Over-the-Counter Data's Impact on Educators' Data Analysis Accuracy

Abstract

There is extensive research on the benefits of making data-informed decisions, but research also contains evidence many educators incorrectly interpret student data. Meanwhile, the types of detailed labeling on over-the-counter medication have been shown to improve use of non-medication products, as well. However, data systems most educators use to analyze student data usually display data without supporting guidance concerning the data's proper analysis. In this dissertation, the data-equivalent to over-the-counter medicine is termed over-the-counter data: essentially, enlisting medical label conventions to pair data reports with straightforward verbiage on the proper interpretation of report contents. The researcher in this experimental, quantitative study explored the inclusion of such supports in data systems and their reports. The cross-sectional sampling of 211 educators of varied backgrounds and roles at nine elementary and secondary schools throughout California answered survey questions regarding student data reports with varied forms of analysis guidance. Respondents' data analyses were found to be 307% more accurate when a report footer was present, 205% more accurate when an abstract was present, and 273% more accurate when an interpretation guide was present. These findings and others were significant and fill a void in field literature by containing evidence that can be used to identify how data systems can increase data analysis accuracy by offering analysis support through labeling and supplemental documentation. Recommendations for future research include measuring the impact over-the-counter data has on data analysis accuracy when all supports are offered to educators in concert. Keywords: abstract, analysis, data, data-driven decision-making, DDDM, data-informed decision-making, data system, data warehouse, footer, ICT, interpretation guide, report.