pith. sign in

arxiv: 2604.16365 · v1 · submitted 2026-03-21 · 💻 cs.CY

"CS 1.5": An Experience Report on Integrating CS1 and Discrete Structures for the AI Era

Ildar Akhmetov , Juancho Buchanan This is my paper

Pith reviewed 2026-05-15 06:28 UTC · model grok-4.3

classification 💻 cs.CY
keywords computer science educationAI collaboration in teachingdiscrete structures integrationCS1 studio coursecode comprehensiongenerative AI in education
0
0 comments X

The pith

Merging CS1 and discrete structures into one studio course treats AI as a collaborator while building theoretical depth through code comprehension.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper presents an experience report on combining introductory computer science and discrete structures into a single course called CS 1.5. It claims this 4-hour studio format responds to generative AI by shifting emphasis from writing code to understanding it, while linking mathematical proofs directly to implementation projects. Sharing circles are introduced to preserve human connection amid tool-assisted work. The report details the timetable changes, project designs spanning set theory and recursion, and the instructor's shift toward mentorship rather than lecturing.

Core claim

Restructuring CS1 and Discrete Structures into a single cohesive studio experience that embraces AI as a collaborator and prioritizes code comprehension alongside theoretical projects supports deeper foundations and human connection in the AI era.

What carries the argument

The CS 1.5 studio model, defined by 4-hour sessions, sharing circles for connection, and integrated projects that connect proofs in set theory, recursion, and probability to software implementation.

If this is right

  • Students can use AI tools without losing focus on theoretical understanding.
  • Sharing circles maintain human interaction in the classroom.
  • Instructors move from knowledge repositories to human mentors.
  • Integrated projects bridge mathematical proofs and practical code work across topics like set theory and probability.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Other computing programs facing AI disruption could test similar timetable and project integrations.
  • Adding outcome measurements such as pre/post assessments would clarify the model's advantages.
  • The approach may suggest rethinking early CS curricula to reduce separate math requirements.

Load-bearing premise

The specific interventions of 4-hour studios, sharing circles, code-comprehension focus, and integrated projects produce better learning outcomes than traditional separate courses.

What would settle it

A direct comparison of student performance metrics such as conceptual test scores or project quality between the integrated CS 1.5 course and separate traditional CS1 and Discrete Structures sections would settle whether the model improves outcomes.

Figures

Figures reproduced from arXiv: 2604.16365 by Ildar Akhmetov, Juancho Buchanan.

Figure 2
Figure 2. Figure 2: Recursive Flood Fill: A strategy game where move [PITH_FULL_IMAGE:figures/full_fig_p004_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: D&D Combat Simulator: Flet app for empirically [PITH_FULL_IMAGE:figures/full_fig_p005_3.png] view at source ↗
read the original abstract

The rapid proliferation of generative AI has fundamentally altered the landscape of introductory computer science education. Traditional methods that prioritize syntax memorization and writing code from scratch are challenged by tools that can generate such code instantly. In response, we designed and implemented an experimental course integration at Northeastern University Vancouver, merging "Intensive Foundations of Computer Science" (CS1) and "Discrete Structures" into a single, cohesive studio experience. Dubbed "CS 1.5"--a playful nod to its position between CS1 and CS2--this course operates on two core principles: embracing AI as a collaborator rather than an adversary, and prioritizing deep theoretical foundations alongside practical implementation. This report details our pedagogical interventions, including the restructuring of the timetable to support a 4-hour studio format, the introduction of "sharing circles" to foster human connection, and the strategic shift to "code comprehension" over code generation. We discuss specific integrated projects--spanning set theory, recursion, and probability--that bridge the gap between mathematical proofs and software implementation. Finally, we reflect on the changing role of the instructor--from a repository of knowledge to a human mentor--and offer practical recommendations for scaling this high-touch, integrated model.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper describes the design and implementation of an experimental 'CS 1.5' course at Northeastern University Vancouver that integrates CS1 and Discrete Structures into a single 4-hour studio format. It emphasizes embracing generative AI as a collaborator, shifting focus to code comprehension rather than generation from scratch, introducing 'sharing circles' for human connection, and using integrated projects on set theory, recursion, and probability to bridge theory and implementation. The report reflects on the instructor's evolving role as a mentor and offers recommendations for scaling the model in the AI era.

