Strategies for Targeting the Learning of Complex Skills Like Experimentation to Different Student Levels: The Intermediate Constraint Hypothesis

Abstract

Providing active learning experiences is particularly challenging when students are learning higher-order skills such the experimental process, where it is critical to provide opportunities to learn by doing, but hard to tune activities to each student’s current skill level or provide the necessary feedback. While virtual learning environments can help, the definition of inquiry in such environments covers a wide range. In building educational activities, particularly on the computer, designers implicitly or explicitly manipulate three axes: scaffolding, feedback, and constraint. In this chapter, I show how thinking deliberately about these axes can improve student learning. I argue that of those three, constraint has been underappreciated. I base this argument on data from several studies involving thousands of students at hundreds of high schools and colleges. The research shows examples of explicitly manipulating constraint in both questions and simulation-based activities, and suggests that choosing the right level of constraint can increase student learning and instructor’s ability to assess student understanding of complex skills. From these data along with theoretical considerations I suggest an Intermediate Constraint Hypothesis stating that focusing on level of constraint in student exercises and assessments is a practical and powerful way to maximize student learning.

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