Supporting small-group learning using multiple Web 2.0 tools: A case study in the higher education context

In this single-case study, small groups of learners were supported by use of multiple social software tools and face-to-face activities in the context of higher education. The aim of the study was to explore how designed learning activities contribute to students' learning outcomes by studying probabilistic dependencies between the variables. Explorative Bayesian classification analysis revealed that the best predictors of good learning outcomes were wiki-related activities. According to the Bayesian dependency model, students who were active in conceptualizing issues by taking photos were also active blog reflectors and collaborative knowledge builders in their group. In general, the results indicated that interaction between individual and collective actions likely increased individual knowledge acquisition during the course.

► Multiple social software tools and face-to-face activities.
► Bayesian methods used to classify and model the complex dependencies.
► Best predictors of good learning outcomes are wiki-related activities.
► Practical implications for designing the use of social software tools.