John Voiklis

Sensitivities to early exchange in synchronous computer-supported collaborative learning (CSCL) groups

This study reports the impact of high sensitivity to early exchange in 11th-grade, CSCL triads solving well- and ill-structured problems in Newtonian Kinematics. A mixed-method analysis of the evolution of participation inequity (PI) in group discussions suggested that participation levels tended to get locked-in relatively early on in the discussion. Similarly, high (low) quality member contributions made earlier in a discussion did more good (harm) than those made later on. Both PI and differential impact of member contributions suggest a high sensitivity to early exchange; both significantly predicting the eventual group performance, as measured by solution quality. Consequently, eventual group performance could be predicted based on what happened in the first 30-40% of a discussion. In addition to drawing theoretical and methodological implications, implications for scaffolding CSCL groups are also discussed.

Problem solving as a complex, evolutionary activity: a methodological framework for analyzing problem-solving processes in a computer-supported collaborative environment

Viewed through the lens of complex systems science, one may conceptualize problemsolving interactions among multiple actors, artifacts, tools, and environmental structures as goal-seeking adaptations, and problem-solving itself, as a complex adaptive activity. Theories of biological evolution point to an analogical equivalence between problem solving and evolutionary processes and, thus, introduce innovative methodological tools to the analysis of computer-supported, collaborative, problem-solving processes. In this paper, we present a methodological framework for characterizing and analyzing these processes. We describe four measures that characterize genetic evolution - number, function, fitness, and persistence - to characterize the process of collaborative problem solving, and instantiate them in a study of problem-solving interactions of collaborative groups in an online, synchronous environment. Issues relating to reliability, validity, usefulness, and limitations of the proposed methodology are discussed.

A Complexity-Grounded Model for the Emergence of Convergence in CSCL Groups

We advance a complexity−grounded, quantitative method for uncovering temporal patterns in CSCL discussions. We focus on convergence because understanding how complex group discussions converge presents a major challenge in CSCL research. From a complex systems perspective, convergence in group discussions is an emergent behavior arising from the transactional interactions between group members. Leveraging the concepts of emergent simplicity and emergent complexity (Bar-Yam 2003), a set of theoretically-sound yet simple rules was hypothesized: Interactions between group members were conceptualized as goal-seeking adaptations that either help the group move towards or away from its goal, or maintain its status quo. Operationalizing this movement as a Markov walk, we present quantitative and qualitative findings from a study of online problem-solving groups. Findings suggest high (or low) quality contributions have a greater positive (or negative) impact on convergence when they come earlier in a discussion than later. Significantly, convergence analysis was able to predict a group’s performance based on what happened in the first 30–40% of its discussion. Findings and their implications for CSCL theory, methodology, and design are discussed.

An Emergentist Account of Collective Cognition in Collaborative Problem Solving

As a first step toward an emergentist theory of collective cognition in collaborative problem solving, we present a proto-theoretical account of how one might conceive and model the intersubjective processes that organize collective cognition into one or another--convergent, divergent, or tensive--cognitive regime. To explore the sufficiency of our emergentist proposal we instantiate a minimalist model of intersubjective convergence and simulate the tuning of collective cognition using data from an empirical study of small-group, collaborative problem solving. Using the results of this empirical simulation, we test a number of preliminary hypotheses with regard to patterns of interaction, how those patterns affect a cognitive regime, and how that cognitive regime affects the efficacy of a problem-solving group.

SKRAPPLE: enabling media-based study schools, apprentice schools, and samba schools

SKRAPPLE stands for sharing knowledge representational artifacts in a peer-to-peer learning environment. SKRAPPLE combines a Squeak-based, media authoring and programming environment, an implementation of the symbols and worlds cognitive architecture, and a pedagogical method based on peer-mentoring. SKRAPPLE is meant to serve as a model for a new kind of school, both formal and informal, that would function as an open-source/open-content, public service media enterprise. In this model of school, children would be responsible for all authoring/production activities and these activities would allow and enable children to passionately immerse themselves in any content area, both intradisciplinary and interdisciplinary. The authors propose an initial specification and invite collaborators to develop, research, and implement the SKRAPPLE model.