"Analysis is a continuous, recursive process throughout data collection to final representation. It can not happen if the researcher is non-reflecctive and mindless in their approach to the topic." - Freed

*Required Readings and Activities

Module Two: Data Collection, Analysis and Interpretation

2.5 Analyzes data for "meaning" categories and makes connections across categories, displays data analysis to show connections with theoretical frameworks

A. Readings: Merriam, Chap 8 & 9; Eisner, Chapter 7; and Clandinen, Chap 8.

B. Web and Other Links

15 Kinds of Data Analysis - Ratcliff
Structural Analysis - Boeree
Analytic Induction as a Qualitative Research Method of Analysis - Ratcliff
Finding A Path Through the Research Maze - Cole

C. Discussion Starters/Reflective Journal Topics: (Choose one topic and start or continue a discussion thread.)

1. Which ways to analyze data come naturally to you? Why might this be so? How could you develop a comfort level for other kinds of data analysis?

D. Experiences/Activities:

1. Browse through the various Data Analysis of Themes (LINK) examples. Notice how data is organized and displayed to facilitate analysis.

***2. Download raw data "Challenges teachers encounter teaching diverse cultures" . Using an inductive process, categorize into 5 - 8 groups. Then discuss how the groups are related to each other. (Do this activity with small groups and identify the level of agreement between groups.)

E. Portfolio Documentation:

1. Organize data that you have analyzed so that others can see how you came to the different categories you have. Document your thinking processes as you developed categories. Show how you defined the various categories. Show how the categories are related to one another .