the question of when—in a typical four-year CS curriculum—to officially teach students the use of AI tools for automation and improved productivity in software development. We describe a “right-left” approach; i.e., formal training should initially occur after students master fundamental software development skills and can confidently build medium- to large-sized programs. Then, as these tools mature and the risks of “hallucinations” diminish, we can then integrate instruction earlier in the curriculum, potentially reducing the need for extensive training in conventional programming skills. We propose capstone design—typically taken by juniors and seniors—as an ideal starting point on the “right” end of the curriculum and document our experiences running a generative AI-first version of this course. My collaborators for this project are Nimisha Roy (SCI faculty and lead) and Oleksandr Horielko (undergraduate researcher).

DataWorks at Georgia Tech is innovating new pathways to the data workforce. As a data services provider, DataWorks hires adults without technical backgrounds for one-year terms as “Data Fellows,” paying them to learn data skills while working on real client projects—a departure from traditional bootcamps or degree programs that are costly and may require participants to stop working.

Our research examines the four-year journey of developing an integrated work-training curriculum across four cohorts and 15 employees. The curriculum combines client project work with training in Excel, Python, critical data literacy, and career development. In reflecting on our experience, we contribute key insights about workplace computing education: adult learners have diverse motivations beyond entering typical tech careers; programs must balance adaptability with stability; and workplace needs often challenge traditional computer science education approaches.

This research is a collaboration between academics and DataWorks employees. The second author of this work, Dana Priest, provided an insider perspective in this research—she began at DataWorks as a Data Fellow and was promoted to Training Coordinator, where she now leads curriculum development and instruction. Graduate students developed several modules of the curriculum, and we hired a high school teacher to fine tune the curriculum design.

Our findings demonstrate that expanding career pathways beyond purely technical roles—including positions in research administration and project management—better served Data Fellows’ goals and expanded our ideas about what constitutes computing work and education. The DataWorks model demonstrates how integrating computing education into paid work can create accessible pathways for adults to develop valuable data skills. Our curriculum is freely available online so other organizations can adapt our approach.

Our work at SIGCSE 2025 focuses on fostering collaboration within student-led project teams through a student-driven formation process. Instead of assigning teams, students are encouraged to form groups based on shared interests, availability, and communication preferences. This open approach promotes meaningful collaboration, as students can select teammates who align with their goals, leading to greater engagement and better project outcomes.

The team formation process is supported by course staff through platforms like Ed Discussion, which allows students to introduce themselves, share interests, and organize their teams. Ongoing support from Teaching Assistants (TAs) helps manage team dynamics, resolve conflicts, and provide constructive feedback. TAs offer actionable advice, guiding students through challenges and ensuring everyone contributes to the project.

By focusing on collaboration, communication, and feedback, we have seen significant success, with around three teams needing intervention each semester among over 200 teams. This approach enhances students’ academic performance and prepares them for the collaborative environments they will encounter in their future careers.

ACM Student Research Competition Posters

Retaining Undergraduate Teaching Assistants by Promoting Professional Growth and Fostering a Strong Community

Zhixian Liding (Georgia Institute of Technology), Athena Malek (Georgia Institute of Technology)

In the face of increasing student enrollment in CS1 and CS2 classes, high undergraduate teaching assistant (UTA) retention rates are necessary for a strong and sustainable teaching assistant (TA) program. However, the motivation for UTAs to ascend to harder, more rigorous courses and the onset of boredom through fulfilling monotonous UTA responsibilities disincentive UTAs from staying with an introductory course for more than a few semesters. This paper reports on a unique approach to a UTA-led management of UTA teams that prioritizes professional growth, facilitates leadership development, and fosters a strong community with a central TA identity—all while enhancing the student educational experience.

ACM TOCE Journal

Ethics, Power, and Persistence

“Show them the playbook that these companies are using”: Youth Voices about why Technology Education Must Center Discussions of Power, Ethics, and Culturally Responsive ComputingMSI

Jean Ryoo (UCLA Computer Science Equity Project), Takeria Blunt (Georgia Institute of Technology)

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Identity, Careers, and Learning

CS=Me: Exploring Factors that Shape Black Women’s CS Identity at the Intersections of Race and GenderMSI

Krystal Williams (University of Georgia), Edward Dillon (Morgan State University), Shanice Carter (University of Alabama), Janelle Jones (University of Alabama), Shelly Melchior (Georgia Institute of Technology)

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Identity, Careers, and Learning

You’re Hired! A Phenomenographic Study of Undergraduate Students’ Pathways to Job Attainment in Computing

