1st Workshop on Exploring the Fitness and Evolvability of Personal Learning Environments (EFEPLE’11) 2nd STELLAR Alpine Rendez‐Vous (ARV), the French Alps, 30-31 March, 2011 Co-chairs Effie L-C. Law1, Felix Mödritscher2, Martin Wolpers3, Denis Gillet4 1 University of Leicester, UK 2 Vienna University of Economics and Business, Austria 3 Fraunhofer FIT, Germany 4 EPFL, Switzerland Participants (in alphabetic order): Sandy El Helou, EPFL, Switzerland Carlo Giovannella, University of Rome Tor Vergata, Italy Martin Memmel, DFKI, Germany Maryam Najafian-Razavi, EPFL, Switzerland Christopher Nehaniv, University of Hertforshire, UK (Keynote speaker) Christian Prause, Fraunhofer FIT, Germany Jose L. Santos, Katholieke Universiteit Leuven, Belgum Benham Taraghi, TU Graz, Austria Fridolin Wild, Open University, UK Special thanks to H. L. Cornish, the Graphic Designer of Open University UK, for the aesthetically pleasing cover of the proceedings i EFEPLE’11 1. INTRODUCTION In the context of PLEs, the selection of tools is at the 1.1 Motivation discretion of individual users, their organisations and the In the recent decade a plethora of interactive software communities of practice (CoP) where users engage in a tools, be they open source or proprietary, have emerged variety of collaborative activities. It is observed that some and perished in the realm of technology‐enhanced learning software tools, after being used for a few typical tasks by a (TEL). Concomitantly, there have also been surge and few people only, unexpectedly spread out within a CoP demise of contents, social networks, and activities widely as well as wildly through good practice sharing, associated with the use of these TEL tools. It is intriguing convincing peers of the benefits of these tools for to understand what factors contribute to their rises and particular lifelong learning activities. In a very short falls, and how. While controversies on the viability of period of time such tools can become as must-have making an analogy between the evolution of natural and infrastructure for collaborative work (e.g. various Google artificial objects prevail, it is deemed worthwhile to services). These tools and the environments built on them explore its potential for analysing the changes in TEL and are not only intensively used but are also modified and charting the future. sustained by active developer communities. On the other hand, some tools are endangered to be rejected by end- In accordance with evolutionary theory, the fitness of an users and to die out after a few successful cases of environment or tool can be defined with respect to its application, even though they have undergone several purpose and depends on the ‘genes’ from former iterations of redesign. Apparently, these observations generations. In context of TEL, these genes can be manifest the notions of descent with modification, understood as features of existing tools and functionality heritable variation and selection, sensitivity to changing being reused from software libraries or developed over environmental or contextual requirements, and “control of multiple lifecycles thus leading to new generations of and types of variability” (Nehaniv, 2003 [3]; Wernick et software artefacts. Personal learning environments (PLEs) al. 2004 [4]) that characterize Darwinian evolution. In the aggregate these functionalities to enable learners to context of PLEs, it is relevant to understand the processes connect to peers and shared artefacts along their learning leading to successful tool uses, create respective models activities. Consequently, the success of a PLE can be and learn how to control respective processes to increase measured by its uptake and usage within different the efficiency and effectiveness of modern individual communities of practice, its perceived effectiveness and learning environments. efficiency in supporting the attainment of learning goals, its application beyond pre‐defined purposes, its The assumption that changes in PLEs can be modelled by distribution and outreach beyond single communities, and Darwinism underpins this proposed workshop, which aims its evolution to new PLE generations through active to explore several pertinent issues: developers. Moreover, data mining of so‐called variables • Nahaniv et al [5] (2006) define the notion of of evolvability (e.g., perceived pragmatic/learning and evolvability as “the capacity to vary robustly and hedonic/fun value) will enable the derivation of specific adaptively over time or generations in digital and guidelines for designing and developing PLEs. Such natural systems”. This definition leads to a basic empirically grounded guidelines, supplementary to those question: What is evolvable? Is it a matter of the for generic IT applications, are currently lacking and much complexity of a