Reflections on High School Students’ Graphing Skills and Their Conceptual Understanding of Drawing Chemistry Graphs

Abstract

Special importance was attached to science education in the Turkish education system in the 1960s in order to catch up with the scientific and technological developments that were occurring especially in European countries; up-to-date science programs were designed and new understanding was brought to these programs through the application of the scientific method as opposed to the context of unnecessary learning and rote memorization that had been included (Ergul, 1999). In order to increase the retention and meaningfulness of scientific knowledge, many concrete materials such as maps, charts, pictures, and graphs of concepts in addition to laboratories have been utilized. Since graphing is an indispensable element of science and social studies, students need to know from an early age how to use graphs and understand the different types (Inan, Inan, & Aydemir, 2014). The skill of using graphs is separated into three areas: interpretation, modeling, and conversion. Interpretation is about expressing the relevant graph orally, modeling is about expressing an observed state through graphs, and conversion is about drawing a different graph that expresses the same state as a given graph. All of these skills require using different types of intelligence. Individuals with mathematical-logical or visual-spatial intelligence need to see patterns in their learning to organize their information and see what they are learning (Secken & Yoruk, 2012). Visualization can be addressed through graphs that symbolize words or concepts and give more idea of the meaning of these words or concepts beyond their sound; thus, graphical representations play a special role in mathematics and science practice (Fuini & Gray, 2000). Different skills are essential in this century in terms of science and mathematics. One of the most important skills is the ability to work with data. This is exemplified by making inferences from given data, finding trends, critiquing and using data to support and rebut claims, ensuring complex relations (dual, triple, quadruple, etc.) between multivariate data, representing results in the quickest way, generating clear and perceptible data displays, and clarifying data assessment and analysis (Glazer, 2011; Kelly, Jasperse, & Westbrooke, 2005).Dori and Hameiri (2003) claimed that chemical education is a complex human endeavor that involves deep understanding of diverse concepts and requires a mental transfer between several modes of representation. Chemistry, being an experimental science, requires chemistry classroom schedules to involve experiments in laboratories. However, secondary schools do not have enough labs for chemical experiments, their equipment is insufficient for investigations, or they have no visual materials for effectively learning chemistry. Graphs are a tool of chemistry classes that can be used to express relations between most chemistry concepts. Therefore, students' proper comprehension and interpretation of the relations between chemistry concepts is directly related to their successful understanding and interpretation of graphs (Secken & Yoruk, 2012).Many researchers believe that inadequate graphing skills are a serious barrier to comprehending the concepts of mathematics and science (Lapp & Cyrus, 2000). Therefore, students' ability to interpret graphs and graphically represent scientific phenomena is critical. Science concerns the study of naturally occurring phenomena, and mathematics has allowed us to describe these phenomena in terms of equations that allow us to predict the behavior of systems as their conditions change. For this reason, mathematical knowledge is necessary for expressing scientific laws and solving problems (Guzel, 2004). A well-drawn graph provides a bridge between the two disciplines as it provides a convenient way of visualizing mathematics and science together. Graphs are overwhelmingly used in science education and laboratories in particular as they convey knowledge that most datasets cannot display alone. …