Making Sense of Generative Learning

Author:

Fiorella LoganORCID

Abstract

AbstractHow do learners make sense of what they are learning? In this article, I present a new framework of sense-making based on research investigating the benefits and boundaries of generative learning activities (GLAs). The generative sense-making framework distinguishes among three primary sense-making modes—explaining, visualizing, and enacting—that each serve unique and complementary cognitive functions. Specifically, the framework assumes learners mentally organize and simulate the learning material (via the visualizing and enacting modes) to facilitate their ability to generalize the learning material (via the explaining mode). I present evidence from research on GLAs illustrating how visualizations and enactments (instructor-provided and/or learner-generated) can facilitate higher quality learner explanations and subsequent learning outcomes. I also discuss several barriers to sense-making that help explain when GLAs are not effective and describe possible ways to overcome these barriers by appropriately guiding and timing GLAs. Finally, I discuss implications of the generative sense-making framework for theory and practice and provide recommendations for future research.

Funder

Directorate for Education and Human Resources

Spencer Foundation

Publisher

Springer Science and Business Media LLC

Subject

Developmental and Educational Psychology,Education

Reference213 articles.

1. Adesope, O. O., Trevisan, D. A., & Sundararajan, N. (2017). Rethinking the use of tests: A meta-analysis of practice testing. Review of Educational Research, 87(3), 659–701.

2. Adesope, O. O., Nesbit, J. C., & Sundararajan, N. (2022). The mapping principle in multimedia learning. In R. E. Mayer & L. Fiorella (Eds.), The Cambridge handbook of multimedia learning (3rd ed., pp. 351–359). Cambridge University Press.

3. Agarwal, P. K., Nunes, L. D., & Blunt, J. R. (2021). Retrieval practice consistently benefits student learning: A systematic review of applied research in schools and classrooms. Educational Psychology Review, 33(4), 1409–1453.

4. Ainsworth, S. (2006). DeFT: A conceptual framework for considering learning with multiple representations. Learning and Instruction, 16(3), 183–198.

5. Ainsworth, S. (2022). The multiple representations principle in multimedia learning. In R. E. Mayer & L. Fiorella (Eds.), The Cambridge handbook of multimedia learning (3rd ed., pp. 158–170). Cambridge University Press.

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