Transfer of learning between related and less related tasks using content specific and content general learning strategies

Abstract

This study compared learning strategies in an effort to determine which strategy would be most beneficial to transfer of learning. A number of approaches were suggested in the related literature for maximizing learning, one of which was to use "learning how to learn," also known by the term content general learning strategy. This study hypothesized that the use of content general learning strategies would produce more transfer of learning across both related and less related tasks than content specific learning strategies. Both learning strategies were combined with either a visual and semantic method of encoding or a semantic only method of encoding. A factorial analysis of covariance (ANCOVA) which combines regression analysis with analysis of variance tested the null hypothesis that the adjusted population means were equal for the covariate of the pretest and the dependent variable of the posttest. Analysis procedures of the ANCOVA on data results reflect that for related and less related tasks, content general with visual and semantic encoding outperformed all other methods tested. The results indicate that a general learning strategy (learning how to learn) is more productive for learning achievement in situations where transfer of learning is desired.