Studying the effect of interaction analysis indicators on students' selfregulation during asynchronous discussion learning activities

Selfregulation has become an important research subject during the past 20 years, especially in Technology Enhanced Learning approaches, following student-centered strategies. When designing learning activities under this scope, in a social context, the need for building supporting tools for the participants of such activities has been highlighted. We have implemented such tools, by applying Interaction Analysis (IA) techniques, in order to support the participants of asynchronous discussion learning activities. In this paper we study the effects of IA indicators on students’ selfregulation. We present research findings from several implemented case studies, in order to confirm our hypothesis, that such supporting tools indeed facilitate students’ selfregulation, as it was shown both quantitatively and qualitatively, thus enhancing the overall activity, as well as the collaborative process itself.