Which Technique is most Effective for Learning Declarative Concepts—Provided Examples, Generated Examples, or Both?


Journal Article

© 2016, Springer Science+Business Media New York. Students in many courses are commonly expected to learn declarative concepts, which are abstract concepts denoted by key terms with short definitions that can be applied to a variety of scenarios as reported by Rawson et al. (Educational Psychology Review 27:483–504, 2015). Given that declarative concepts are common and foundational in many courses, an important question arises: What are the most effective techniques for learning declarative concepts? The current research competitively evaluated the effectiveness of various example-based learning techniques for learning declarative concepts, with respect to both long-term learning and efficiency during study. In experiment 1, students at a large, Midwestern university were asked to learn 10 declarative concepts in social psychology by studying provided examples (instances of concepts that are provided to students illustrate how the concept can be applied), generating examples (instances of concepts that the student generates on his or her own to practice applying the concept), or by receiving a combination of alternating provided examples and generated examples. Two days later, students completed final tests (an example classification test and a definition cued recall test). Experiment 2 replicated and extended findings from experiment 1. The extension group was a variation of the combination group, in which participants were simultaneously presented with a provided example while generating an example. In both experiments, long-term learning and study efficiency were greater following the study of provided examples relative to the other example-based learning techniques.

Full Text

Cited Authors

  • Zamary, A; Rawson, KA

Published Date

  • March 1, 2018

Published In

Volume / Issue

  • 30 / 1

Start / End Page

  • 275 - 301

Electronic International Standard Serial Number (EISSN)

  • 1573-336X

International Standard Serial Number (ISSN)

  • 1040-726X

Digital Object Identifier (DOI)

  • 10.1007/s10648-016-9396-9

Citation Source

  • Scopus