The article argues that authentic student learning should be defined by observable behaviors and measurable outcomes rather than vague ideals like intrinsic motivation. By integrating the educational theories of Bloom, which emphasizes cognitive skills, and Skinner, which focuses on behavior change through reinforcements, a clearer path to understanding learning emerges. The article highlights the potential of artificial intelligence to provide real-time feedback and insights, empowering educators to target specific skills effectively, ultimately enhancing student mastery through engaging, real-world tasks.
Observable student behaviors, not vague ideals, define learning as skill acquisition and mastery. By combining Blooms and Skinner, we create a measurable system of learning.
Students actively demonstrate mastery through real-world tasks, guided by AI that provides instant feedback, ensuring precise reinforcement of skills and deepening their learning experience.
Real-time AI insights empower educators by placing a focus on specific skills and enabling them to reinforce learning effectively, transforming the educational environment.
Authentic learning must be showcased through measurable, observable outcomes rather than remaining confined to internal processes or motivational theories.
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