ACM COMPUTE 2025 Best Practices Track Proceedings
These proceedings collect selected experience reports and editorial summaries from the Best Practices Track of COMPUTE 2025, an Indian conference focused on sharing innovative pedagogical strategies and teaching methods in computer science education.
Original paper licensed under CC BY 4.0 (http://creativecommons.org/licenses/by/4.0/). This is an AI-generated explanation of the paper below. It is not written or endorsed by the authors. For technical accuracy, refer to the original paper. Read full disclaimer
Imagine you are part of a massive, nationwide kitchen crew, and everyone is trying to learn how to cook the perfect meal. For a long time, the "chefs" (the teachers) have been standing at the front of the room reading recipes out loud while the "students" (the learners) just sit there, trying to memorize the ingredients.
The COMPUTE 2025 Best Practices paper is essentially a "Master Chef Meeting" report. It’s a summary of a gathering of computer science teachers in India who met to figure out how to stop just reading recipes and start actually cooking great software.
Here is the breakdown of their "recipe for success" using three main themes:
1. From "Reading the Cookbook" to "Getting Hands-on" (Classroom Activities)
In the past, computer science classes were often like watching a cooking show on TV—you see someone else do it, but you don't touch the stove. The experts at this conference said: "Enough watching! Let’s start cooking!"
- The Analogy: Instead of a 60-minute lecture on how to chop an onion, they want students to spend 48 minutes actually chopping onions and only 12 minutes listening to the theory.
- The Method: They suggested "Pair Programming" (like two chefs sharing one workstation to catch each other's mistakes) and "Debugging Activities" (giving students a "spoiled" dish and asking them to figure out why it tastes bad).
2. The "AI Chef" Problem (AI-Resistant Assignments)
This is the biggest challenge today. Imagine a student who doesn't actually know how to cook, but they have a "Magic Robot" (like ChatGPT) that can instantly whip up a perfect soufflé. If the student just hands in the soufflé, did they actually learn anything? Probably not.
The teachers discussed how to make homework "AI-proof."
- The Analogy: If you ask a student to "make a sandwich," the robot can do it instantly. But if you ask them to "make a sandwich using only the weird ingredients found in your own fridge, and then explain why you chose that specific mustard," the robot struggles.
- The Method: Instead of just grading the final "dish" (the code), teachers want to grade the process. They want to see the student's "cooking logs"—how they talked to the AI, how they corrected the AI's mistakes, and how they defended their choices in a live conversation (a "viva voce").
3. Building the "Global Kitchen Network" (The Community)
Finally, the paper argues that teachers shouldn't be "lone wolves" working in isolated kitchens. If one chef discovers a brilliant new way to teach algebra, that secret shouldn't stay in one kitchen; it should be shared with the whole country.
- The Analogy: They want to build a "Grand Culinary Guild." Instead of every teacher struggling alone to figure out a new curriculum, they want to create regional clubs, online forums, and workshops where they can swap "secret recipes" (teaching tools) and help each other grow.
- The Method: By creating "Regional Champions" and shared digital libraries, they hope to turn a collection of individual teachers into a powerful, united movement to improve education across India.
The Bottom Line
This paper is a blueprint for a revolution in learning. It moves away from "memorizing the menu" and toward "mastering the kitchen," ensuring that when students graduate, they aren't just good at following instructions—they are true creators who can think, adapt, and solve problems in a world full of AI.
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