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Meta‐design principles for open learning ecosystems
Kai Pata Tallinn University,
Ins;tute of Informa;cs Center for Educa;onal Technology
MUPPLE Lecture Series, 2011
An overview
• What is an eco‐cogni;ve view to learning? – The examples of open learning ecosystems in course design
– The learning niches and how to use them in learning design
– Why to use the meta‐design approach? – The meta‐design approach to open learning ecosystems
– Some developments and limita;ons for meta‐design from the soFware side
Open learning ecosystems
• Open learning ecosystem is an open, adap;ve complex and dynamic learning system in which self‐directed learners design their learning ac;vi;es and follow open educa;on principles by sharing freely over the internet knowledge, ideas, infrastructure and teaching methodology using Web 2.0 soFware.
Par;cle and system level views to open learning ecosystems
Learners in open learning ecosystems:
• Self‐direc;ng • Networking, PLEs, PLNs
• Communi;es of open educa;on
• Co‐designing and sharing
• Monitoring • Adap;ng • Naviga;ng
“Ecosystem” not as a metaphor
• Self‐regula;ve • “Connec;vist Networks” in open
learning ecosystems
• “Community” of digital cultures
• Open, Dynamic and Evolving
• Accumula;ng
• An evolu;onary feedback loop
Towards the learner‐centered approach
• Two pedagogical paradigms have been highlighted in open learning ecosystems.
• Firstly, the interpre;vist learning principles suggest that students should be: – guided towards becoming independent, autonomous and self‐directed learners)
– who learn from being ac;vely engaged in the situa;ons that are meaningful to them, from their interac;ons with peers and teachers in which they are given the voice so they that they can become co‐constructers of the learning environment
– and by reflec;ng on their prior knowledge and experiences to construct new meanings
An example course
ICamp interna;onal eLearning course (Pata & Merisalo, 2010)
Towards the learner‐centered approach
• Secondly, for cul;va;ng the “ecosystem” view in digital systems (see Pór & Molloy, 2000; Crabtree & Rodden, 2007; Boley & Chang, 2007), George Siemens (2006) formulated the Connec;vism framework as the new learning theory for open learning ecosystems.
• Connec;vism assumes that: – Learning is primarily a network‐forming process, and the dynamically appearing and changing networks form basis for the learning ecosystems
An example course
Ecology of narra;ves course (Pata & Fuksas, 2009 hap://padis2.uniroma1.it:81/ojs/index.php/cogphil/ar;cle/view/4338/4200
A gap in design principles for open learning ecosystems
• Without wishing to suppress down such a boaom‐up self‐emergence of eLearning designs, we should provide teachers in learning ins;tu;ons with design solu;ons that enable them to regain some co‐control in the learner‐ini@ated ac@vi@es and systems is needed (Fiedler and Pata, 2009).
A gap in design principles for open learning ecosystems
• The teachers’ need to control the learning design and learning process in distributed systems
• The necessity to allow freedom for learners to be self‐directed and using their own personal learning environments in higher educa;on courses
Offloading cogni;ve func;ons to the digital ecosystem
• Humans constantly delegate cogni@ve func@ons to the environment (Bardone, 2011)
An eco‐cogni;ve view to learning • Human cogni@on is chance‐seeking system that is developed within an evolu;onary framework based on the no;on of cogni@ve niche construc@on.
• We build and manipulate cogni@ve niches so as to unearth addi@onal resources for behavior control.
• Human cogni;ve behavior consists in ac@ng upon anchors – the affordances* (*see Gibson, 1977) ‐ which we have secured a cogni@ve func@on to via cogni;ve niche construc;on. (Bardone, 2011)
Distributed cogni;on and affordances as a cogni;ve niche
Schema adopted from Zhang, J., & Patel, V. L. (2006)
Learners’ goals and perceived ac;on poten;ali;es
Teachers’ goals and instruc;ons for ac;on
Learning environment as digital ecosystem
Previous ac;on experiences in this environment
A cogni;ve niche
Learning affordances and PLE • PLEs are dynamically evolving Ac@vity systems* (*see Engeström, 1987) in which the personal objec@ves and human and material resources are integrated in the course of ac;on.
• PLE is also distributed ecologically, integra@ng our minds with the environment (see Zhang & Patel, 2006; Bardone, 2011).
Different learning goals assume the percep;on of different affordances in PLE
Affordances as a networked system? • Affordances may
constrain each other • Synergy may be arrived
from using several affordances simultaneously
• Some affordances may need the presence or the co‐ac;va;on of other affordances to be used effec;vely
• Using one affordance may actualize another affordance in the network
Defining community niches by affordances
• People determine the personal learning affordances within their PLEs.
• Any individual conceptualizes affordances personally, but the range of similar learning affordance conceptualiza;ons visualizes community’s preferences – a community learning niche
Affordances in a community
The learning niches
• Adapta;on ‐ the adjustment of an organism to its environment in the process by which it enhances fitness to its niche
• The forma;on of learning niches in open learning ecosystems appears through accumula;ng learning affordances from PLEs (Pata, 2009).
• The community’s affordances may be interpreted and used by each learner to best adapt to the community niche for certain goal‐based ac;on
Kirschner et al. (2004)
Learner’s role is passive, design is created by the teacher.
Learning environment not dynamically evolving.
Earlier models that use affordances in learning design
Why meta‐design approach?
