EFEPLE'11 1.

In the recent decade a plethora of interactive software tools, be they open source or proprietary, have emerged and perished in the realm of technology-enhanced learning (TEL). Concomitantly, there have also been surge and demise of contents, social networks, and activities associated with the use of these TEL tools. It is intriguing to understand what factors contribute to their rises and falls, and how. While controversies on the viability of making an analogy between the evolution of natural and artificial objects prevail, it is deemed worthwhile to explore its potential for analysing the changes in TEL and charting the future.

In accordance with evolutionary theory, the fitness of an environment or tool can be defined with respect to its purpose and depends on the 'genes' from former generations. In context of TEL, these genes can be understood as features of existing tools and functionality being reused from software libraries or developed over multiple lifecycles thus leading to new generations of software artefacts. Personal learning environments (PLEs) aggregate these functionalities to enable learners to connect to peers and shared artefacts along their learning activities. Consequently, the success of a PLE can be measured by its uptake and usage within different communities of practice, its perceived effectiveness and efficiency in supporting the attainment of learning goals, its application beyond pre-defined purposes, its distribution and outreach beyond single communities, and its evolution to new PLE generations through active developers. Moreover, data mining of so-called variables of evolvability (e.g., perceived pragmatic/learning and hedonic/fun value) will enable the derivation of specific guidelines for designing and developing PLEs. Such empirically grounded guidelines, supplementary to those for generic IT applications, are currently lacking and much desired.

Overall, the main aim of the workshop is to explore the fitness and evolvability of PLEs in order to identify and understand characteristics and mechanisms for successfully evolving PLEs.

In principle, for a software system to be sustainable, it needs to be able to adapt to the changing requirements [1] in terms of use contexts, user goals, organizational cultures and technological opportunities. Specifically, in the field of TEL, there has been a shift from the pioneer work on designing and implementing full-featured, organisationdriven learning management systems (LMSs) to the emerging trend of developing specialised tools, which then can be assembled by users to extend/create personal learning environments (PLEs, Attwell, 2007) [2]. Not least due to the Internet, users have access to a seemingly innumerable amount of content and software tools, which are useful and partially even necessary to achieve the learning goals driven by the demands of job tasks, higher, and further education, or even private activities.

In the context of PLEs, the selection of tools is at the discretion of individual users, their organisations and the communities of practice (CoP) where users engage in a variety of collaborative activities. It is observed that some software tools, after being used for a few typical tasks by a few people only, unexpectedly spread out within a CoP widely as well as wildly through good practice sharing, convincing peers of the benefits of these tools for particular lifelong learning activities. In a very short period of time such tools can become as must-have infrastructure for collaborative work (e.g. various Google services). These tools and the environments built on them are not only intensively used but are also modified and sustained by active developer communities. On the other hand, some tools are endangered to be rejected by endusers and to die out after a few successful cases of application, even though they have undergone several iterations of redesign. Apparently, these observations manifest the notions of descent with modification, heritable variation and selection, sensitivity to changing environmental or contextual requirements, and "control of and types of variability" (Nehaniv, 2003 [3]; Wernick et al. 2004 [4]) that characterize Darwinian evolution. In the context of PLEs, it is relevant to understand the processes leading to successful tool uses, create respective models and learn how to control respective processes to increase the efficiency and effectiveness of modern individual learning environments.

The assumption that changes in PLEs can be modelled by Darwinism underpins this proposed workshop, which aims to explore several pertinent issues:

• Nahaniv et al [5] (2006) define the notion of evolvability as "the capacity to vary robustly and adaptively over time or generations in digital and natural systems". This definition leads to a basic question: What is evolvable? Is it a matter of the complexity of a system that is quantifiable such as lines of codes, number of modules? Or is it more a matter of quality-in-use manifests in terms of user experience [6] (i.e. a non-functional requirement)?

Another key question: Why does a system evolve? It can be instigated by changes in a system's environment, user requirements, usage, implementation methodologies and technologies. Answers to these what and why questions can shed some light onto the question How to effectively and reliably evolve a system (Ciraci & van den Broek, 2006; footnote 3)? Addressing these questions in the context of PLEs will instigate stimulating discussions.

• Fitness for survival is a widely known but poorly understood concept of Darwinian evolution. Paradoxically, the idea of heritable variation and selection is necessary but not sufficient to explain inherent phenotypic expression of fitness (Nehaniv et al. 2006; footnote 5). It hinges on the rigidity (or flexibility) of the genotype-phenotype mappings. The main difficulties lie in drawing analogies between biological concepts and artificial artifacts (e.g. What constitutes an "individual", a "species", or "interbreeding"). Insights can be gained from the EFEPLE'11 notion of fit-for-purpose in the field of HCI (e.g. Wong et al., 2005) [7] and the fitness model of nodes in the science of (social) networks (Barabasi, 2002) [8]. Nonetheless, it remains an open question on how to define and measure the fitness of PLE tools 2.

There were 10 presentations, including a keynote speech.

In addition, plenary discussions on specific topics were held. Section 2.1 reports the main ideas addressed by individual presentations. Section 2.2 highlights the ideas explored by the workshop participants.

In this section, we highlight the ideas discussed in each of the presentations and present them in the form of notes that may inspire further thoughts along the related inquiries. These notes can serve as pointers to the tenets of the respective workshop papers. 4.

Evolutionary or Darwinist theories are inherently controversial; applying them to explain and predict the trajectory of the development of Personal Learning Environments (PLE) is particularly challenging. PLE is still at its infancy stage, and a consensual definition is still lacking. Amongst others, the task of defining fitness models for predicting the rise and demise of specific widgets (which are commonly seen as the building blocks of PLE) and a specific configuration of PLE per se is daunting. The workshop is seen as the first step moving in the direction, though there are still many steps to be taken to achieve this seemingly insurmountable task. The initial step is seen as successful with intriguing ideas being conceived. Future work includes organizing a series of related workshops/seminars that involve participants with diverse backgrounds. Project proposals addressing the emergent topics are seen as a promising way to explore them in depth over a relatively long period of time. In the meantime several meetings amongst the workshop participants have been held to explore these possibilities.