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WCQR2025 – 9th World Conference on Qualitative Research
The 9th World Conference on Qualitative Research (WCQR2025) will be held from 4 to 6 February 2025 at Jagiellonian University,…
Visual methodologies in education have a potential for engaging students in a process of self-reflection to change behaviours. This essay aims to explore the benefits of image-based data and methodologies, such as cartoons analysis, in tourism educational environments, based on an exploratory exercise…
Qualitative Research has benefited from the enormous progress in terms of methods and techniques with intensive use of technology. The current demands in the investigative context compel more and more researchers to equip themselves with digital tools that provide speed and efficiency in their research processes.
One of the main errors verified in research is the lack of planning of adequate methods for data analysis. For example, to develop a data collection instrument, it is necessary to pay attention to the tools used to obtain results (analysis). Analysing qualitative data is not a task without difficulties, as the non-numeric and unstructured data corpus is generally diffuse and complex. There are no clear and widely accepted rules on how to analyse non-numeric and unstructured data.
The seven essential steps or subtasks that we will describe below are transversal or generic to qualitative data analysis techniques. The technique’s focus on the analysis rests on specific choices according to each objective and research questions.
Content Analysis is a data analysis technique, collected from a variety of sources, but preferably expressed in text or images. The nature of these documents can be varied, such as archival material, literary texts, reports, news, evaluative comments of a given situation, diaries and autobiographies, articles selected through the method of literature review, transcripts of interviews, texts requested on a specific subject, field notes, etc