Allen School Colloquium: Aligning Computing Education with Modern Software Development

Why It Matters

Aligning curricula with industry development processes directly boosts graduate employability and lowers companies’ onboarding expenses, addressing both educational equity and business efficiency.

Key Takeaways

• Live coding shows no improvement in learning outcomes.
• Students struggle with note‑taking during traditional live coding sessions.
• Active live coding boosts engagement but not programming process mastery.
• Incremental development metrics reveal no link to assignment scores.
• Bridging academia‑industry gap requires teaching process‑oriented skills for students.

Summary

Anchel Shaw, a computing‑education researcher at UC San Diego, presented a colloquium on aligning university programming instruction with the realities of modern software development. He highlighted the persistent academia‑industry gap, where students learn green‑field coding and are graded solely on final code correctness, while industry demands incremental, collaborative, and maintainable development practices.

Shaw examined the standard assignment cycle—large classes, autograders, and final‑code assessment—and argued that it overlooks students’ programming processes such as debugging, testing, and code comprehension. Citing a 2020 study showing only 57 % of graduates completed internships, he stressed that limited process training hampers career readiness and exacerbates socioeconomic inequities.

His empirical work compared traditional live coding with static‑code demonstrations across three term‑long courses. Using a novel incremental‑development metric and the Barry protocol for behavioral engagement, he found no statistically significant differences in learning outcomes, process adherence, or exam performance, and students reported poorer note‑taking during live coding. A follow‑up “active live coding” variant raised engagement by roughly 25 % but still did not improve grades or process metrics.

The findings suggest that popular pedagogical practices like live coding may be ineffective for teaching industry‑relevant skills, and that educators should prioritize process‑oriented feedback, active learning structures, and tools that capture students’ development workflow. Closing the gap could enhance graduate employability and reduce costly onboarding for tech firms.

Original Description

Title: Bridging the Gap: Aligning Computing Education with Modern Software Development

Speaker: Anshul Shah (UC San Diego)

Date: Tuesday, March 10, 2026

Abstract: The academia-industry gap in software engineering describes the misalignment between the skills students learn in universities and the expectations placed upon early-career software developers. This gap is already present: while software developers work on large, existing code bases, university coursework typically requires students to create projects from scratch. Unfortunately, this gap is growing: as developers increasingly rely on GenAI tools, CS programs must consider how to prepare students to use these tools while still promoting student learning.

Computing education research tends to study the final code artifacts that students produce (i.e., assignment submissions). In contrast, my work aims to understand the processes that students use to create those final code artifacts. In this talk, I’ll share my work to understand and improve three programming processes: 1) incremental development, 2) program comprehension in large code bases, and 3) student-AI collaboration for programming. I’ll highlight the novel teaching techniques, curricula, and instructional materials that my research has contributed to across the undergraduate curriculum, from introductory programming to advanced software engineering courses. Finally, I’ll discuss key challenges facing computing education in the age of GenAI and how my work to emphasize “process over product” will help computing educators adapt to meet the moment.

Bio: Anshul Shah is a PhD candidate at UC San Diego advised by Gerald Soosairaj, Leo Porter, and Bill Griswold. His research aims to improve undergraduate computer science curricula to prepare students for modern software development. His work has been published in top computing education venues, such as ICER and TOCE, and has been featured on the GenAI in CS Education Consortium website. He has been selected for two international working groups that have focused on developing instructional materials related to code quality and AI literacy. He's been recognized for both his teaching and research, earning the Doctoral Award for Teaching Excellence from UCSD CSE in 2025 and the Best Paper Award at ICER 2025--a premier computing education venue.

This video is in the process of being closed captioned.