Big Data, Adaptive Learning and the Assumptions behind Part 1

This post on adaptive learning and big data sounds interesting. Thanks to Stephen Downes for the reference.

What are the significance of big data?

What is adaptive learning?

What are the assumptions behind the relationship between big data and adaptive learning?

Here is my previous post relating MOOC to adaptive system.

Before I could address the three questions above, here is my comment to my previous post:

What questions of learning would lead to a particular learning theory? If you ask me a question of learning based on behavior learning theory, surely I could gather evidences which could match your questions.
Similarly, if you ask me if instructivist approach is best for teaching, like those in xMOOCs, I could show you all the great, positive and praising and thankful responses from the learners on the professors, and course content, and the high distinctions result of the students, as evidence of great pedagogy of mastery learning, and the cognitivism/behaviorism play a major role in the whole notion of learning. Experiments and empirical researches surely have demonstrated these under classroom environments.
Would these be equally true and effective in virtual learning environment? If we are to use the assessment results like an improvement and grades or scores as evidence of learning achievement, we may likely end up with the theory that cognitivism relates to learning most directly, as the intellectual capability of a person is demonstrated through the achievement of results in test, examination or assignment. These seem certainly be the case, under a formal education system.
However, how about the social aspects of learning? Could we assume that a highly intelligent person (who is tested with high IQ or highest achiever) be socially capable in connecting with others in classroom, workplace or community? What assumptions have we made in judging the correlations between individual intellectualism and social skills and social intelligence? Would we be able to easily delineate the relationships between all these various parameters and factors? You could quote examples in real life indicating that many highly intellectual scholars won’t socialize, and these included Issac Newton, Albert Einstein, etc, but that they were highly successful in their academic achievement, and should be role models for many learners. Did this prove anything about personal learning or social learning as explained under learning theories? Again, this depends on what assumptions you have made, and what questions that you are asking in your scientific research, or inquiry in learning.

If you ask me if connectivist approach is best for learning under a complex learning environment, I could show you social network analysis, and how the 4 properties of openness, diversity, autonomy, interactivity and connectivity lead to better networked learning, under Connectivism.

In summary, it is not what I want it to be that would lead Connectivism to become a learning theory. It is what you could demonstrate and theorise that would lead one to “believe” in certain validity and reliability of a learning theory such as Connectivism.

How would I relate the big data to adaptive learning?  I would explore these in the coming posts.

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Learning Theories and the Assumptions behind them

Thanks Peter for a thorough review of General System’s theory.  Here is my post relating to a critique on whether Connectivism is a new learning theory or not https://suifaijohnmak.wordpress.com/2013/01/17/my-reflection-on-connectivism-as-a-new-learning-theory-to-date/ I have been participating in the discourse about Connectivism since 2008, and since then I “believe” that it is a new learning theory.  However, I have raised many critical questions since then, in particular the notion of learning, as you have also mentioned in your comments – the social learning, at the level of learner behavior, and psychological ideas about motivation, rational choice behavior etc.

What I think is important is that connections in network is necessary but not sufficient in learning, and the principles that are postulated under Connectivism could also be emerging and are not prescriptive in nature.

Indeed, even the theory of emergence and the principles of Complexity Theory are very difficult to be applied in education.  We might however, be best to have some principles and a theory that approximates what actually happened, based on empirical research findings, rather than waiting for a complete learning theory that would soon prove to show that whole is greater than the sums of their parts, and that reductionism doesn’t reflect the reality of the truth.

I suppose that there are so many variables and strange attractors in an open system that any significant changes in parts of the system could create a totally different pathway (of learning) that may hardly be explained with conventional learning theories.  Even with the tens of thousands of research papers proving certain points of learning, we could challenge the assumptions behind each of the theory by critically examining the evidences presented, and the conclusions are: it is only valid if the assumed conditions are satisfied, based on certain context, certain people with certain behaviors (rational behaviors in general, and certain motivation patterns etc.) and certain professors and students etc.  That might be some light based on the arguments and evidences presented, using the scientific and empirical approaches towards research into those learning theories.

Nevertheless, I reckon there are still differences in perceptions and interpretations of any theory of learning presented, due to our differences in each of our learning experiences.