07/20 - Data Analysis and Interpretation

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07/20 - Data Analysis and Interpretation by Mind Map: 07/20 - Data Analysis and Interpretation

1. Qualitative Analysis

1.1. Things to do

1.1.1. Finding categories and making connetions

1.1.2. Combining the evidence

1.1.3. Looking for themes and patterns

1.1.4. looking at the type of language used

2. Analysing Data

2.1. 1. familiarise yourself with data

2.1.1. Read through it and start noting themes

2.1.2. Examples of reoccuring themes Attitudes Behaviours Motivations Views/opinions

2.1.3. Patterns Frequencies Magnitudes Major occurences Structures Topics outlining Processes Causes Consequences

2.2. 2. Categories the data

2.2.1. Devise a conceptual framework/index

2.2.2. List themes Journal Post-it notes

2.2.3. Identify links or connections

2.2.4. Aim is to create sub-themes of concepts within larger categories It's worth having an "other" category for themes that don't fit.

2.2.5. CODE and DEFINE categories

2.3. 3. Code the data

2.3.1. Place an index next to the data

2.4. 4. Sort the data

2.4.1. Focus on categories so you can look at the detail of each category

2.4.2. Thematic sets

2.5. 5. Summarise and synthesis the data

2.5.1. Reduce the data and highlight relationships

3. Suggestions

3.1. Use POLTS as a theory led analysis

3.2. To improve teaching practice

4. Data

4.1. Types of Data

4.1.1. Ordinal Data Data in order eg. Unsatisfactory - Excellent

4.1.2. Nominal Data eg. Male/Female Used to compare groups/populations

4.2. Likert Scales

4.2.1. Needs to have order and equal value

4.3. 3 Steps

4.3.1. 1. Present

4.3.2. 2. Describe In describing, explain the most indicative result The mean is usually the most indicative

4.3.3. 3. Analyse Make Meaning of the data

4.4. Averages

4.4.1. Mean Parametric Uses the bell curve

4.4.2. Median Middle score in the rankings

4.4.3. Mode Most common score

5. Excel Proficiency

5.1. Correlation

5.2. Mean, Median, mode