A professor challenged the relevance of behaviorism in teaching, questioning its value when AI can replicate desired behaviors. The article defends behaviorism by clarifying its focus on the conditions affecting learning and the evolution of student behavior rather than mere output. While AI, such as ChatGPT, can generate content and simulate behavior, it lacks human engagement and the reflective learning process that accompanies it. The main emphasis is on whether the student's behavior improves, making the educational experience meaningful and focused on skill development rather than just output.
While machines can simulate behavior and even adapt based on feedback, they are not users of technology; humans are.
The key question is: Did the student's own behavior change? Did they act more skillfully, make more informed decisions, or respond more effectively than before?
In education, our focus is not whether AI systems evolve or improve, but whether students learn.
Behaviorism doesn't diminish the value of the outputs we expect from students, it asks us to ensure those outputs reflect learning.
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