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…
Data visualisation can be used from organising qualitative research data to analysing and presenting results. It also can contribute to researchers and their readers to discover new interpretations and knowledge about the phenomenon studied.
Visual representation is helpful during all phases of data analysis. These allow identifying patterns, numerical and non-numerical trends, using graphs, maps, tables, diagrams, flowcharts, among others.
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.