After initial acquisition, problem-solving leads to better long-term performance than example study, even for complex tasks

Background

Successful implementation of effective acquisition strategies (e.g., example study, problem-solving) could help improve mathematics performance. However, it is not yet fully understood when each acquisition strategy should be used, despite the practical value of this knowledge for mathematics textbook authors, teachers, and students.

Aims

Building upon two recent perspectives on when example study and problem-solving are beneficial, we proposed that the optimal acquisition strategy could depend on both task complexity and retention interval (i.e., time between the final practice opportunity and the test). We conducted a multi-classroom experiment to test this proposition.

Sample

166 typically-developing Dutch fifth-grade students participated (M_age = 11.14 years; 42.2% boys).

Methods

We used a 2 (Task Complexity: simple vs. complex) x 2 (Acquisition Strategy: example study vs. problem-solving) x 2 (Retention Interval: 5 min vs. 1 week) between-subjects design with problem-solving performance as dependent variable.

Results

There was no evidence for the hypothesised three-way interaction effect of task complexity, acquisition strategy, and retention interval. However, there was evidence for the hypothesised two-way interaction effect of acquisition strategy and retention interval, independent of task complexity. More specifically, after 5 min, there was no statistically significant performance difference between students studying worked examples and those solving practice problems, but after 1 week, students solving practice problems outperformed those studying worked examples.

Conclusions

Our findings imply that, after initial acquisition, problem-solving leads to better long-term problem-solving performance than example study. This holds true even for a relatively complex task and with limited instruction.