Modeling the influence of format and depth during effortful retrieval practice
This research combines work in memory, retrieval practice, and depth of processing research. This work aims to identify how the format and depth of a retrieval practice item can be manipulated to increase the effort required to successfully recall or formulate an answer, with the hypothesis that if the effort required to answer an item is increased there will be more benefit to learning. This hypothesis stems from work on desirable difficulties and the effortful retrieval hypothesis. Our data source was an experiment that used a 2 (question depth: factual, applied) x 2 (answer format: multiple choice, short answer) between-subjects design to investigate the effects of these conditions on retrieval practice performance. The experiment was delivered online though Mechanical Turk (n = 178). A logistic regression predicting performance during practice indicates that participants get more (in terms of an increase in future predicted success) from successful retrievals of items that fall within the more difficult level of both the format and depth factors (i.e., short answer and applied). There is also some support that the benefit from multiple choice items may be increased by asking deeper, more applied questions. The application of these results to scheduling effective practice is discussed.
Proceedings of the 9th International Conference on Educational Data Mining, EDM 2016
Maass, J., & Pavlik, P. (2016). Modeling the influence of format and depth during effortful retrieval practice. Proceedings of the 9th International Conference on Educational Data Mining, EDM 2016, 143-150. Retrieved from https://digitalcommons.memphis.edu/facpubs/8226