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Drawing-to-Learn: Does Meta-Analysis Show Differences Between Technology-Based Drawing and Paper-and-Pencil Drawing?


Drawing-to-learn is a specific learning/reading strategy studied across many domains. In response to gaps in our knowledge about drawing-to-learn, we conducted a systematic meta-analysis of the literature published since the influential 2005 Van Meter and Garner literature review. We analyzed the benefits of directed learner-generated visual representations such as sketching, drawing, or computer-assisted creation of a full or partial static image. Forty-one peer-reviewed articles were screened in, together with 9 dissertations and 2 other documents; published from 2005 to 2018, these included 53 studies and 166 effects based on 8111 participants. The overall effect of drawing-to-learn across all dependent variable types (factual, inferential, and transfer) and both types of effects—comparing different types of drawing and comparing drawing to non-drawing conditions—was a significant g = 0.69. The overall effect was significant but differed across outcomes (g = 0.85 for factual, g = 0.44 for inferential, and g = 0.22 for transfer). Analyses across 6 moderators are presented. Not only does the literature continue to show that drawing-to-learn is better than the status quo, but directed drawing improves factual as well as inferential and transfer learning. Finally, researchers have found ways to improve drawing-to-learn instruction so that it can be even more effective than the simple directive to make a drawing.

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    Omitted domains (e.g., humanities and mathematics) were not represented among these effects for these dependent variables and research designs.


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The authors thank Yanhong “Olivia” Zhong and Dawn M. Brown for assistance with tallying results and creating tables.


The research reported herein was supported by award #DRL-1560724 from the US National Science Foundation to the University of Illinois at Urbana-Champaign. The opinions are solely the authors’ own and do not represent the policies of NSF or the US Government.

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Correspondence to Jennifer G. Cromley.

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Submitted for consideration in Journal of Science Education and Technology on May 15, 2019.

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Appendix 1

Appendix 1

Table 4 Correlations (Cramer’s V) among categorical moderators

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Cromley, J.G., Du, Y. & Dane, A.P. Drawing-to-Learn: Does Meta-Analysis Show Differences Between Technology-Based Drawing and Paper-and-Pencil Drawing?. J Sci Educ Technol 29, 216–229 (2020).

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  • Visual representations
  • Strategies
  • Mental models
  • STEM