Analyzing Qualitative Data

Notes to the talk

Here is a brief that summarizes the main themes and important ideas discussed in the provided sources: an audio recording ("Data Analysis_042025.mp3") of a thesis seminar session and excerpts from a document titled "Making Sense of Stories: Analyzing Qualitative Data in ELT Teacher Training." The primary focus is on data analysis techniques, particularly qualitative coding, triangulation, and the potential for incorporating quantitative elements.

I. Key Themes and Important Ideas:

A. Importance of Completing Data Collection Before Analysis:

* The seminar leader emphasizes that data analysis should only begin after all data collection is complete. "Today's discussion is about data analysis. All of you have collected or very close to having completed uh collecting all of your data and this is an important requirement to continue the process of data analysis... If you are still trying to collect some information, know that what we talk about today uh you need to wait."

* Starting analysis prematurely, before all data is gathered, is considered a "mistake."

B. Understanding the Purpose of Data Analysis:

* Data analysis is crucial for understanding the collected data and determining what is relevant and significant to report in the results and discussion sections of the thesis.

* It helps researchers move from a large amount of raw data to focused and insightful findings. "Think of it like this. All of you are at this point, you've collected, if not all, most of your data. So you have all this data that you've collected... Ahora con todo esta información which data is not relevant... So you're going to then include this circle represents now only the information that relates to your research questions... Now from your data analysis... you're going to then figure out ok of all this information that now is relevant to my study, what is worth What is including in mys discussion?"

* Not all relevant data needs to be reported; the analysis helps identify the most "important, surprising, insightful, interesting" findings.

C. The Concept and Importance of Triangulation:

* Triangulation involves bringing together different data sources (e.g., interviews, observations, documents) to gain a more comprehensive understanding of the research topic.

* It allows for comparison between what participants say they do/believe, what they actually do (observed), and their planning/reflection processes. "Think of this if it helps to look at it like this. Your um your information here is allowing you to compare different things. For example, what people say they do or believe... What do they actually do? Well, to know that, what do we have to do? Have to observe."

* The seminar leader stresses the importance of having sufficient data to triangulate and encourages participants to address any concerns about this. "If anybody today right now has concerns about whether or not you have the types of data to allow you to triangulate, we need to have a discussion today."

* The "Making Sense of Stories" document provides specific examples of triangulation in ELT teacher training research, such as comparing planned instructions in lesson plans with delivered instructions observed in the classroom. "Compare the planned instructions (document) with the delivered instructions (observation). Were planned ICQs actually used?"

D. Introduction to Qualitative Coding:

* Qualitative coding is defined as a systematic process of labeling and organizing segments of text data (transcriptions, observation notes, documents) to identify patterns, themes, and concepts relevant to the research questions. "The process of