Hi. I have spent many years in widening and opening up access to education and learning. That has shaped very much my interests in MOOCs. What I learned during that time is the power of “openness” and of “a negotiated curriculum’’ to engage people, from areas of social and economic deprivation, in learning that is relevant to their needs. That attitude is still with me. It has shaped my views of technology and how emerging technologies and MOOCs might help people in their learning.
New technologies make it possible to connect with other people and exchange information and create knowledge on an unprecedented scale; they facilitate the creation of an open knowledge commons. You will not be surprised after that I am interested in connectivist MOOCs and their development, rather than xMOOCs, commercial and institutionally based. I see many opportunities in cMOOCs as they represent a new pedagogical approach in the network age. cMOOCs focus on knowledge creation and generation. In cMOOCs, the learners take a role in shaping their learning experiences, while facilitators focus on fostering a space for learning connections to occur. When in a cMOOC, students are empowered to make their own learning decisions. This self-reliance is the basis for a re-emergence of the promising paradigms in (adult) educational practice of informal, autonomous learning, self-directed learning, and self-managed learning within personal learning environments.
I emphasise dialogue in learning as I believe, and that belief is based on research evidence and what great thinkers of the past say, that dialogue with other people is still what inspires and deepens the learning process. Freire for instance enmphasised the social in learning when discussing concienciazation of local people regarding power relations in their lives when teaching basic language skills. As adult educator I am very much aware of the transformative effect individual learning might have on the community in which learning takes place. Jezegou’s research, and she is a psychologist, emphasises what communicating with others do to the internal thinking process.
While Dewey goes as far as stating that communication with others is making us human beings to what we are as human beings. That is what I would like you to hold on to throughout this presentation.
At the heart of all of this is learning in dialogue. This dialogue might be face to face with people in a local context, or it might be synchronously or a synchronously online
Over the past years I have been trying to get clear for my self how people learn in a PLE and I’ve come up with the following model. At the centre is the “learner-in-dialogue” and some of you might recognise the Kolb learning cycle: the learner has an experience or problem that needs solving and needs information and some form of aggregation takes place. The person organises what has been collected, might share and collaborate with others, perhaps advice from a more knowledgeable other to reach understanding. She will reflect on it, perhaps find more information that is relevant, and links it to knowledge or experience the user already has and reach some level of understanding, that might even become clearer by writing about it, or producing a video about it and sending it and publishing it, which could invoke feedback. This would make the circle round as after reviewing what has been learnt, it might lead to new experiences or problems that require the circle to start all over again.
What does this mean then when moving from a class room environment to a MOOC, which might be based on open learning, such as in connectivist moocs, or group based as is xMOOC providers are still trying to facilitate. Education must address the technological way-of-being which is becoming dominant in everyday life. Part of this is the representation of things through abstract categories in order to make them manageable for efficient manipulation. There is extensive research evidence available, however, to show that the human should be kept in mind when designing and developing technologies. When talking about appropriate technologies I would like to refer to a blog post by George Siemens who earlier in the month highlighted five criteria of technology that would make them empowering for learners and reflective of a human in a creative-oriented future: Does the technology foster creativity and personal expression? Does the technology develop the learner and contribute to her formation as a person? Is the technology fun and engaging? Does the technology have the human teacher and/or peer learners at the centre? Does the technology consider the whole learner?
Education must address the technological way-of-being which is becoming dominant in everyday life. Part of this is the representation of things through abstract categories in order to make them manageable for efficient manipulation. There is extensive research evidence available, however, to show that human interaction, such as dialogue, communication, collaboration, do enhance our thought processes. If we move away from human interaction, what might replace it? Automated competency progress visualization - Information recommender systems – Learner support apps. based on activity and collaboration My question to you is: Should information and resources be validated by humans?
There are indications that it would be advantageous to learners if they are pro-active themselves in shaping their information stream (Ihanainen & Moravec, 2011). One of the challenges for learners in conducting a fruitful serendipitous investigation would be a change in search strategy from looking something up and relying on brokers and search engine algorithms to filter search results and &quot;push&quot; information towards them, to taking personal control and foster more randomness in the information stream by &quot;pulling&quot; information themselves. Ideally, people should find ways of incorporating web-searching into their thinking and reflection processes and integrate it into their own technological system that streams their information, and that is related to their own personal context; an unfiltered but manageable store of resources (Boyd, 2010).
To a certain extent human beings do edit search engine algorithms (Goldman, 2010), but an important component to a search result is trust in the information provider, and could people ever trust a machine, even though it is tweaked by humans, to find really useful information especially to advance their learning? In the past teachers would be trusted with the decision making over resources, or individuals might browse the library shelves to find what they needed themselves, but in the open networked environment in which people now learn, all that is changing. Learners use other resources than ones provided by educational institutions and instructors to support critical reflection and analysis. They also use information filters and commercial search engines, based on algorithms that make decisions about the information they receive on a daily basis. Search engines are very good at finding &quot;relevant&quot; information to a search, but not so good at information that is of a more capricious nature (Andre et al, 2009). They don&apos;t necessarily cater to advanced intellectual inquiry as their top search results merely reflect the general information needs of the population as a whole by bringing up relevant information based on key words. Google and Facebook algorithms provide us ‘with the information that they think we want to see, rather than all we can – and should. . . The way algorithms work means that the focus is on what we click on most often, rather than providing us with a “balanced information diet” that also includes things that are uncomfortable and challenging and that include other points of view’ (Zetter, 2011, p1.). What is hard to replicate in algorithm-driven searches, is serendipity; the chance of finding a gem of information, unrelated to a focused search, more as a by-product that stimulates creativity and thinking to arrive at a particular insight (Andre et al, 2009; Falconer, 2010).
