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.