system that is quantifiable such as desired. lines of codes, number of modules? Or is it more a Overall, the main aim of the workshop is to explore the matter of quality-in-use manifests in terms of user fitness and evolvability of PLEs in order to identify and experience [6] (i.e. a non-functional requirement)? understand characteristics and mechanisms for Another key question: Why does a system evolve? It successfully evolving PLEs. can be instigated by changes in a system’s environment, user requirements, usage, 1.2 Related Work implementation methodologies and technologies. In principle, for a software system to be sustainable, it Answers to these what and why questions can shed needs to be able to adapt to the changing requirements [1] some light onto the question How to effectively and in terms of use contexts, user goals, organizational cultures reliably evolve a system (Ciraci & van den Broek, and technological opportunities. Specifically, in the field 2006; footnote 3)? Addressing these questions in the of TEL, there has been a shift from the pioneer work on context of PLEs will instigate stimulating discussions. designing and implementing full-featured, organisation- • Fitness for survival is a widely known but poorly driven learning management systems (LMSs) to the understood concept of Darwinian evolution. emerging trend of developing specialised tools, which then Paradoxically, the idea of heritable variation and can be assembled by users to extend/create personal selection is necessary but not sufficient to explain learning environments (PLEs, Attwell, 2007) [2]. Not least inherent phenotypic expression of fitness (Nehaniv et due to the Internet, users have access to a seemingly al. 2006; footnote 5). It hinges on the rigidity (or innumerable amount of content and software tools, which flexibility) of the genotype-phenotype mappings. The are useful and partially even necessary to achieve the main difficulties lie in drawing analogies between learning goals driven by the demands of job tasks, higher, biological concepts and artificial artifacts (e.g. What and further education, or even private activities. constitutes an “individual”, a “species”, or “interbreeding”). Insights can be gained from the ii EFEPLE’11 notion of fit-for-purpose in the field of HCI (e.g. changing requirements; lineage, different fitness Wong et al., 2005) [7] and the fitness model of nodes between offspring and parents in the science of (social) networks (Barabasi, 2002) o Properties of evolvable systems: robustness to [8]. Nonetheless, it remains an open question on how genetic variability, phenotypic robustness, to define and measure the fitness of PLE tools redundancy, conservation of core mechanisms/features; robustness to environment 2. WORKSHOP DESCRIPTION change (resilience), self-monitoring, There were 10 presentations, including a keynote speech. compartmentalization (modularity), In addition, plenary discussions on specific topics were symbiogenesis held. Section 2.1 reports the main ideas addressed by o Software evolution: re-use, modularity, individual presentations. Section 2.2 highlights the ideas information hiding, encapsulation, OO explored by the workshop participants. inheritance, coupling and cohesion; o PLE: system as fielded (instance: individual) o Persist over time, descent with modification 2.1 Report on Presentations o Lines of code, modules can be considered as In this section, we highlight the ideas discussed in each of genes (re-usable) the presentations and present them in the form of notes o Variation: customization of generic software that may inspire further thoughts along the related product via parameterization, copying and inquiries. These notes can serve as pointers to the tenets sharing of the respective workshop papers. o Iteratively adapted by users to context and changing requirements; 2.1.1 Keynote by Prof. Chrystopher Nehaniv o Immediate fitness is very different from capacity o Core concepts addressed: individual, to support possible evolvability; reproduction, population, robustness, variability, o Variational capacity (vary/be varied robustly and phenotypic plasticity, autopoiesis, self-replication adaptively) is crucial to evolvability and repair, and evolvability o The notion ‘replicating individual’ is difficult to 2.1.2 Discussion on the Keynote define in the realm of software evolution – Is it a Notion of energy/resources in the context of software; behaviour, an artifact or software release? o Areas of tension: o Self-replication is a key notion in evolution (cf. - immediate fitness vs. variability computer viruses, cancer cells, self-reproducing - simplicity: usability vs. complexity automata); replicators entail external support; - genotype (design: functionality) vs. o Constraints of evolution: finite resources, phenotype (affordances: practices) heredity, variability, differing reproductive o Complexity: base is interaction, energy comes success, turn-over of generations; from interaction, non predictable o Increasing complexity through successive o Consciousness/Intentionality (or awareness): inheritable mutation; a measure of complexity in comes from interaction, collaboration biological sciences can be number of cell types o Is evolvability kind of higher level creativity and in software can be level of embeddedness, o Success: performance improvement of learners; lines of code, number of loops, etc.Adaptive “form follows failures” changes in population over generations o Complexity: maximise contact with environment (genotype-phenotype map) subject to being able to understand and o Artificial selection vs. natural selection; manipulate: complexity needs to be close to o Variability: neutral mutation (no harm, no contact benefit) is important: similar fitness in the same o Educational technology so far has failed: because environment; mutation that is neutral in such an there are no solutions of scale (past: LMS have environment is beneficial as a resource; been successful, but not ‘real’ learning support o Neutral mutation such as user interfaces – a tools) variety of choice for selection; o Capacity for variability: Learning is development o Fitness landscape: inheritable fitness to flourish of potential for action: competence, but we can o Open-ended evolution is unbounded increase of only assess performance complexity over time; o Capacity relates to complexity through adaptation o External fitness function imposed on agriculture through exchange of modules and over time! (can we learn from this domain?); number of o Freedom of adaptation vs. ethical concerns offspring and living long enough to reproduce experimenting with bad combinations of software (fitness measures); o Sharing of successful practices/arrangements/etc. o Symbiogenesis: dynamic user-synthesis of PLE is hereditary replicability from components; combinations from the lower o Problem: It’s not the PLEs surviving and being level units; fit, it’s the widgets o Evolvability for artefacts: capacity for producers o Problem: PLE: Livespan of generations is not to rise to adaptive variants for flexibly meeting controlled iii EFEPLE’11 o But: Behaviour vs. artefacts: patterns of practices o Use traces of user activity to observe evolution vs. widgets o Arrival of facebook changed the use of the o Behaviour: duplication and divergence; behaviour system patterns can be very far away from genetics; o New journal: Interaction Design & Architecture active copying vs. environment driven auto discovery 2.1.5 Presentation by Felix Moedritscher o Controlling of behaviour: we can (to a part) o Environment: socio-technical system: activities, control the environment to recreate ‘situations’ purposes, patterns, interaction, features, o Translation of behaviour (phenotype) into functionality, implementation genotype? No convergence in other areas. o Evolvability: versioning, copying/reusing, o Would be helpful to very clearly define concepts interoperability such as genotype, phenotype in the PLE context o Fitness: usefulness & usability, user feedback, o Groundbreaking works in e.g. evolutionary technological compliance algorithms: e.g. von Neumann: theory about live; o Distribution approximation e.g. evolutionary algos: were designed as o Fitness depends on the usage context (e.g. optimisation techniques (example: designing publication impact) nozzles, aircraft wings) o Impact of papers very strongly relates on experience of the researcher (years of experience 2.1.3 Presentation by Benham Taraghi in a field). What about production of widgets? o Success measurement: Are widgets produced by more experienced users - Complexity: number of widgets in an more successful? environment - Change: rate of change: number of 2.1.6 Presentation by Martin Memmel replacements, new widgets o Sustainability - Number of users o Interoperability: using and offering APIs, o Selection types: stabilising selection, disruptive following standards selection, directed selection o Number of application scenarios: very many o Selection strategies: r-strategy (short livespan, application scenarios for PLEs unknown environments) vs. K-strategy (long o Low technical and low conceptual barriers to livespan, known environments) system use o Mutation: slight variation of existing o Resources are finite: people, time, infrastructure, functionality or UI money o Recombination: combining code of different o Repurposing and re-theming/branding of systems widgets to build new ones: code sex o Solve a specific problem, but do it in a generic o Tracking of use: frequency of activated widgets, way frequency of interactions with widgets that can be o Support tools for setup and