Improving Example-Based Learning

Anybody who spent time in a generic classroom is familiar with the simple three step process of example-based learning.

1. Teacher instructs students about principles and concepts in a certain domain.
2. Students see worked-examples that demonstrate the principles and concepts.
3. Students attempt problems on their own.

Understanding exactly how students learn from worked-examples is important because worked-examples are a key component of the technology-based cognitive tutors and personalized lessons that could one day be the backbone of our education system. Computers will never be able to mimic everything a teacher can do, but they can come close to mimicking instruction through worked-examples.

For this reason it was nice to see a meta-analysis in a recent Review of Education Psychology that examined how instructional explanations — explanations that clarify problem states or explicate principles — affect the learning outcomes of worked-example lessons. Although the authors found the overall effect of instructional explanations to be small, they did make a few discoveries that point to hidden significance.

First, instructional explanations had greater effects on mathematics knowledge and conceptual knowledge, two types of knowledge that are generally considered to be more difficult to obtain and more important than counterparts such as history or procedural knowledge. The authors also found that providing instructional explanations was helpful only when students were not encouraged to engage in self-explaining.

What’s important here is that nothing about the findings suggests a significant benefit to human instruction.  Although some kind of reflection about the problem solving process is clearly helpful,  it need not be a complex instructional explanation that requires a human teacher. Simply giving the students a prompt that asks them to think about what they’re doing and why they’re doing it may be enough to reap the potential learning gains.

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