Improving visual data literacy skills of high school earth and space science students by weekly data analysis curriculum

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Montana State University - Bozeman, College of Letters & Science


Students must be able to interpret and analyze visual data to be successful in science classes, on high stakes assessment testing, and in their adult life. Visual data includes graphs, tables, charts, and diagrams. Traditionally, students receive instruction and practice using visual data literacy skills repeatedly in elementary school, middle school, and high school. This is a challenging skill set, as it requires scientific logical thinking and interpretation of abstract information. Students practice and grow as they continue through school, but continually seem to struggle to achieve mastery of visual data literacy. This project investigated how to improve student understanding, analysis, and use of visual data by focusing on a weekly treatment of Interpreting the Graph. Each week students focused on a piece of visual data that related to current class curriculum. Students worked in lab groups to understand and analyze the data. Class discussion allowed students to share their thoughts and discuss areas that were hard to understand. Data collected for this project included a student survey before the treatment process that assessed student perception of their own abilities and skill in visual data literacy. Students then took a pretest with data literacy questions using graphs, tables, charts, and diagrams. Each week for six weeks students filled out an Interpreting the Graph student worksheet. Each week students also recorded their weekly progress and overall class progress in a graphing packet. At the end of the six week treatment process students took a posttest. Students filled out a student survey about their growth and confidence in data literacy skills through the project, and a selection of students were interviewed about their growth in visual data literacy skills. The intervention seemed to show a positive impact on student learning and abilities. Students showed a 16.7% gain between pretest and posttest assessments. Through the course of the six week intervention, students showed an increase in confidence in visual data literacy skills, as well as showing improvement on the posttest assessment. Students improved their abilities to identify independent and dependent variables of an experiment. However, students showed limited growth in their ability to explain theoretical experimental methods used to create visual data seen in class, and in their ability to write explanations for patterns in visual data using numerical evidence from the data. The key findings showed that students seemed to benefit from learning a methodical analysis procedure to work through interpreting visual data. Students also benefited from participating in regular class discussion about visual data as it pertains to the curriculum. These findings were used in continued discussion with students to help them focus on their own learning. The methods from the intervention were used in curriculum planning to change how visual data analysis was taught in Earth and Space Science classes in future years and shared with other secondary science classes to increase student skill in visual data interpretation and analysis within our school district.




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