Significance. If the described interventions prove effective, the report could provide a practical template for adapting introductory CS curricula to generative AI tools by prioritizing theoretical depth and interpersonal elements. However, the complete absence of any evaluation data means the significance remains potential rather than demonstrated; the contribution is limited to a detailed narrative of one institution's experience.

major comments (2)
  1. [Abstract and Reflections] Abstract and the section describing outcomes: The central claim that the 4-hour studio format, sharing circles, code-comprehension emphasis, and integrated projects 'support deeper foundations and human connection' is presented without any supporting evidence such as pre/post concept inventories, student performance metrics, survey results, grade comparisons, or retention data against the prior separate CS1 + Discrete Structures sequence. This absence is load-bearing because the paper's rationale for the interventions rests entirely on these asserted benefits.
  2. [Integrated Projects] Section on integrated projects (set theory, recursion, probability): While specific project examples are described, there is no discussion of how student learning was assessed (e.g., via proof quality rubrics, code comprehension quizzes, or project completion rates), making it impossible to evaluate whether the integration actually achieved the claimed bridging of mathematical proofs and software implementation.
minor comments (2)
  1. [Course Design] The manuscript would benefit from a dedicated subsection on implementation timeline and enrollment numbers to allow readers to contextualize the scale of the experiment.
  2. [Introduction] Clarify in the introduction whether 'CS 1.5' is intended as a replacement for both courses or as an optional integrated track, as this affects how the model could be adopted elsewhere.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the constructive feedback on our experience report. We agree that the manuscript would benefit from more explicit framing of its observational nature and clearer acknowledgment of the absence of formal evaluation data. We address each major comment below, indicating the revisions we will make.

read point-by-point responses

  1. Referee: [Abstract and Reflections] Abstract and the section describing outcomes: The central claim that the 4-hour studio format, sharing circles, code-comprehension emphasis, and integrated projects 'support deeper foundations and human connection' is presented without any supporting evidence such as pre/post concept inventories, student performance metrics, survey results, grade comparisons, or retention data against the prior separate CS1 + Discrete Structures sequence. This absence is load-bearing because the paper's rationale for the interventions rests entirely on these asserted benefits.

    Authors: We acknowledge this limitation. As an experience report based on a single offering of the course, the described benefits reflect the instructor's observations and informal student feedback rather than controlled measurements. In revision we will qualify the abstract and outcomes section to state explicitly that claims are qualitative and observational, add a limitations paragraph noting the lack of pre/post inventories or comparative metrics, and adjust language to avoid implying demonstrated efficacy. revision: partial

  2. Referee: [Integrated Projects] Section on integrated projects (set theory, recursion, probability): While specific project examples are described, there is no discussion of how student learning was assessed (e.g., via proof quality rubrics, code comprehension quizzes, or project completion rates), making it impossible to evaluate whether the integration actually achieved the claimed bridging of mathematical proofs and software implementation.

    Authors: We agree that the section would be strengthened by describing how learning was gauged. We will expand the integrated projects section to detail the informal methods employed, including in-class code-comprehension discussions, project walkthroughs, and instructor review of student artifacts for evidence of conceptual integration. We will also add an explicit statement that no formal rubrics, quizzes, or quantitative completion rates were collected, framing this as a limitation of the current experience report. revision: partial

Circularity Check

0 steps flagged

No circularity: purely descriptive experience report with no derivations or predictions

full rationale

The paper is an experience report describing course restructuring, timetable changes, sharing circles, code-comprehension emphasis, and integrated projects. It contains no equations, no fitted parameters, no predictions of outcomes, and no load-bearing self-citations that reduce claims to prior author work. All statements are narrative accounts of implemented practices and instructor reflections rather than derived results, so the derivation chain is empty and no circularity exists.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

As a descriptive experience report on educational practice, the paper introduces no free parameters, mathematical axioms, or invented entities; all content is narrative description of observed classroom changes.

pith-pipeline@v0.9.0 · 5520 in / 1155 out tokens · 34138 ms · 2026-05-15T06:28:16.990951+00:00 · methodology

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.

