Evaluating a range of learning schedules: hybrid training schedules may be as good as or better than distributed...

We investigated theoretically and empirically a range of training schedules on tasks with three knowledge types: declarative, procedural, and perceptual-motor. We predicted performance for 6435 potential eight-block training schedules with ACT-R's declarative memory equations. Hybrid training schedules (schedules consisting of distributed and massed practice) were predicted to produce better performance than purely distributed or massed training schedules. The results of an empirical study (N = 40) testing four exemplar schedules indicated a more complex picture. There were no statistical differences among the groups in the declarative and procedural tasks. We also found that participants in the hybrid practice groups produced reliably better performance than ones in the distributed practice group for the perceptual-motor task--the results indicate training schedules with some spacing and some intensiveness may lead to better performance, particularly for perceptual-motor tasks, and that tasks with mixed types of knowledge might be better taught with a hybrid schedule.

We explored distributed and massed training schedules as well as hybrids between them with respect to three knowledge types based on theories and an empirical study. The results suggest that industrial and operator training in complex tasks need not and probably should not be done on a distributed training schedule.