Worked examples and tutored problem solving: redundant or synergistic forms of support?

Area of Science:

• Educational Technology
• Cognitive Science
• Instructional Design

Background:

• Tutored problem solving using automated tutors is an effective instructional method.
• Worked-out examples complement untutored problem solving but their efficacy with tutored problem solving is understudied.
• The effectiveness of adaptive example fading in computer-based learning environments remains largely uninvestigated.

Purpose of the Study:

• To investigate the effectiveness of combining tutored problem solving with worked examples.
• To examine the impact of adaptive versus fixed fading of worked-out examples in automated tutors.
• To compare adaptive example fading with standard automated tutoring.

Main Methods:

• Conducted one lab and one classroom experiment.
• Compared a standard Cognitive Tutor against two enhanced Cognitive Tutors.
• Implemented fixed and adaptive fading of worked-out examples in the enhanced tutors.

Main Results:

• Adaptive fading of worked-out examples resulted in higher transfer performance on delayed posttests.
• Learners in the adaptive fading condition outperformed those in fixed fading and standard tutoring conditions.
• The study provides empirical evidence on the benefits of adaptive example fading.

Conclusions:

• Adaptive fading of worked-out examples is a superior instructional strategy for enhancing learning transfer in tutored problem-solving environments.
• Computer-based learning environments can effectively leverage machine-adapted example fading for personalized instruction.
• Future research should explore the mechanisms behind adaptive fading's effectiveness and its applicability across different domains.