Date of Award

5-2014

Level of Access Assigned by Author

Campus-Only Thesis

Degree Name

Master of Science (MS)

Department

Teaching

Advisor

Natasha M. Speer

Second Committee Member

Eric Pandiscio

Third Committee Member

Daniel Capps

Abstract

There is an increase in demand for individuals to be successful with graph interpretation. Society is currently lacking individuals who have majored in Science, Technology, Engineering and Mathematics (STEM). Most STEM courses require linear graph comprehension as a prerequisite skill. The Common Core State Standards Initiative for Mathematics, Next Generation Science Standards, and the Maine Revised Learning Results all characterize linear graph comprehension as skills to be mastered before a student enters high school. Reading information from graphs and making inferences based on graphically-presented information is challenging for students. Researchers have documented a variety of difficulties students have with graph comprehension. These difficulties include, among others, having knowledge of the graph context that incorrectly influences graph comprehension, viewing the graph as an iconic representation of the event, and confusing slope and height. Being able to extrapolate and make predictions based on graphs is especially challenging for students. This research on graph comprehension has been primarily focused on students in elementary, middle, and high school and findings do not provide definitive answers as to why these difficulties are prevalent or why certain kinds of questions are so challenging for students. Despite the important role graph comprehension plays in undergraduate students’ learning of STEM content, little is known about the performance and thinking of this population of students. For the present study, college students in introductory mathematics and physics courses were given linear graph comprehension tasks. Data include both written responses from all students and interviews of a subset of students designed to understand their thinking as they answered the written responses. Findings indicate that students answered extrapolation questions incorrectly more often than other questions. On a written in-class survey only 67.6% of students correctly answered an extrapolation question correctly, compared to a success rate of 86.7% on interpolation questions. Interview data analysis corroborated this finding. Moreover, the data suggest that student responses to interpolation questions can be used as a predictor of a student’s success on extrapolation questions. Implications for instruction are discussed along with directions for further research.

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