This segment defines qualitative coding as the process of creating and assigning labels to categorize data extracts, using the example of coding the sentence "Pigeons attacked me and stole my sandwich" to illustrate the concept of a code as a label describing a piece of content, and introduces the different ways codes can be applied. This segment explains the core difference between deductive and inductive coding approaches. Deductive coding uses pre-established codes applied to data, while inductive coding generates codes based on the data itself. The advantages and disadvantages of each approach are discussed, highlighting the trade-off between focused analysis and the potential for uncovering unexpected insights. This video explains qualitative coding for research. It covers deductive (pre-determined codes) and inductive (codes emerging from data) approaches, along with a hybrid method. The coding process involves initial coding (overview) and line-by-line coding (detailed analysis). Several coding methods are detailed (in vivo, process, descriptive, structural, value coding). The video concludes by discussing moving from coding to analysis (categorization and theme identification) and offers tips for successful coding. In vivo: Participant's own words, rather than an observation, close to the original. This is particularly useful when participants speak different languages or different cultures. This segment details the two crucial stages of qualitative coding: initial coding (gaining a general overview and developing initial codes) and line-by-line coding (in-depth analysis, refinement, and code expansion). It emphasizes the importance of avoiding automated coding software and focusing on human-based analysis for nuanced understanding.This segment introduces two specific coding methods: in vivo coding (using participants' own words as codes) and process coding (using action-based codes). The explanation includes examples and highlights the usefulness of in vivo coding when dealing with linguistic and cultural differences, and process coding for capturing unspoken actions and their contextual meaning. This segment offers five practical tips for optimizing the qualitative coding process. These include planning coding steps and approach beforehand, using a detailed codebook for deductive approaches, consistently tracking code meanings, keeping research aims in mind to avoid directional drift, and maintaining consistency throughout the coding process for reliable results. This segment focuses on the line-by-line coding stage, emphasizing the importance of detailed analysis, code refinement, and iterative adjustments. It highlights the iterative nature of the coding process, recommending meticulous work to ensure a high-quality code set. The importance of not rushing this stage is stressed.This segment discusses the transition from coding to qualitative data analysis. It emphasizes the iterative nature of the process, suggesting that insights may emerge during coding itself. It mentions several qualitative analysis methods (content analysis, thematic analysis, discourse analysis) and provides guiding questions to initiate the analysis phase, such as exploring actions, interpretations, language, assumptions, and the research aims.This segment explains the crucial step of code categorization in qualitative data analysis, illustrating how to group similar codes (e.g., dogs, llamas, lions into "mammals") to organize data and reveal connections between different code groups, ultimately enriching the dataset for further analysis. The process transforms raw codes into structured categories, laying the groundwork for identifying meaningful themes.This section details the process of identifying and articulating themes from categorized codes. It emphasizes synthesizing insights from coding and categorization to develop a narrative that aligns with the research aims and questions, using examples of content or thematic analysis to illustrate the development of meaningful interpretations from the data. Process coding: Action-based codes, movement, add non-verbal Descriptive coding: use a word to encapsulate a general idea/concept/event, non-textual stuff Structural coding: structure attributes Value coding Line by Line coding: Deep refine and code as much content as possible What actions and interactions are shown in the data What are the aims of the interaction? How do participants interpret what is happening? What does their choice of language reveal? Assumptions why are they doing and why is it important to me? What re they doing?