deployment tracked in the system o Refactor o TUG system: 1000 users, 30% active users o Fitness is plasticity with respect to user o Competition not between widgets, but between requirements PLE system and competing websites o Code complexity of the PLEs: PLE as a whole (of one user) or widgets? How did it change over 2.1.7 Presentation by Sandy El Helou time? Lines of code? Level of embeddedness? o Viability: Modularisation? Interwidget communcation? - flexible representation of interaction and Service orientation? contents o Affordances (= in a certain cultural context)? - adopt social media paradigms o Other factors (besides fitness): usability, (encouraging participation) usefulness (e.g. indirect via level of the learners)? - elastic community and CMS services o Need to look at overall PLE system, not only at - automate/openness: recommender single widget; still: number of contexts, number systems: open corpus environments of functions, number of other widgets it has been o Use of Graaasp used with (degree centrality, betweenness, o Flexible representation: not necessarily dependant prestige): indicator of complexity on number of users o Symbiotic relations: themingWidget: cannot exist on its own 2.1.8 Presentation by Jose L. Santos o Coevolution of development and users o CAM dashboard o Activity – actions executed in widgets 2.1.4 Presentation by Carlo Giovanella o Capturing communcation data from interwidget communication o Evolution: strong focus on learning analytics: e.g. o Specialisation to styles? activity graphs, emotions, social networks, o Active use of the dashboard to change behaviour? emotion in social networks o Evolution: Awareness > Social Behaviour > … iv EFEPLE’11 o How to support awareness between developer and user? 2.2.2 Teachers as Target Groups o Representation of context to make use of the o Find a way to prove to the teacher that activity monitoring relying on a specific technology will help o Fitness: take care of environment them be more effective o Visual quality o Tackle danger for teachers: environments o Trust relationship between developers and user disappear: but environments change with their needs 2.1.9 Presentation by Fridolin Wild o How to sell technology to the teachers? o Acceptance: expectancies, social influence, o Show that with the help of any technology, facilitating conditions etc. the learners in the classroom/course became o Longer term 10% better: works only with criterion- referenced testing (no norm referenced 2.1.10 Presentation by Christian Prause testing): skills assessment: increase by 10% o “Walking on water and developing software from o Emergence of new widgets coming from the a specification are easy if both are frozen.” teacher and learner community (Edward V. Berard) o Living community: Increased sharing of best o high costs of change lead to extinction practices: 1 million teachers / million learner o evolvablity: internal quality using a PLE; There are enough teachers in o software quality: ISO 9126: functionality, Europe reliability, usability, efficiency, maintainability, o Digital literacy of teachers is a problem portability o Technology is seen as an amplifier o developers learn software: documentation! Code! o Combine agents and human tutors to provide o Fitness = external quality + quality in use = Tool high quality tutoring to every child in environment in its context o Case-based tools 2.2.3 Invisible PLE o very low entry barrier 2.1.11 Presentation by Maryam Najafian-Razavi o Sharing a curriculum in 15 minutes o Barriers to adoption (of gleanr) o No good idea: it is rather about - Lack of simplicity reconfiguration, not sharing: more about the - Slow ROI: differed benefit adoption than that it is fast - Need for training o Extremely complex issue - Usability problems: memorability, error o Widgets: 1000 widgets: which one is better rate, portability and how do we measure that? Through the - Success factors: clear value prop, community awareness, ease of integration o Testing: could include teacher has to be able - Interesting: big and fluid sites show up to re-use a PLE in 15 minutes; but: it’s not earlier in google about time, it’s about the return on - Suggestions: anonymity, prepopulation, investment network effects o Identifying the scores that someone gets o Success factors: could be fitness factors based on the traces that someone leaves in o Fitness leads to adoption the system o Prepopulation: problematic and difficult o Pedagogically sound user interfaces o Prepopulating vs. survival? o Ecosystem: has to be created, needs a context 2.2.4 Predictive Modelling o Predictive models: Predicting performance based 2.2 Report on Plenary Discussions on traces o Testing of predictive models in competitions: 2.2.1 Contextual Issues accuracy vs. satisfaction o Flexibilisation of technology support