Reference graph

Works this paper leans on

14 extracted references · 14 canonical work pages

  1. [1]

    Brett A Becker, Paul Denny, James Finnie-Ansley, Andrew Luxton-Reilly, James Prather, and Eddie Antonio Santos. 2023. Programming Is Hard-Or at Least It Used to Be: Educational Opportunities and Challenges of AI Code Generation. In Proceedings of the 54th ACM Technical Symposium on Computer Science Education V. 1. 500–506

    work page 2023

  2. [2]

    2009.Computer Science Unplugged: School Students Doing Real Computing Without Computers

    Tim Bell, Jason Alexander, Isaac Freeman, and Mick Grimley. 2009.Computer Science Unplugged: School Students Doing Real Computing Without Computers. Vol. 13. 20–29 pages

    work page 2009

  3. [3]

    Paul Denny, Juho Leinonen, James Prather, Andrew Luxton-Reilly, Thezyrie Amarouche, Brett A Becker, and Brent N Reeves. 2024. Prompt Problems: A new programming exercise for the generative AI era. InProceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1. 296–302

    work page 2024

  4. [4]

    Fernandez and Kimberly A

    Amanda S. Fernandez and Kimberly A. Cornell. 2024. CS1 with a Side of AI: Teaching Software Verification for Secure Code in the Era of Generative AI. In Proceedings of the 55th ACM Technical Symposium on Computer Science Education V. 1(Portland, OR, USA)(SIGCSE 2024). Association for Computing Machinery, New York, NY, USA, 345–351. doi:10.1145/3626252.3630817

    work page doi:10.1145/3626252.3630817 2024

  5. [5]

    Christopher D Hundhausen, Anukrati Agrawal, and Pawan Agarwal. 2013. Talk- ing about code: Integrating pedagogical code reviews into early computing courses.ACM Transactions on Computing Education (TOCE)13, 3 (2013), 1–28

    work page 2013

  6. [6]

    Ludek Kucera, Ildar Akhmetov, Cruz Izu, and Olufisayo Omojokun. 2025. Adapt- ing Computing Curricula in the Era of Automated Software Development. In Proceedings of the ACM Global on Computing Education Conference 2025 Vol 2 (Gaborone, Botswana)(CompEd 2025). Association for Computing Machinery, New York, NY, USA, 353–355. doi:10.1145/3736251.3754332

    work page doi:10.1145/3736251.3754332 2025

  7. [7]

    Rongxin Liu, Carter Zenke, Charlie Liu, Andrew Holmes, Patrick Thornton, and David J Malan. 2024. Teaching CS50 with AI: leveraging generative artificial intelligence in computer science education. InProceedings of the 55th ACM technical symposium on computer science education V. 1. 750–756

    work page 2024

  8. [8]

    C Marco-Detchart and C Lopez-Molina. 2025. Redefining programming assess- ments in the era of artificial intelligence and large language models. InINTED2025 Proceedings. IATED, 5610–5615

    work page 2025

  9. [9]

    James Prather, Juho Leinonen, Natalie Kiesler, Jamie Gorson Benario, Sam Lau, Stephen MacNeil, Narges Norouzi, Simone Opel, Vee Pettit, Leo Porter, et al. 2025. Beyond the hype: A comprehensive review of current trends in generative AI research, teaching practices, and tools.2024 Working Group Reports on Innovation and Technology in Computer Science Educa...

    work page 2025

  10. [10]

    It’s Weird That It Knows What I Want

    James Prather, Brent N. Reeves, Paul Denny, Brett A. Becker, Juho Leinonen, Andrew Luxton-Reilly, Garrett B. Powell, James Finnie-Ansley, and Eddie Antonio Santos. 2023. "It’s Weird That it Knows What I Want": Usability and Interactions with Copilot for Novice Programmers.ACM Transactions on Computer-Human Interaction31 (2023), 1–31. doi:10.1145/3617367

    work page doi:10.1145/3617367 2023

  11. [11]

    2017.Lifelong Kindergarten: Cultivating Creativity through Projects, Passion, Peers, and Play

    Mitchel Resnick. 2017.Lifelong Kindergarten: Cultivating Creativity through Projects, Passion, Peers, and Play. MIT Press

    work page 2017

  12. [12]

    Schmidt, Caitlin J

    Logan W. Schmidt, Caitlin J. Kidder, Ildar Akhmetov, Megan Bebis, Alan C. Jamieson, Albert Lionelle, Sarah Maravetz, Sami Rollins, and Ethan Selinger. 2025. An MS in CS for non-CS Majors: A Ten Year Retrospective. InProceedings of the 56th ACM Technical Symposium on Computer Science Education V. 1(Pittsburgh, PA, USA)(SIGCSETS 2025). Association for Compu...

    work page doi:10.1145/3641554.3701928 2025

  13. [13]

    Xiaojing Weng, XIA Qi, Mingyue Gu, Kumaran Rajaram, and Thomas KF Chiu

    work page

  14. [14]

    9https://github.com/cs1-5

    Assessment and learning outcomes for generative AI in higher education: A scoping review on current research status and trends.Australasian Journal of Educational Technology(2024). 9https://github.com/cs1-5

    work page 2024