Alan Turing, in his 1950 paper “Computing Machinery and Intelligence,” proposed a test for artificial intelligence while working at the University of Manchester. The Turing Test, originally dubbed the "imitation game," challenges a machine's ability to engage in a conversation indistinguishable from a human's. If a human evaluator cannot reliably differentiate between the machine and a human, the machine is said to have passed. This test, in essence, is a litmus test for the presence of true intelligence—a test of imitation versus genuine understanding. Turing's test provides a framework for evaluating AI's role in learning. Just as the test measures a machine's ability to mimic human conversation, AI's effectiveness in learning depends on its capacity to genuinely enhance rather than merely replicate the process. The goal is not to replace human intelligence but to augment it, creating a synergistic partnership that optimizes learning outcomes.