chapter  5
19 Pages

Quantitative Methods for Studying Small Groups

ByUlrike Cress and Friedrich Wilhelm Hesse (Knowledge Media Research Center, Tübingen, Germany)

Quantitative methodology includes various di erent methods of gathering and analyzing empirical data. What these methods have in common is that they do not just categorize phenomena but measure them and express their relationships in terms of quantity. If applied to collaborative learning, these methods allow researchers to analyze both learning processes and learning outcomes of individuals, interaction processes among group members, and learning outcomes of groups. e aim of quantitative research is to go beyond simply describing processes and outcomes, but to make and test predictions about the interrelation of these processes and about factors that trigger them. For understanding the quantitative research approach, we will rst describe some fundamental concepts of quantitative methodology: its hypothetico-deductive approach, its experimental logic, operationalization, measurement, and use of inferential statistics. On this basis, we will present some quantitative methods which are suited for collaborative learning (CL) studies. But quantitative research is a wide eld, and this chapter will not be able to give an exhaustive overview of its methods. Here we would refer readers to standard literature like Everitt and Howell (2005), or Keeves (1997). e focus of this chapter is on showing quantitative approaches for analyzing data of collaborative learning. ese consist of di erent types: data t hat describe interactional processes, data that describe individuals within groups, and data that describe groups. Considering this speci c structure of data, we will introduce the concept of units of analysis and describe events, interactions, persons, and groups as relevant units in the context of analyzing collaborative learning. For each of these levels of analysis, we will explain some typical quantitative methods and provide examples from CL-relevant studies. In addition, one speci c example will be cited throughout the whole chapter. is will make it easier to concentrate on relevant aspects of all the methods which are presented here.