for any kind o Learning analytics: graphical user interfaces that of educational process foster quick understanding of performance and o Culture of certification: assessment and aesthetic display, streaming feedback accreditation; o Learning analytics, traces, context capturing; o Fitness: Integration of environments: mobile, Privacy-ensured, anonymised; Streaming analysis web, all o Open requirements elicitation: Implicit o Fitness of users: critical design skills, measure requirement modelling, helpdesk monitoring, experience / styles Implementation competitions in the bartering o Context: capture context of learners holistically, platforms for software development make this context description available to sound applications; o Plasticity: Support change in pedagogical approaches v EFEPLE’11 3. EMERGING RESEARCH the direction, though there are still many steps to be taken QUESTIONS to achieve this seemingly insurmountable task. The initial step is seen as successful with intriguing ideas being • Find a way to prove to the teacher that relying on a conceived. Future work includes organizing a series of specific technology will help them be more effective related workshops/seminars that involve participants with o The million practices & million teacher diverse backgrounds. Project proposals addressing the challenge: ad hoc formation of large scale emergent topics are seen as a promising way to explore learning networks: Reach a certain level of them in depth over a relatively long period of time. In the scale in variability and build capacity for meantime several meetings amongst the workshop variablity of practices of technology use in participants have been held to explore these possibilities. learning and teaching. o This includes: sharing of context information such as attention meta data, interoperability, ACKNOWLEGEMENTS practice capturing and sharing facilities such We are obliged to the two EU FP7 projects on technology- as scripts or learning designs or activity enhanced learning: ROLE (http://www.role-project.eu/) streams and STELLAR (http://www.stellarnet.eu/) for enabling the o This is not about showing that a certain realisation of this stimulating workshop. We would also template is used by a million people, but that like to express our appreciation of the organisers of the 2nd 1 million people have differing, adapted to Alpine Rendez‐Vous (ARV) 2011 whose efforts have their needs practices in technology support make the event enjoyable and successful. Last but not o Ad hoc formation of large scale learning least, thanks should go to authors of the workshop papers. networks • Fitness of learning environments is plasticity with REFERENCES respect to user requirements: [1] Ciraci, S. and van den Broek, P. M. (2006) o Variation: Adaptation or mutation: Evolvability as a Quality Attribute of Software construction set widget-based PLE, coding Architectures. In: The International ERCIM according to changing user requirements, Workshop on Software Evolution 2006, 6-7 Apr 2006, mash-ups LIFL et l’INRIA, Universite des Sciences et o Speed of change: Technologies de Lille, France, pp. 29–31.  Evidence that a trajectory is [2] Attwell, G. (2007). Personal learning environments: followed that a system has been The future of eLearning, eLearning Papers, January adapted: evidence of plasticity 2007, 2(1), www.elearningpapers.eu. ISSN 1887-  Knowledge management for 1542 teachers [3] Nehaniv, C. (2003). Evolvability, Biosystems: Journal  Dissolving of communities of of Biological and Information Processing Systems, practices: problem solved, 69(2-3), 77-81. community dissolved [4] Wernick, P., Hall, T., Nehaniv, C. (2006). Software • Invisible PLE evolutionary dynamics modeled as the activity of an o Low entry barriers actor-network. Proceedings of 2nd Intl. Workshop on o Flexibility with respect to pedagogical and Software Evolvability. IEEE computer society press. andragogical approaches [5] Nehaniv, C., Hewitt, H., Christianson, B., & Wernick, o fitness of widgets: create an open market for P. (2006). What software evolution and biological widgets; then we can use the market evolution don’t have in common. In Proc. Of 2nd Int’l mechanisms; show that there are widgets IEEE Workshop on Software Evolvability (SE’06). from each of the European countries; [6] Law, E. L-C. & van Schaik, P. (2010). 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Amongst others, the task of defining fitness Amateurs and Professionals in Berkeley's Museum of models for predicting the rise and demise of specific Vertebrate Zoology, 1907-39". Social Studies of widgets (which are commonly seen as the building blocks Science 19 (4): 387–420. of PLE) and a specific configuration of PLE per se is doi:10.1177/030631289019003001. daunting. The workshop is seen as the first step moving in vi