Johanna Bohm wins poster price

Abstract: Optimizing students' lasting learning in complex domains, e.g., in physics, requires teachers to address different instructional goals. Students need to understand the learning content in order to transfer this knowledge to new or more complex problems. Generative learning activities like self-explanations promote understanding and knowledge transfer. However, short-term understanding and transfer is not sufficient in educational settings. School curricula are designed in cycles in which the material is revised and increased in complexity after longer delays (e.g., eight weeks). Such delays require students to remember knowledge for longer periods to be able to extend their knowledge in the next cycle. Hence, this instructional goal could be addressed by using retrieval practice. Retrieval practice (e.g., closed-book vs. open-book task performance) was able to increase retention after a delay of one to two weeks. This study will investigate how combining retrieval practice and generative learning – referred to as constructive retrieval – fosters lasting learning of complex materials in physics after an eight-week delay. We will extend the literature by using longer delays and complex materials that allow to evaluate possible boundary conditions essential in educational settings. Therefore, we will implement a 2 (self-explanation prompts vs. description prompts) x 2 (closed-book vs. open-book) experimental between-subject design. We expect that only the combination of closed-book and self-explanation prompting will enhance lasting learning and thus prepare students optimally for future learning.

Keywords: example-based learning, instructional design, knowledge construction, science and STEM