Stephanie Lunn (Florida International University), Ellen Zerbe (Georgia Institute of Technology), Monique Ross (The Ohio State University)

Demos

KimBilet.com: Leveraging Generative AI for Personalized Learning Experiences

Mirbek Dzhumaliev (KimBilet.com), Aibek Musaev (Georgia Institute of Technology), Calton Pu (Georgia Institute of Technology)

This demo presents KimBilet.com, an educational platform that utilizes generative AI to create personalized educational content on demand. Catering to high-school and college students, instructors, job seekers, and lifelong learners, the system generates customized courses based on user prompts, covering any topic of interest. Each course may include a sequence of AI-created lessons and quizzes, providing detailed feedback for every quiz option to enhance understanding. The platform supports intuitive navigation through keyboard shortcuts and allows users to jump between course items seamlessly.

Flock

Creating a Community of Graduate Student Computer Science Education Researchers

Grace Barkhuff (Georgia Institute of Technology), Katherine Braught (University of Illinois at Urbana-Champaign), Emma R. Dodoo (University of Michigan), Michael Link (University of Florida), Xinying Hou (University of Michigan), Elliot Roe (Georgia Institute of Technology)

This Birds of a Feather (BoF) session serves to build a community of graduate student researchers in Computer Science Education (CSEd) at SIGCSE TS and beyond. Many graduate students lack a CSEd research community within their own institution. This BoF session will serve to provide a space for SIGCSE TS graduate students to build their community across institutions, both during and after the conference. During the session, we will discuss the successes and challenges that come with being a CSEd graduate student, including work/life balance, advisor-student relationships, and developing collaborations. Attendees will leave with an opportunity to connect with other CSEd graduate students after the conference through a dedicated CSEd graduate student Slack channel.

Lightning Talks

Empowering Future Software Engineers: Integrating AI Tools into Advanced CS Curriculum

Nimisha Roy (Georgia Institute of Technology), Fisayo Omojokun (Georgia Institute of Technology), Oleksandr Horielko (Georgia Institute of Technology)

Artificial Intelligence (AI) tools have transformed software development, making it crucial to equip computer science (CS) students with the skills to leverage these technologies. This talk presents an innovative curriculum approach, integrating AI tools into an advanced CS capstone course at a stage where students possess foundational skills in software engineering. This strategic timing ensures that students can critically engage with AI, recognizing biases and managing challenges like hallucinations in AI-generated outputs.

Panel

Innovative Approaches to CS Education Research that Enable All Students’ Success (Hybrid)

Monica McGill (Institute for Advancing Computing Education), Joseph Carroll-Miranda (University of Puerto Rico, Rio Piedras Campus), Joshua Childs (The University of Texas at Austin), Stefanie Marshall (Michigan State University), Tamara Pearson (Georgia Institute of Technology)

What does it mean to conduct computer science education research in a manner that ensures that the evidence produced is high quality and benefits a wide variety of students? One can pour over various guides from institutions like What Works Clearinghouse (WWC) and the American Psychology Association (APA). However, what many standards like is a holistic perspective of an education re- search field and how the aggregated data presented represents the student population that the research will ultimately serve. In this panel, we tackle both and explore approaches that have been used in other education research fields as well as those appropriate to CS education research that can be leveraged to ensure that all students’ needs, experiences, cultures, identities, and voices are captured and presented in our research.

Paper

Data Science

A Window into DataWorks: Developing an Integrated Work-Training Curriculum for Novice Adults

Lara Schenck (Georgia Institute of Technology), Dana Priest (DataWorks at Georgia Tech), Gabe Dubose (Emory University), Zajerria Godfrey (Maynard Jackson High School), Annabel Rothschild (Georgia Institute of Technology), Benjamin Shapiro (Georgia State University), Betsy Disalvo (Georgia Institute of Technology)

Computing education is often confined to the context of formal education or after-school programs; however, there is a growing industry built around adult education, including workshops, coding intensives, online learning, and the workplace. Amidst these efforts, little research has explored the workplace as a site for novice adult learners to develop computing skills. In this experience report, we present an integrated training curriculum for adults at DAP (Data Apprenticeship Program), an organization that trains and employs novice adults from groups historically underrepresented in computing who seek to advance their career through on-the-job learning. “Data Apprentices” are hired to complete client projects by providing data services for local organizations, nonprofits, and businesses. Training is integrated into employees’ weekly responsibilities at DAP, and the curriculum consists of four modules: Microsoft Excel, Critical Data Literacy, Python Fundamentals, and Career Development. In this report, we reflect holistically on the evolution of the curriculum over the years. We distill our reflection into insights to inform other integrated training programs that aim to equip novice adults with computing skills in the workplace.