Bouchard (2011) believes that this is not enough, and that for learning it would be desirable for information be filtered not only by learners themselves, but to also be validated by other human beings. Interaction with human beings is for most people at the heart of a quality learning experience and receiving information from friends, and friends of friends which might still be close in interest to the learner could enhance serendipity. Of course in the era of social media there are a myriad of opportunities to raise social presence and human interaction; one would even argue that the abundance of social networks and contacts makes choosing the right person to listen and talk to problematic. The challenge would be to manage this stream of communications effectively and to choose the best tools for human mediation to avoid being overwhelmed by the volume and dimensions. We carried out some exploratory research in serendipity in information streams on a Massive Open Online Course.
How might people receive feedback on their learning?
How can we create feedback loops in an open environment? 1. in enhancing serendipity after collecting massive amounts of discursive data. 2 to use an information aggregation filtering system based on people. This could be in the form of friends, or following people on Twitter 3. It could be by introducing mentors and have facilitators in the MOOC, or to create systems in which peers give feedback, which is of course challenging as it is difficult to scale in a MOOC 4. I agree with Stephen that diversity is important in this, but how would this diversity be created? Using filters of experts, such as Stephen with his OlDaily, to distribute information would be a start, but my data led me to believe that a more detailed look at the level and nature of communication and messaging in learning would be desirable to understand which factors would be important. In the research that Helene Forunier and I carried out on PLENK2010 we analysed data of using Twitter it made that people receive relevant information, but relevant with a twist, that is unexpected seemed to me to require a certain level of distance between the learner and the person supplying the information.
It is probably already clear to you that I value human involvement in learning. I also think it important that MOOCs contribute not only to learners own learning process and that of their peers during an open learning event, but also to the knowledge commons. The Web is a place where information is stored, in addition to a place where people come together and actively do something with this information and the available resources (perhaps to produce multimedia, share, remix, or build on information). It is not only access to information that is at stake but also public access to knowledge. According to Hess and Ostrom, this situation requires “a new way of looking at knowledge as a shared resource, a complex ecosystem that is a commons —a resource shared by a group of people that is subject to social dilemmas” (Hess & Ostrom, 2006, p. 3). For this to occur, MOOCs should be open and make available all resources. Moreover, learners’ active involvement in knowledge production, and in creating and contributing to knowledge, should be fostered. This viewpoint requires a pedagogical model that is not just based on traditional transfer of knowledge, but that involves active participation in the learning process, through which learners produce something of relevance. It involves communication with (knowledgeable) others to advance their learning as well as guidance on how to contribute to the knowledge commons. It is toward such ends that I advocate promoting a sharing across any and all learning environments.
Rita Kop Naples Capri September 2015 MOOC Federica
The human element in learning:
Dialogue, Ethics, Openness and
Control in MOOCs
Rita Kop, Yorkville University,
Fredericton, NB, Canada
Future of MOOCs conference,
Naples and Capri, September 2015
Paolo Freire: ‘I engage in dialogue because I recognize the social and
not merely the individualistic character of the process of knowing.’
By communication with others our inner thoughts will become clear.
This collaboration is ‘nourished through exchanges, mutual
contributions, confrontations, and negotiations that provoke within
the person certain interrogations and stimulate new learning
through carrying out new activities’ (Jézégou, 2010, pg. 14).
‘Mind, consciousness, thinking, subjectivity, meaning, intelligence,
language, rationality, logic, inference and truth – all of these things
that philosophers over the centuries have considered to be a part of
the natural ‘make-up’ of human beings – only come into existence
through and as result of Communication’ (Dewey, 1958, as cited in
Model of open
Relevance for MOOCs
• Appropriate technologies being used?
• Engagement and motivation
• Effectiveness is not enough
• Learning is not the same as assimilation of
Alternatives to dialogue
what are we replacing human interaction with
and what is the value, what are the strengths
and weaknesses of the replacement to
education and learning?
•Automated competency progress visualization
•Information recommender systems
•Learner support apps. based on activity and collaboration
•Should information and resources be validated by humans?
what conditions should be created and
what environments designed to
support learners in managing and
controlling their own learning
Information and resource
‘Data analytics software works
from simplistic premises: that
problems are technical,
comprised of knowable,
measurable parameters, and
can be solved through
Complexities of ethics and
values, ambiguities and
tensions, culture and politics
and even the context in which
data is collected are not
accounted for’ (Fenwick, 2015,
Challenges with data-driven systems
Fenwick (2015) and Boyd & Crawford (2010):
•They change “everyday practice and responsibilities in
ways that may not be fully recognised” (p.71).
•A reliance on comparison and prediction “can be self-
reinforcing and reproductive, augmenting path
dependency and entrenching existing inequities”
•especially if the people producing the algorithms are not
aware of the reinforcement of stereotypes when use of
Big Data is not a combined effort between social and
• Who owns the data used in analytics?
• Who decides what can be done with collected
• Privacy and consent issues.
• Who is responsible when things go wrong?
Validation of information through
other human beings
The human factor
Level of communication
Degree of distance