3c.+Data+Analysis

=**Data Analysis**=

The survey incorporates "multi-data" and subsequently I will have to use "multi-analysis" (Johnson, B., & Christensen, L., 2008) to produce conclusions. An example of one of the many ways this data can be treated would be to statistically compare teachers attitudes towards technology with their actual utilization of specific tools.

Once I have collected data from the "Google Docs" spreadsheet, I will use contingency tables as described in chapter 17 of (Johnson, B., & Christensen, L., 2008) to examine the quantitative questions in the survey. This type of data could be checked for validity using the "chi-square" test as described in chapter 18. It would be interesting to see, for instance, which middle school grade level utilizes more technology, or to determine if teachers of different subject areas are greater consumers of technology.

The data that will be the heart of my research is, however, the qualitative questions that seek to uncover new and effective technologies that hold the most promise for enhancing education of the middle school special education student. This data will initially be analyzed and shared using bar graphs highlighting the most popular responses. For this method to be effective I will have to create and sort all the responses into inductive categories. Otherwise we will have far too many bars to view on the graph. See page 538 of (Johnson, B., & Christensen, L., 2008) for example of this type of coding.

I will be using the IBM computer program "SPSS Statistics" to link to the spreadsheet and analyze and validate the data. I have begun to test this program with sample questions from my survey and I have two screen shots below from my initial trials. This is a robust program and it should be able to offer all the necessary conclusion needed for my research.



Johnson, B., & Christensen, L. (2008). Educational Research, Quantitative, Qualitative, and Mixed Approaches (3rd ed.) (J. McNall, Ed.). Thousand Oaks, CA: Sage Publications Inc.