Toward Measuring and Maintaining the Zone of Proximal Development in Adaptive Instructional Systems

Intelligent tutoring Systems (ITSs) adapt content and activities with the goals of being both effective and efficient instructional environments. They have goals for students to be challenged and guided in an optimal way--without being too overwhelmed with difficult material or too bored with easy or repetitive material. We propose a particular definition of the zone of proximal development (ZPD) as a general way to describe what all ITSs try to do, and we propose a foundational analysis of instructional adaptivity, student modeling, and system evaluation in terms of the ZPD. We give an operational definition of the ZPD and give an example of its use, and summarize how instructional methods such as scaffolding can be used to maintain ZPD-learning. We also explain how our definition of the ZPD can lead to a more complete model for efficient and effective instruction than common mastery learning criteria.