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CS 315-02 Lecture/Lab Meeting Summary — Fall 2025

Date: Dec 02, 2025
Time: 02:50 PM Pacific (US and Canada)
Meeting ID: 868 6589 0521

Quick Recap

  • The meeting opened with a discussion of VPN access requirements for Beagle machines and a brief survey of student experiences with remote usage.
  • The group examined differing approaches to AI tools in computer science education, comparing restrictive versus permissive policies for academic use.
  • The session concluded with an overview of the final exam format and content, emphasizing conceptual understanding over memorization.

Next Steps

  • Greg:
  • Post solutions for the final exam practice problems.
  • Assist students with Project 7 during tomorrow’s lab section.
  • Rerun and regrade all projects by Friday, allowing up to 50% late credit for resubmissions.
  • Publish a solution for Question 4 (digital design problem) as noted during the review.
  • Schedule and conduct follow-up meetings as needed for students requiring additional time or help with labs/projects (noted for Thursday, potentially others as needed).
  • Students needing help with Project 7: Attend tomorrow’s lab section for assistance.
  • Unnamed student: Meet with Greg at 3:45 to discuss and complete lab work.

Discussion Highlights

VPN Access for Beagle Machines

  • A class poll indicated that most students needed to set up VPN access to use Beagle machines remotely.
  • The group discussed best practices for accessing remote resources securely and reliably.

AI in Computer Science Education: Policy Approaches

  • The conversation contrasted two main approaches:
  • Restrictive: Ban AI tools entirely for assignments and assessments.
  • Permissive with guidelines: Allow AI use under explicit rules and transparency.
  • Bray reported that exam-focused restrictions effectively reduced AI use on assignments.
  • Greg argued that AI can be a valuable learning aid when used appropriately and transparently.

Practical Use of AI Tools (e.g., ChatGPT, Gemini)

  • Greg shared observations from using AI for debugging and study:
  • Strengths: Quick answers, rapid prototyping, and assistance identifying likely issues.
  • Limitations: Weak at teaching concepts deeply; may miss underlying problems or mislead with plausible but incorrect explanations.
  • The group noted potential distractions and overreliance risks.
  • Emphasis was placed on:
  • Code reviews and interactive grading to promote deeper understanding.
  • Personal engagement with course material rather than outsourcing thinking to AI.
  • Greg briefly addressed the “enrollment cliff,” referring to anticipated declines in college enrollment due to demographic shifts.
  • The discussion touched on the complexity of modern processors and the prevalence of security flaws, providing context for why conceptual understanding remains crucial in CS.

Final Exam Review

  • Format and content were discussed, including the types of questions students should expect.
  • Students were encouraged to prioritize:
  • Understanding concepts and reasoning processes.
  • Applying principles rather than memorizing isolated facts.