Measurement of effectiveness of cMOOCs

Here is my response to Christina’s post on difficulties researching cmoocs.

How to measure the effectiveness of a cMOOC?

There are 4 semantic conditions of networks that Stephen Downes has proposed. As Stephen has commented, those properties – openness, diversity, autonomy and connectedness & interactivity is not perfect in cMOOCs. Besides Connectivism as applied in cMOOCs could likely best be based on an informal learning, rather than a traditional institutional model.

I have reiterated that the constraints typically imposed with an institutional model would be huge challenge for administrators and educators to adapt, as is witnessed even in xMOOCs, where a totally new approach (such as flipping the class or flipped learning) as perceived by professors would be at odds with the mass lecture approach typical in mass-education, with a broadcasting model. How to overcome those challenges, and ensure learning is more effective, when cMOOCs are embedded in an institutional model?

Here is my response  that I perceive as a way to measure the effectiveness of cMOOCs – in its

1. awareness of Networked Learning and Connectivism as an “informal learning paradigm”,

2. an adoption and leveraging of the 4 properties- openness, diversity, autonomy and connectedness & interactivity when networking,

3. an achievement of personal goals with immersion in the network and community (and community of practice) on personal basis,

4. adoption of Personal Learning Environment and Network PLE/PLN in pursuit of life-long learning, and

5. a shift of frame of reference and paradigm from knowledge transmission to knowledge sharing and creation model under a knowledge ecology.

John Mak

Personalization of education and learning

What should our future education be aiming for?  Massification of education or personalization of learning?

In this paper on Instructional Theory by Reigeluth C. (2012), he highlights the need of having more personalized approach towards learning, through a post-industralist instructional approach, where learner becomes the centre for learning.

In this Mastery Learning and this paper on Mastery Learning, there are benefits of adopting its philosophy in MOOCs.  That’s also the central pedagogy adopted by most xMOOCs providers.

As I have shared in my previous post, students may master what is expected to be learnt if all teachers are teaching solely to the test.  However, it seems that many people might have mis-understood the initial intention of Mastery Learning, where the intention is NOT to ask the teacher to teach only those concepts for the sake of assessment or testing, but to allow the learners to master their learning at their own pace, in a progressive manner with immediate feedback in order to reinforce their understanding of concepts, and to correct any mis-understood concepts where possible.  Besides, Mastery Learning could be effectively employed in a mentoring and apprenticeship program where the mentor could guide the mentee through the program.

The future of education though would lie with personalization rather than massification of education as Aoki concludes here

This massification of online education appears to go in an opposite direction to personalization that elearning and use of ICT in education should aim for the purpose of providing more effective individualized learning experiences to learners.

How to progress from massification to personalization of online education?  I have shared that here.

Giving  students the correct answers strict away may sound a good instructional approach towards teaching.  However, have the students learnt how to arrive to those calculations?  Have the students mastered the concepts CORRECTLY?  How do we know if the students could apply their skills and transfer them from one area to another, in solving problems?

Aoki elaborates further on how personalization of learning could be achieved:

With the vast amount of data gathered through learners, personalization will become possible eventually with proper learning analytics and data mining. Furthermore, quality of learning outcomes may be further assured with the evidence of learning.