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Ethics

Towards a More Inclusive Curriculum: Opportunities for Broadening and Diversifying Computing Ethics Education

Grace Barkhuff (Georgia Institute of Technology), Jason Borenstein (Georgia Institute of Technology), Daniel Schiff (Purdue University), Judith Uchidiuno (Georgia Institute of Technology), Ellen Zegura (Georgia Institute of Technology)

Computing ethics instruction is a vital aspect of the undergraduate computing curriculum. It has received greater focus in recent years driven in part by concerns about the societal impacts of computing technologies such as social media and artificial intelligence. The increased attention provides an opportunity, even imperative, to examine and rethink common practices. To support our understanding of current practices in computing ethics education, we surveyed 318 computing educators in the United States (U.S.), including 56 who have never taught ethics.

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TA Training and Retention

Exploring the Humanistic Role of Computer Science Teaching Assistants across Diverse Institutions

Grace Barkhuff (Georgia Institute of Technology), Ian Pruitt (Georgia State University), Vyshnavi Namani (Georgia Institute of Technology), William Gregory Johnson (Georgia State University), Rodrigo Borela (Georgia Institute of Technology), Ellen Zegura (Georgia Institute of Technology), Anu Bourgeois (Georgia State University), Benjamin Shapiro (Georgia State University)

In this paper, we use qualitative methods to analyze 109 survey responses collected across two different institutions as part of a larger design-based research project to make two contributions. First, we illustrate how CS TAs adopt humanistic stances and demonstrate care in their roles, thereby expanding prevailing understandings of CS TAs. Second, we detail similarities and differences across CS TAs’ experiences at each institution that underscore the importance of understanding CS TAs as they are situated in different institutional contexts.

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Teaching Practices

Enhancing CS1 education through experiential learning with robotics projects

Rodrigo Borela (Georgia Institute of Technology), Zhixian Liding (Georgia Institute of Technology), Melinda McDaniel (Georgia Institute of Technology)

To meet the challenges posed by generative AI’s ability to solve homework problems and a competitive internship market, CS1 education is evolving to emphasize higher-level problem-solving and systems thinking. In response, a novel experiential learning initiative grounded in High-Impact Practices was introduced to a CS1 course over the course of 2 semesters, involving 133 students. This initiative utilized robotics lab assignments to enhance computational thinking, real-world application, and job market readiness through hands-on programming projects. Emphasizing project-based learning, significant engagement time, and reflective practices, the approach aimed to deepen understanding and engagement. The curriculum included both individual and team projects to develop foundational skills and encourage collaborative problem-solving. We assessed the impact of this initiative against a control group of 439 students in traditional web development labs, using course and instructor evaluations, thematic student reflections, and exam performances. The results indicated a substantial positive effect on learning outcomes, particularly among novices. The experiential learning group demonstrated increased confidence in real-world applications, heightened engagement, and greater computational skill improvement. Notably, they showed a twofold improvement in understanding course topics, as reflected in their exam grades, compared to the control group. These findings underscore the effectiveness of integrating practical, interactive elements into computer science education to align with current technological and professional demands.

Posters

A Blueprint for Q-CS1, an Introductory Quantum Programming Course

Austin J. Adams (Georgia Institute of Technology), Rodrigo Borela (Georgia Institute of Technology), Jeffrey Young (Georgia Institute of Technology), Thomas Conte (Georgia Institute of Technology)

Despite the need to build a quantum workforce, current courses that introduce quantum programming are rooted in quantum notation that students may find intimidating. We propose Q-CS1, a quantum equivalent of CS1 that begins with hands-on quantum programming. Q-CS1 is enabled by the Qwerty quantum programming language, which allows for reasoning about qubit behavior without physics notation or quantum circuits. An outline of Q-CS1 is provided along with plans for assessing its effectiveness.

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Broadening CS Research Opportunities for Online Graduate Students

Bobbie Eicher (Georgia Institute of Technology), Alex Duncan (Georgia Institute of Technology), Dante Ciolfi (Georgia Institute of Technology), Maria Konte (Georgia Institute of Technology), Nicholas Lytle (Georgia Institute of Technology)

In a master’s degree, research opportunities offer a way for students to apply knowledge, create projects they can market to employers, and gain familiarity with the research process in preparation for doctoral study. As more students choose online programs, it is crucial to examine how to replicate these offerings in the digital space to ensure online students have access to the full range of educational opportunities. In this poster, we discuss our experience building the infrastructure for expanding research opportunities. We talk about a few efforts we have begun to establish at our online program, namely dedicated courses and seminars for research-interested students, and supports for connecting faculty to student projects. We discuss our intended future efforts to build research infrastructure to help manage and facilitate research experiences at scale.

