Reporting Data with "Over-the-Counter" Data Analysis Supports Increases Educators' Analysis Accuracy

• Main Author: Rankin, Jenny Grant
• Format: Report
• Language: English
• Published: 05.12.2013
• Subjects: Accuracy; California; Data Analysis; Data Interpretation; Database Management Systems; Drug Therapy; Error of Measurement; Experiments; Information Utilization; Knowledge Base for Teaching; Merchandise Information; Statistical Analysis; Statistical Data; California

There is extensive research on the benefits of making data-informed decisions to improve learning, but these benefits rely on the data being effectively interpreted. Despite educators' above-average intellect and education levels, there is evidence many educators routinely misinterpret student data. Data analysis problems persist even at districts where there is proactive support for data use, as another variable plays a significant role in rendering successful or unsuccessful data use: the tool educators use for data analyses, which is typically a data system. These data systems and their reports usually display figures "without" supporting guidance concerning the data's proper analysis. A solution to analysis errors lies in the data-equivalent to over-the-counter medicine, termed "over-the-counter data": essentially, enlisting medical labeling conventions to pair education 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 education data systems and their reports, while also investigating varied formats for each support. The cross-sectional sampling procedure incorporated responses from 211 educators of varied backgrounds and roles at nine elementary and secondary schools throughout California. Participants 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. Findings were significant and fill a void in field literature with evidence that can be used to identify how data systems can increase educators' data analysis accuracy by offering analysis support through labeling and supplemental documentation.