How generative drawing affects the learning process: An eye‐tracking analysis

Abstract

SummaryGenerative drawing is a learning strategy in which students draw illustrations while reading a text to depict the content of the lesson. In two experiments, students were asked to generate drawings as they read a scientific text or read the same text on influenza with author‐provided illustrations (Experiment 1) or to generate drawings or write verbal summaries as they read (Experiment 2). An examination of students' eye movements during learning showed that students who engaged in generative drawing displayed more rereadings of words, higher proportion of fixations on the important words, higher rate of transitions between words and workspace, and higher proportion of transitions between important words and workspace than students given a text lesson with author‐generated illustrations (Experiment 1) or students who were asked to write a summary (Experiment 2). These findings contribute new evidence to guide theories for explaining how generative drawing affects learning processes.

Let’s draw molecules: Students’ sequential drawing processes of resonance structures in organic chemistry

“…By referring to the prognostic drawing principle, Schwamborn et al (2010) point out that the quality of learners' drawings is predictive of their learning outcomes, i.e., the more accurately and correctly learners draw, the better their performance. This finding has been replicated in various studies (Mason et al, 2013;Schmeck et al, 2014;Rellensmann et al, 2016;Fiorella and Zhang, 2018;Hellenbrand et al, 2019;Schmidgall et al, 2020;Stieff and DeSutter, 2020).…”

“…In fact, by expressing one's reasoning and externalizing mental models, drawings can help learning new concepts and support problem-solving (Cox, 1999;Ainsworth et al, 2011;Quillin and Thomas, 2015;Cooper et al, 2017;Wu and Rau, 2019). In recent years, much research has been conducted on drawing as a learning activity across different STEM contexts such as chemistry (Hellenbrand et al, 2019), physics (Maries and Singh, 2018), biology (Schmeck et al, 2014), and geography (Gobert and Clement, 1999) at school and college levels. Predominantly, it has been shown that prompting learners to visually depict content presented in text-or animation-based instructional materials is an effective learning strategy as students who draw not only build higher quality explanations and develop a more coherent mental model of a studied phenomenon, but also perform better in subsequent tasks and tests (Bobek and Tversky, 2016;Fiorella and Zhang, 2018;Cromley et al, 2019).…”

Children learning to sketch: sketching to learn

“…Prain and Tytler (2012) provides a Representational Construction Affordances framework integrating three perspectives – semiotic , epistemic and epistemological – to explain how and why representational construction supports learning. For example, drawing helps direct learners’ attention to the conceptually relevant parts of the content (Hellenbrand et al , 2019). More recently, Ainsworth and Scheiter (2021) argue learners should draw visual representations for themselves as it is an active, constructive and interactive form of engagement and promotes learning.…”

Mobile Eye-Tracking Data Analysis Using Object Detection via YOLO v4

“…In this way, the technique allows for the investigation of social influences on learning [24]. It also enables study of the underlying processes that occur when students generate external representations [25]. For example, Hellenbrand and colleagues analyzed the learning strategies of students who generated schematic representations of virus cells and discovered that relevant words in the instructional text were reread more often, and transitions between the drawing and the text increased when students produced the drawings themselves [25].…”

“…It also enables study of the underlying processes that occur when students generate external representations [25]. For example, Hellenbrand and colleagues analyzed the learning strategies of students who generated schematic representations of virus cells and discovered that relevant words in the instructional text were reread more often, and transitions between the drawing and the text increased when students produced the drawings themselves [25]. Schindler and colleagues used mobile eye-tracking to investigate creative problem-solving processes in the context of math and found that this method allows for more insight than analysis of videos and/or paper-pencil solutions [26].…”