Students’ representational competence with drawing technology across two domains of science

Abstract

Research has indicated the importance of representational competence for learning science. Issues related to the nature of students’ representational competence, such as how they demonstrate representational competence across different domains of science, require investigation. In the present study, four aspects of representational competence across two domains of science were investigated: use of dynamic representations, use of multiple representations, use of adequate science concepts, and use of visualization strategies. Two instruments, the representational competence of states of matter and the representational competence of carbon cycling assessments were delivered via a computer‐based drawing tool and were used to measure 40 senior high school students’ representational competence for the topic of states of matter and carbon cycling. The results indicated that the representational competence demonstrated in one topic was not significantly correlated to that demonstrated in the other. The results of path analyses using multiple regressions indicated a trend that the extent to which multiple representations were employed was significantly and closely related to the extent to which appropriate science concepts were applied to make the drawings. Implications of the findings are discussed.

Sketching, not representational competence, predicts improved science learning

“…Studies on the efficacy of drawing for improving STEM learning outcomes have demonstrated the independent utility of drawing for improving learning (e.g., Cromley et al (2020) for a review). With the appropriate scaffolds, drawing has been demonstrated to support students' developing mental models of scientific phenomena presented primarily through text-based instructional materials (e.g., Chang, 2018;Gobert, 2005;Schleinschock, Eitel, & Scheiter, 2017); Schwamborn et al, 2011) and animations (e.g., Wu & Rau, 2018). These studies suggest that activities focused on drawing disciplinary representations may better help students to develop the skills associated with RC in a domain that will, in turn, facilitate their learning of disciplinary concepts related to various scientific models.…”

Physics Learning with E-Book Using Problem Based Learning (PBL) Model to Improve Image Representation Ability of High School Students on Optical Material

“…Students' ability to understand images, and understand the relationship between variables in the picture affected learning outcomes. Students with good image representation ability, has a good learning outcome, because the representation serves as a tool to help solve problems in physics [26] [12] and make it easier to understand and explain certain phenomena [10][27] [28].…”

Plan‐Draw‐Evaluate (PDE) pattern in students' collaborative drawing: Interaction between visual and verbal modes of representation

“…Recent studies have also examined analyzing students' representational competence using drawing technology across different topics (H. Y. Chang, 2018) as well as developing analytical frameworks to understand the various meanings made in student-generated drawings (Tang et al, 2019).…”