Abstract:

Collective intelligence which results in intelligent collective action can be a powerful force for change; we have the power and potential to achieve many goals through the application of collective intelligence that we could never achieve individually. At the same time, our collective intelligence is rarely optimized and in spite of collaborative efforts to tackle a range of problems throughout our time, we find ourselves in a time of social crisis characterized by economic and environmental turmoil, war, crime, poverty, chronic disease, mental illness and social disengagement. Experience to date shows us how imperfectly we deal with these problems. Collective intelligence and collective action are often impeded by three interdependent human limitations: poor critical thinking skills, no clear methodology to facilitate group coherence, consensus design, and collective action; and limited computational capacities. These limitations need to be addressed if the power of collective intelligence and collective action is to be fully realized. We seek to address these limitations by proposing a new strategy for systems science education. This involves embedding a new systems science tool within a new systems science curriculum. The software tool we have developed integrates three thought structuring technologies: Argument Mapping (AM) for critical thinking, Interactive Management (IM) for system design, and Structural Equation Modelling (SEM) for mathematical modeling. The research agenda and preliminary research findings we present in this conference paper build upon the framework for systems science, collective intelligence, and collective action developed by John Warfield, past president of the International Society for the Systems Sciences.

Four experimental studies examine issues of tool and process optimization and overall curriculum efficacy:
(1) Study 1 examines the effects of open versus closed IM voting and high/low dispositional trust on measures of group consensus and trust in IM technology;
(2) Study 2 examines the efficacy of generic versus problem- specific feedback on the complexity and validity of collaborative argumentation during the IM/AM modeling process;
(3) Study 3 examines the effects of feedback on the emergence of cooperative conversational dynamics in groups high and low in dispositional trust, and finally,
(4) Study 4 will examine immediate (post-intervention) and sustained effects (1 year later) of integrated AM/IM/SEM systems science education training on critical thinking ability (using the Halpern Critical Thinking Assessment; Halpern, 2010), systems thinking ability (using the Lectical Reflective Judgment Assessment; Dawson, 2008). Final results from studies 1 and 2, and preliminary results from study 3, will be presented.

Keywords:

Collective Intelligence, Critical Thinking, Systems Thinking, Systems Science, Curriculum Design, Collaborative Learning.