• The ecological Meta‐Design framework applies for open learning ecosystems that are adap;ve and dynamically changing.
• Meta‐design is designing the design process for cultures of par;cipa;on – crea;ng technical and social condi;ons for broad par;cipa;on in design ac;vi;es (Fisher et al., 2004).
• The meta‐design approach is directed to the forma;on and evolu;on of open learning ecosystems through the end‐user design.
Meta‐design approach
• The meta‐design approach is known as a methodology for collabora;ve co‐design of social, technical and economic infrastructures in interdisciplinary teams in order to achieve synergy similarly to the symbiosis phenomena in natural environments.
• The meta‐design, known from End User Design in computer science, extends the tradi;onal no;on of system development to include users in an ongoing process as co‐designers, not only at design ;me but throughout the en@re existence of the system (Fisher et al., 2004).
Meta‐design approaches
• Autonomous and self‐organized designers in meta‐design framework can increase the diversity of design solu;ons in the system, allowing diversity and variability to emerge within the ecosystem.
• The open, community‐driven, emergent and itera;ve ac;vity sequences in the learning design process models are based on learner contribu;on (Hagen & Robertson, 2009).
Meta‐design approaches
Hagen & Robertson (2009)
Ecological principles in meta‐design
• Learning in the cultures of par;cipa;on may be characterized as the process in which learner and the system (community, culture) detects and corrects errors in order to fit and be responsive (Fisher et al., 2004).
• In this defini;on, learning process is conceptualized as largely self‐organized, adap@ve and dynamic.
• It may be assumed that such learning follows the ecological principles
Some principles of meta‐design
• Both focuses – the learning ecosystem evolu@on by end‐user design, and nourishing the end‐user design process by crea;ng the scaffolds for designing (Fisher et al., 2004), are equally important aspects of ecological Meta‐Design.
The process view to meta‐design in open learning ecosystems (Pata, 2010)
Suitable
Learners’ role
• In learning ecosystems autonomous learners con;nuously develop and dynamically change design solu;ons to support their learning.
• They incorporate into their personal learning environments different Web 2.0 tools, networking partners and ar;facts, and monitor the state of the whole learning ecosystem to adapt their design solu;ons and learning objec;ves to the system and to other learners.
Teachers’ role • Providing the teacher‐created scaffolds and incen;ves for the learners' design ac;vi;es that would foster the accumula;on of learning niches: – a) monitor the evolu;on of the open learning ecosystem, – b) provide learners with the op;ons that enhance and speed up the self‐directed network‐forma;on process (e.g. tags, mashups),
– c) analyze the emerging affordances within the learning community, and provide analy;cal guidance for them aiding to make design decisions and selec;ng learning ac;vi;es (e.g. social naviga;on, seman;c naviga;on), and
– d) seed learning ac;vi;es into the open learning ecosystem that are based on self‐organiza;on (e.g. swarming).
The limita;ons for applying meta‐design in an open learning ecosystem • There is the need for dynamic accumula@on and monitoring systems for learning niche forma@on to be used by each learner for benefi;ng from par;cular open learning ecosystem and allowing them to par;cipate in the course design – accumulated affordances and their dissipa;on in ;me (community‘s learning niche)
– real‐;me awareness of affordances for other learners (their cogni;ve niches)
The tools to support meta‐design in open learning ecosystems (Pata, 2011)
Suitable
Learning contract tools (LeContract, Learning creator (Siadty et a.l, 2011),)
Monitoring tools (EduFeedr (Põldoja & Laanpere, 2009))
Connec;vity with PLE components (Dippler, Tallinn University development)
User monitoring, accumula;on and visualiza;on
Distributed course assembling tools (Dippler)
Kai Pata senior researcher,
Tallinn University, Ins;tute of Informa;cs, Center for Educa;onal Technology
kpata@tlu.ee, blog hap://;hane.wordpress.com
References • Bardone, E. (2011). Seeking Chances. From Biased Ra;onality to Distributed Cogni;on. Springer, Heidelberg. • Boley, H., & Chang, E. (2007). Digital Ecosystems: Principles and Seman;cs, published at the 2007 Inaugural IEEE Interna;onal Conference on
Digital Ecosystems and Technologies. Cairns, Australia. February 2007. NRC 48813. • Crabtree, A., & Rodden, T. (2007). Hybrid ecologies: understanding interac;on in emerging digital‐physical environments. Personal and Ubiquitous
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Steven Warburton (Eds.). Handbook of Research on Social SoFware and Developing Community Ontologies. (145 ‐ 158). Idea Group Reference. • Engeström, Y. (1987). Learning by Expanding: An Ac;vity‐Theore;cal Approach to Developmental Research (
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OF THE ACM September 2004/Vol. 47, No. 9 (33‐37 . • Gibson, J.J. (1977). The theory of affordances. In R. Shaw & J. Bransford (eds.), Perceiving, Ac;ng and Knowing. Hillsdale, NJ: Erlbaum. • Hagen, P. and Robertson, T. (2009
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• Siemens, G. (2006) Knowing knowledge. URL. hap://www.knowingknowledge.com/2006/10/knowing_knowledge_pdf_files.php • Zhang, J. & Patel, V.L. (2006). Distributed cogni;on, representa;on, and affordance. Distributed Cogni;on: Special issue of Pragma;cs & Cogni;on 14,
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