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Examining Student Interest and Motivations in Graduate Computer Science Research

Bobbie Eicher (Georgia Institute of Technology), Alex Duncan (Georgia Institute of Technology), Dante Ciolfi (Georgia Institute of Technology), Maria Konte (Georgia Institute of Technology), Nicholas Lytle (Georgia Institute of Technology)

The research focuses in academia are typically driven from the top down, with professors primarily focusing on projects that align with their existing lab or can be readily supported by grants. Student interest in learning how research is done, however, does not always align with those existing focuses.

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Managing Project Teams in an Online Class of 1000+ Students

Nazanin Tabatabaei Anaraki (Georgia Institute of Technology), Taneisha Ng (Georgia Institute of Technology), Gaurav Verma (Georgia Institute of Technology), Yu Fu (Georgia Institute of Technology), Martin Oconnell (Georgia Institute of Technology), Matthew Hull (Georgia Institute of Technology), Susanta Routray (Georgia Institute of Technology), Max Mahdi Roozbahani (Georgia Institute of Technology), Duen Horng Chau (Georgia Institute of Technology)

We discuss our approach of managing, evaluating, and providing constructive feedback on over 200 project teams, comprising 1000+ graduate students distributed globally, two pro- fessors, and 25+ teaching assistants. We deployed and iteratively refined this approach over 10 years. Our approach and insights can help others striving to make CS education accessible, especially in online and large-scale settings.

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Scaling Academic Decision-Making with NLP: Automating Transfer Credit Evaluations

Nimisha Roy (Georgia Institute of Technology), Fisayo Omojokun (Georgia Institute of Technology), Huaijin Tu (Georgia Institute of Technology)

Manual processes for evaluating external course syllabi for transfer credit in higher education are time-consuming, inconsistent, and prone to bias. This project leverages Natural Language Processing (NLP) and large language models (LLMs) to automate the transfer credit evaluation process. The system processes external syllabi by embedding course content, conducting similarity searches, and providing structured reasoning for each match. Using techniques such as chain-of-thought reasoning and reflection agents, the system generates similarity scores and detailed explanations to support informed, data-driven decision-making by faculty.

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Teaching Assistants’ Experiences of and Opinions on CS Ethics

Grace Barkhuff (Georgia Institute of Technology), Ian Pruitt (Georgia State University)

CS ethics coursework is required at many institutions for undergraduate CS majors. However, little is known about how students perceive the addition of this topic into the CS curriculum which is otherwise largely technical in nature. To understand perceptions of CS ethics as a course, we included questions about CS ethics instruction on a survey of 88 graduate and undergraduate teaching assistants (TAs) at two institutions in the United States.

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Uncovering Opportunities for K-12 CS Professional Development in West African Schools.

Jane Awuah (Georgia Institute of Technology), Judith Uchidiuno (Georgia Institute of Technology)

Computer science education in Africa is gaining momentum as computer science skills give employees a competitive advantage in an increasingly globalized labor market. Researchers and educators have addressed this demand by making CS instructional materials more accessible, creating professional development (PD) resources, and designing online courses targeted at undergraduate CS education settings. However, there is limited research on what types of support African teachers need to improve pedagogy in K-12 settings, which is critical for fostering foundational interest in CS. To address this, we interviewed fourteen CS teachers in nine K-12 schools in the Greater Accra Region of Ghana to uncover opportunities to design interventions that address challenges they experience with teaching CS in schools and support their professional development.

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Understanding the Effects of Integrating Music Programming and Web Development in a Summer Camp for High School Students

Daniel Manesh (Virginia Tech), Andrew Jelson (Virginia Tech), Emily Altland (Virginia Tech), Jason Freeman (Georgia Tech), Sang Won Lee (Virginia Tech)

This poster presents the development and implementation of a 10-day remix-based summer camp curriculum designed to introduce high school students, particularly young women from developing countries, to programming through creative coding. The curriculum integrates music composition using EarSketch and web development with HTML and CSS. The camp aims to inspire participants to gain self-efficacy in programming and motivate them to explore STEM/computing careers.