ENHANCING STATISTICS LEARNING TRANSFER WITHIN A PRACTICE TESTING LEARNING FRAMEWORK
Practice testing is promoted widely as an effective learning technique however boundary conditions may exist depending on knowledge domain and where the transfer of learning is required. This paper investigates e-assessment practice testing within a Practice Testing Learning Framework (PTLF) in an introductory statistics module. The test development approach employs Hess’s Cognitive Rigor (CR) matrix to map learning outcomes to support item development and classification. Test items are designed to reflect the cognitive process dimension with required depth of knowledge. In Experiment 1, the results suggest significantly enhanced performance with practice testing where practice test items are identical to the criterion test. The results from Experiments 2 and 3 show enhanced performance in topically related items requiring a transfer of learning in the statistics domain. Mean performance in criterion test topics increased depending on the number of times students completed the relevant topic practice tests for both identical and topically related items. These findings suggest that practice testing in introductory statistics enhances performance in criterion tests particularly when students complete more than one attempt and when those attempts are distributed over time. Future work will consider testing these finding within a more controlled environment and include evaluation of practice testing schedules across other learning domains in classroom contexts.