Expanding the Learning Network: How Teachers Use Pinterest

Quantitizing, commonly understood to refer to the numerical translation, transformation, or conversion of qualitative data, has become a staple of mixed methods research. Typically glossed are the foundational assumptions, judgments, and compromises involved in converting disparate data sets into each other and whether such conversions advance inquiry. Among these assumptions are that qualitative and quantitative data constitute two kinds of data, that quantitizing constitutes a unidirectional process essentially different from qualitizing, and that counting is an unambiguous process. Among the judgments are deciding what and how to count. Among the compromises are balancing numerical precision with narrative complexity. The standpoints of "conditional complementarity," "critical remediation," and "analytic alternation" clarify the added value of converting qualitative data into quantitative form. Show more

The emergence of the internet, particularly Web 2.0 has provided access to the views and opinions of a wide range of individuals opening up opportunities for new forms of communication and knowledge formation. Previous ways of navigating and filtering available information are likely to prove ineffective in these new contexts. Connectivism is one of the most prominent of the network learning theories which have been developed for e-learning environments. It is beginning to be recognized by medical educators. This article aims to examine connectivism and its potential application. Show more