From Codes to Connections: What Axial Coding and CCA Revealed

Coding paradigm (Strauss & Corbin 1998, p. 127)

I learned a lot practicing axial coding and constant comparative analysis (CCA) this week. With axial coding, I found that I didn’t just have to label parts of the data on their own. I started to look at how the codes might connect, or how one learner’s experience might relate to another. I also start to group smaller ideas into larger categories.

My study of online courses showed that poor technology, unclear instructions, and a lack of teacher feedback affected how learners felt while learning. A learner who was confused would probably become irritated and avoid asking for help. Furthermore, unnecessary confusion would lead to a loss of motivation in the long run. For instance, living in a place where the technology does not work most of the time will create negative feelings. When I saw the codes together, the patterns became visible. It became even more clear to me how one issue can definitely affect another. Hence, it is evident that issues for learners are often linked and are not necessarily separate problems.

Deciding which codes should be grouped together was the hardest part for me. Sometimes two codes seemed similar. Even though they might represent two slightly different experiences, I was not sure if they meant the same at times. Therefore, I had to constantly remind myself not to make assumptions based on my interest in online learning and technology. To help overcome this, I turn my focus more on what participants actually said and how they described their experiences. This took time because I really wanted the categories to reflect the data as closely as possible.

CCA helped me notice differences between learners that I may have missed. For example, two students may say an online class was challenging, but for very different reasons. One learner might struggle to use the relevant technology, while another might feel they aren't getting enough support from their instructor. By comparing their answers, it helped me see how learners can have the same experience but for different reasons. This help me to notice shared patterns and distinct needs among learners.

This connects to my research interests in AI, mindfulness, and online learning. These methods  will definitely help me understand how learners experience AI tools and support systems, and how they may affect motivation, confidence, stress, engagement, and students’ overall success in an online learning context.