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Classes & Objects (constructors, methods, fields)
Arrays, ArrayLists, and iteration patterns
Encapsulation, access modifiers, and design basics
Inheritance & polymorphism (the parts York tests hard)
Exceptions, debugging, and test-driven fixes
Assignment structure, UML-lite thinking, and code reviews
An EECS 1022 assignment is usually one class, a few methods, maybe an ArrayList. AI writes that in seconds, constructors and getters included, and it looks exactly like the lecture examples. You submit working Java without ever building a mental model of what an object is or what a reference points at.
York asks you to trace inheritance by hand, predict what polymorphic code prints, and write a class from a plain English description with nothing open. The same gap comes back in EECS 2030, where these concepts return heavier and faster.
The goal is not to stop using AI. It is to use it in a way that leaves you more capable than it found you: hints instead of finished classes, explaining your own code back, predicting output before you run it. Same tool, very different result by the end of term.
Yes, and most students in this course have done the same thing. Small assignments plus a tool that finishes them instantly is a normal way to end up here, and it is fixable. We separate what you genuinely understand from what AI has been carrying, rebuild the Java OOP underneath it, and get you to where you can write and explain a class on your own.
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