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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
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http://depositphotos.com/2956013/stock-photo-the-open-lock.html
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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).
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‘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 Biesta).
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Learner in dialogue
• Social interaction
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Model of open online learning
Reflecting
Understanding
ReviewingAggregating
Aggregating
Feeling
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Relevance for MOOCs
• Scalability• Appropriate technologies being used?• Engagement and motivation• Effectiveness is not enough• Learning is not the same as assimilation of
information
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Alternatives to dialoguewhat 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?
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what conditions should be created and what environments designed to
support learners in managing and controlling their own learning
activities?
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Information and resource aggregation
Moving from:
Rita Kop
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Rita Kop
Recommender systems
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‘Data analytics software works from simplistic premises: that
problems are technical, comprised of knowable,
measurable parameters, and can be solved through technical calculation.
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,
p.70).
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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 computer scientists.
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Ethical issues
• Who owns the data used in analytics?
• Who decides what can be done with collected data?
• Privacy and consent issues.
• Who is responsible when things go wrong?
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Rita Kophttp://davidwarlick.com/colearners/?p=73
and
Validation of information through other human beings
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Rita Kop
The human factor and serendipity
Level of communicationDiversityDegree of distance
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Rita Kopritakop.com [email protected]://yorkvilleu.academia.edu/RitaKop