Aims and Scope
The Workshop in Multiagent System Based Learning Environments (MASLE) intends to highlight the increasing impact of the Multiagent Systems (MAS) paradigm in educational learning environments in recent years.
MAS technologies have been used in different educational applications such as Intelligent Tutoring Systems (ITS), Interactive Learning Systems (ILS) and Intelligent Learning Environments (ILE) [Giraffa & Viccari, 1998; Gürer, 1998; Sklar & Richards, 2006; Viccari & Gluz, 2007]. The research focus of these field has been on improving interactivity among human and no human agents, ascribing different roles to agents (as in a classroom environment), promoting dialogue across different actors in learning environments [Self, 1992; Flores et al., 2005; Gluz et al., 2006], exploring possible ways to extract information from the application environment, such as, students' capabilities and needs [Kim & Baylor, 2007)], and finally, fostering student interactivity and building software environments in which students share their knowledge with synthetic agents, acquiring meta-cognitive abilities [Aleven et. al., 2006] . Automatic assessment is also an area in expansion where the use of data-mining techniques provide feedback from students' misconceptions and improve their results in on-line tests [Icke & Sklar, 2008].
Several new developments in Intelligent Learning Environments systems have made clear their proximity to research issues in the field of agent and multi-agent systems. Challenges around new teaching and learning environments imply two important aspects. Firstly, these systems must acquire more autonomy, and must show a skillful behaviour, which means they have to assume roles and learn how to behave in a social environment. Secondly, they must have a comprehensive understanding of the students or teacher using the system, which means having an internal representation of their beliefs and goals [Giraffa & Viccari, 1998] . Those aspects taken together put ITS research clearly in the field of agent and multi-agent systems. Moreover, interdisciplinary work across different fields has always been present in ITS research. Animated characters would provide an example of one such field (a research issue since the initial steps in Agent technology [Paiva & Machado, 1999; Rickel & Johnson, 1998; Lester at al., 1999; Saksiri et al., 2006]), leading to applications which marry entertainment with educational purposes ('edutainment'), making possible the symbiosis of things like emotional expression to create empathy with cognitive reasoning to answer 'intelligently' during agent vs. human interaction [Jaques & Viccari, 2007]
Clarifying the relationship between multi-agent systems and educational applications also improves the discussion around the background technical issues with respect to agent specific modelling languages, formal languages and agent interaction [Dillenbourg & Self, 1992; Self 1994; Mûra et al., 1998; Gluz et al., 2006].
Finally the focus on empirical research supported by the specific methodologies used in Intelligent Learning Environments, such as testing and results validation, can contribute to the discussion about testing and validating technology methodologies applied to MAS and related fields [Vicari & Gluz, 2007].
This workshop will be intended for all researchers dealing with MAS cognitive architectures for Intelligent Learning Environments, simulation (school management, class interaction), MAS social interaction (peer, collaborative and cooperative), agent-agent and human-agent interaction, interaction between peers, argumentation, Artificial Assistant and also Pedagogical agents.