Automatic Analysis of Student Drawings in Chemistry Classes

authored by

Markos Stamatakis, Wolfgang Gritz, Jos Oldag, Anett Hoppe, Sascha Schanze, Ralph Ewerth

Abstract

Automatic analyses of student drawings in chemistry education have the potential to support classroom teaching. To date, related work on handwritten chemical structures or formulas is limited to well-defined presentation formats, e.g., Lewis structures. However, the large variety of possible illustrations in student drawings in chemical education has not been addressed yet. In this paper, we present a novel approach to identify visual primitives in student drawings from chemistry classes. Since the field lacks suitable datasets for the given task, we introduce a method to synthetically create a dataset for visual primitives. We demonstrate how detected visual primitives can be used to automatically classify drawings according to a taxonomy of drawing characteristics in chemistry and physics. Our experiments show that (1) the detection of visual primitives in student drawings, and (2) the subsequent classification of chemistry- and physics-specific drawing characteristics is possible.

Organisation(s)

L3S Research Centre
Biology Education Section
Chemistry Education Section
Institute of Science Education
Leibniz School of Education

External Organisation(s)

German National Library of Science and Technology (TIB)

Type

Conference contribution

Pages

824-829

No. of pages

6

Publication date

26.06.2023

Publication status

Published

Peer reviewed

Yes

ASJC Scopus subject areas

Theoretical Computer Science, General Computer Science

Electronic version(s)

https://doi.org/10.1007/978-3-031-36272-9_78 (Access: Closed)

 

Details in the research portal "Research@Leibniz University"