THE IMPACT OF MENTORING ON THE VARIATION OF STUDENT COLLECTED CLIMATE DATA

KCE3 is a program designed to increase the visibility and relevance of environmental science to pre-college and college students by collecting climate data in Kansas City. Surface and air temperature data is collected by middle, high school, undergraduate and graduate students where they live. Public participation in scientific research (PPSR), is scientific research that involves volunteers in data collection, analysis, and interpretation. The main goal of PPSR in the collection of urban surface temperature data is to collect large numbers of and spatially distributed data points using volunteers that are part of the impacted communities and increase awareness of the consequences of urban heat. Using PPSR over 3,200 temperature measurements were collected over three years by providing guidelines for data collection to Kansas City residents, and the variance in the data was compared with level of guidance.

The data shows that the more experienced the participants are, the more precise the data is. Younger scientists need additional guidance in collecting data to be used for research. Middle school students struggle to collect precise data in educational settings and were the least engaged with the process of data collection. In guided extra-curricular environments with a 2-to-1 student to mentor ratio, middle school students can collect data as accurate as an established researcher. This was tested over two consecutive years with a group of middle and high school students who were mentored over four weeks, and students collected data that had a variance of 3.34 as compared to students of the same age who were not mentored, with a variance of 16.03. Graduate students were used as a control and collected data independently with no mentoring with a variance of 2.92.

If younger students are guided through data collection with mentoring, they collect more precise data with less variation. An f-test was run to analyze the significance in the calculated differences in the data sets, showing a large statistical difference (n=4.80) in the data based on the presence of mentoring. Mentoring is one of the most crucial steps in improving the precision of data collected by younger students so that they can be included in PPSR research projects.