Systemic intervention for computer-supported collaborative learning

This paper presents a systemic intervention approach as a means to overcome the methodological challenges involved in research into computer-supported collaborative learning applied to the promotion of mathematical problem-solving (CSCL-MPS) skills in schools. These challenges include how to develop an integrated analysis of several aspects of the learning process; and how to reflect on learning purposes, the context of application and participants' identities. The focus of systemic intervention is on processes for thinking through whose views and what issues and values should be considered pertinent in an analysis. Systemic intervention also advocates mixing methods from different traditions to address the purposes of multiple stakeholders. Consequently, a design for CSCL-MPS research is presented that includes several methods. This methodological design is used to analyse and reflect upon both a CSCL-MPS project with Colombian schools, and the identities of the participants in that project

Between the Lines: documenting the multiple dimensions of computer supported collaborations

When we consider the possibilities for the design and evaluation of Computer Supported Collaborative Learning (CSCL) we probably constrain the CS in CSCL to situations in which learners, or groups of learners collaborate with each other around a single computer, across a local intranet or via the global internet. We probably also consider situations in which the computer itself acts as a collaborative partner giving hints and tips either with or without the addition of an animated pedagogical agent. However, there are now many possibilities for CSCL applications to be offered to learners through computing technology that is something other than a desktop computer, such as the TV or a digital toy. In order to understand how such complex and novel interactions work, we need tools to map out the multiple dimensions of collaboration using a whole variety of technologies. This paper discusses the evolution of a documentation technique for collaborative interactions from its roots in a situation where a single learner is collaborating with a software learning partner, through its second generation: group use of multimedia, to its current test-bed: young children using digital toys and associated software. We will explore some of the challenges these different learning situations pose for those involved in the evaluation of collaborative learning

A grid-based approach for processing group activity log files

The information collected regarding group activity in a collaborative learning environment requires classifying, structuring and processing. The aim is to process this information in order to extract, reveal and provide students and tutors with valuable knowledge, awareness and feedback in order to successfully perform the collaborative learning activity. However, the large amount of information generated during online group activity may be time-consuming to process and, hence, can hinder the real-time delivery of the information. In this study we show how a Grid-based paradigm can be used to effectively process and present the information regarding group activity gathered in the log files under a collaborative environment. The computational power of the Grid makes it possible to process a huge amount of event information, compute statistical results and present them, when needed, to the members of the online group and the tutors, who are geographically distributed.Peer ReviewedPostprint (author's final draft

Online discussion compensates for suboptimal timing of supportive information presentation in a digitally supported learning environment

This study used a sequential set-up to investigate the consecutive effects of timing of supportive information presentation (information before vs. information during the learning task clusters) in interactive digital learning materials (IDLMs) and type of collaboration (personal discussion vs. online discussion) in computer-supported collaborative learning (CSCL) on student knowledge construction. Students (N = 87) were first randomly assigned to the two information presentation conditions to work individually on a case-based assignment in IDLM. Students who received information during learning task clusters tended to show better results on knowledge construction than those who received information only before each cluster. The students within the two separate information presentation conditions were then randomly assigned to pairs to discuss the outcomes of their assignments under either the personal discussion or online discussion condition in CSCL. When supportive information had been presented before each learning task cluster, online discussion led to better results than personal discussion. When supportive information had been presented during the learning task clusters, however, the online and personal discussion conditions had no differential effect on knowledge construction. Online discussion in CSCL appeared to compensate for suboptimal timing of presentation of supportive information before the learning task clusters in IDLM

Emerging and scripted roles in computer-supported collaborative learning

Emerging and scripted roles pose an intriguing approach to analysing and facilitating CSCL. The concept of emerging roles provides a perspective on how learners structure and self-regulate their CSCL processes. Emerging roles appear to be dynamic over longer periods of time in relation to learners’ advancing knowledge, but are often unequally distributed in ad hoc CSCL settings, e.g. a learner being the ‘typist’ and another being the ‘thinker’. Empirical findings show that learners benefit from structuring or scripting CSCL. Scripts can specify roles and facilitate role rotation for learners to equally engage in relevant learning roles and activities. Scripted roles can, however, collide with emerging roles and therefore need to be carefully attuned to the advancing capabilities of the learners

Adaptive Genetic Algorithm for Crystal Structure Prediction

We present a genetic algorithm (GA) for structural search that combines the speed of structure exploration by classical potentials with the accuracy of density functional theory (DFT) calculations in an adaptive and iterative way. This strategy increases the efficiency of the DFT-based GA by several orders of magnitude. This gain allows considerable increase in size and complexity of systems that can be studied by first principles. The method's performance is illustrated by successful structure identifications of complex binary and ternary inter-metallic compounds with 36 and 54 atoms per cell, respectively. The discovery of a multi-TPa Mg-silicate phase with unit cell containing up to 56 atoms is also reported. Such phase is likely to be an essential component of terrestrial exoplanetary mantles.Comment: 14 pages, 4 figure

PeerPigeon: A Web Application to Support Generalised Peer Review

Peer Review (also known as Peer Assessment) is an important technique in learning, but can be difficult to support through e-learning due to the complexity and variety of peer review processes. In this paper we present PeerPigeon, a Web 2.0 style application that supports generalised Peer Review by using a canonical model of Peer Review based on a Peer Review Pattern consisting of Peer Review Cycles, each defined in terms of Peer Review Transforms. We also demonstrate how PeerPigeon makes use of a Domain Specific Language based on Ruby to define these plans, and thus cope with the irreducible complexity of the flow of documents around a peer network