Complex learning communities

A new breed of learning community which is driven by the need to generate learning, creativity and economic capacity is emerging as a result of the demands of the Information Society. Radical heterogeneity and multiple drivers make these learning communities significantly different from previously identified learning communities such as corporate Communities of Practice or Virtual Learning Communities. If full benefit is to be realised from such Complex Learning Communities (CLCs), then better understanding of their complex behaviour and methods of maximising their effectiveness are required. This short paper presents an overview of CLCs and reports on the development of a research agenda designed to address the identified gaps in knowledge

The assessment of complex learning outcomes

The Engineering Professors' Council (EPC) produced an output standard in 2000 containing a setof 26 generic statements of what an engineering graduate should have an ability to tackle. In addition, Higher Education (HE) is concerned with the promotion of complex or advanced understanding of subject matter. This leads to complex learning outcomes, which need to be adequately assessed. Changing demands mean changing assessment practices. While good practice is being used in many cases, there is a need to ensure assessment stimulates complex learning. The article seeks to address these issues

Emergent characteristics of complex learning communities

In response to the rapidly changing demands of the Information Society, learning has undergone radical change, becoming a true lifelong activity with emphasis on situated, communal learning and flexible delivery designed to meet individual learning styles and increasingly underpinned by technology

Community space in complex learning communities : lessons learnt

Highly complex learning communities where diverse participants collaborate to achieve multiple aims through synergy have the potential to be highly creative and productive. However the diversity and multiple aims can also mean the advantages of a community - share understand, trust and direction - are difficult to achieve, resulting in few if any of the aims being realised. We review two case studies, where the learning community is trying to achieve multiple aims, in order to explore how virtual and physical space are employed to support collaborative learning and enhance synergistic potential. The analysis shows that high levels of diversity have influenced these spaces and trends towards differentiation and holistically designed hybrid, virtual and physical, collaboration space. The characteristics of theses cases are sufficiently general to lead us to draw insights for the building of collaborative space in multi-purpose complex learning communities. These are equably applicable to learning communities which share features such as heterogeneity, multiple locations or a mixture of spaces

A framework to study learning in a complex learning environment

This paper presents a framework for analysing variations in the ways in which students experience learning in complex, computer-supported environments. It involves an application of phenomenography extended to encompass the content of the learning as well as its context. Concepts from activity theory are drawn upon to enlarge the scope of phenomenography. By applying this framework, researchers, as well as course organisers, may gain insights into how courses are experienced by the participants and can thus develop these in a way that will be perceived as improvement by the course participants. Within this predominantly phenomenographic approach, the focus is upon the content of the learning experience, giving the ability to relate learning outcomes to the experience of the learning environment. Hence, insights can be gained that can help to improve learning environments and thereby outcomes. A case study illustrating the kinds of results than can be obtained when using the framework is provided

Interactions between the hippocampus, prefrontal cortex, and amygdala support complex learning and memory.

One of the guiding principles of memory research in the preceding decades is multiple memory systems theory, which links specific task demands to specific anatomical structures and circuits that are thought to act orthogonally with respect to each other. We argue that this view does not capture the nature of learning and memory when any degree of complexity is introduced. In most situations, memory requires interactions between these circuits and they can act in a facilitative manner to generate adaptive behavior

Exploring Complex Learning Spaces

This project focuses on developing an understanding of the complexity of learning spaces which are inhabited by students in higher education institutions. Developing work already carried out by the project leaders on experimental learning spaces within the university, this is a project which aims to gain a better understanding of the ‘learning lives’ of students beyond the formal learning spaces such as the lecture theatre, laboratory and seminar room. Using a mixed methods approach focusing on survey and photo-ethnographic methods data will be developed from the general to the particular to investigate the other spaces which students use to develop their learning. These spaces include both physical and virtual spaces, as well as on and off campus spaces, including cafes, libraries, study bedrooms as well as virtual learning environments and social networking/Web 2.0 technologies. This research intends to consider the complex interplay of these different spaces in the learning of students and also how they relate to the formal spaces of which we have a clearer understanding. This project will therefore aid academics in better understanding the dynamics of the learning ecologies which underpin the experiences of students within the university

Fostering complex learning-task performance through scripting student use of computer supported representational tools

This study investigated whether scripting student use of computer supported representational tools fostered students’ collaborative performance of a complex business-economics problem. Scripting the problem-solving process sequenced and made its phase-related part-task demands explicit, namely (1) determining core concepts, (2) proposing multiple solutions, and (3) coming to a final solution. The representational tools facilitated students in constructing specific representations of the domain (i.e., conceptual, causal, or mathematical) and were each suited for carrying out the part-task demands of a specific phase. Student groups in four experimental conditions had to carry out all part-tasks in a predefined order, but differed in the representational tool(s) they received during their collaborative problem-solving process. In three mismatch conditions, student groups received either a conceptual, causal, or simulation representational tool which supported them in only carrying out one of the three part-tasks. In the match condition, student groups received the three representational tools in the specified order, each matching the part-task demands of a specific problem phase. The results revealed that student groups in the match condition constructed more task-appropriate representations and had more elaborated and meaningful discussions about the domain. As a consequence, those student groups performed better on the complex learning-task. However, similar results were obtained by student groups who only received a representational tool for constructing causal representations for all part-tasks