ABSTRACT
The field of media literacy is characterized by a multitude of literacy frameworks and related competence models. These models consist of multiple variables and indicators referring to knowledge, skills, and competences. To study these different models, a sound methodology that allows to map and compare them is needed. Classical comparative research falls short. In the literature a distinction is made between (1) qualitative analysis of a single or limited number of in-depth case studies and (2) a cross-case analysis of large amounts of quantitative data based on large datasets. The former has the downside of being time-intensive and, due to its qualitative nature, is not generalizable. The second has the downside of requiring extensive datasets that need to be statistically analyzed. To overcome this problem, the quick-scan method was developed. It comprises a larger number of qualitative case studies that capture the variation of possible cases in a field. The cases are analyzed based on a limited set of variables that constitute the analytical framework. By mapping the variables and their indicators in a large single matrix, the analysis of similarities, differences, and variances over the cases becomes possible, allowing for the detection of trends, blind spots, and shared characteristics. The method is explained by applying it to 13 digital literacy models.
