Investigating College Students' Reasoning With Messages of Risk and Causation

• Main Author: Samuel Luke Tunstall
• Format: Article
• Language: English
• Published: Taylor & Francis Group 2018-05-01
• Series: Journal of Statistics Education
• Subjects: Quantitative reasoning; Statistics education research; Statistical literacy; Toulmin
• Online Access: http://dx.doi.org/10.1080/10691898.2018.1456989

Language of risk and causation pervades modern media sources. In response, statistical literacy is often framed as a critical means of understanding such discourse. At Michigan State University, several faculties have worked to create a new mathematics course, entitled Quantitative Literacy, to fulfill the University's general education mathematics requirement. Though the course does not center exclusively on statistical thinking and methods, the curriculum does include attention to science reports in the media, among other topics, which are often based on research using statistical methods. In an effort to begin to understand how students reason with such articles before having taken the course, students in Quantitative Literacy answered several open-ended questions at the beginning of the semester in response to an opinionated news article about risk in relation to processed meats. Analysis of 152 students' responses using Toulmin's framework for argumentation revealed that the majority of the students agreed with the author's misleading message. These results suggest that prior knowledge and preexisting biases serve as potential barriers to the types of reasoning fostered in the course, and thus that the Quantitative Literacy curriculum should specifically attend to students' preexisting beliefs about the real-world contexts encountered in the course.