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

http://depositphotos.com/2956013/stock-photo-the-open-lock.html

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 Biesta).

Learner in dialogue

• Social interaction

Model of open online learning

Reflecting

Understanding

ReviewingAggregating

Aggregating

Feeling

Relevance for MOOCs

• Scalability• Appropriate technologies being used?• Engagement and motivation• Effectiveness is not enough• Learning is not the same as assimilation of

information

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?

what conditions should be created and what environments designed to

support learners in managing and controlling their own learning

activities?

Information and resource aggregation

Moving from:

Rita Kop

Rita Kop

Recommender systems

‘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).

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.

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?

Rita Kophttp://davidwarlick.com/colearners/?p=73

and

Validation of information through other human beings

Rita Kop

The human factor and serendipity

Level of communicationDiversityDegree of distance

Rita Kopritakop.com rkop@yorkvilleu.cahttps://yorkvilleu.academia.edu/RitaKop