Combining Worked Examples and Problem Solving in a Data-Driven Logic Tutor
Zhongxiu Liu, Behrooz Mostafavi, Tiffany Barnes
Previous research has shown that worked examples can increase learning efficiency during computer-aided instruction, especially when alternatively offered with problem solving opportunities. In this study, we investigate whether these results are consistent in a complex, open-ended problem solving domain, where students are presented with randomly ordered sets of worked examples and required problem solving. Our results show that worked examples benefits students early in tutoring sessions, but are comparable to hint-based systems for scaffolding domain concepts. Later in tutoring sessions, worked examples are less beneficial, and can decrease performance for lower-proficiency students.
The final publication is available at Springer via https://doi.org/10.1007/978-3-319-39583-8_40.