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As an engineer from the 1980s, I found movie series such as Terminator and Matrix truly mind-blowing; it often left me wondering "what if machines took over the world one day?” The 'artificial intelligence’ that powered the cyborgs was fascinating. In 2014, when I realised Coursera was offering a course in artificial intelligence, I immediately enrolled for the course.
It was my curiosity and eagerness which drove me to enroll. I believe, curiosity, among many other reasons such as 'learning from world’s leading educational institutions’ and 'learning what you always wanted to learn’, was a key driver that powered Massive Open Online Courses (MOOCs) to a large scale. Since 2012, many university-led and private MOOCs have emerged. According to a recent survey, 23 million people had registered for their first online course in 2016. MOOCs have truly gone massive - but how massive will they get? What will drive it?
While MOOCs were kicked off with the intention to democratise learning in its purest sense, many of them have turned for-profit for sustenance. They continue to be open under certain conditions. Content is charged; assessments and case studies are monetised and so are the verified credentials. This monetisation is unlikely to dent the growth of MOOCs. MOOCs have emerged as a possible solution to address the shortage in quality faculty and high tuition cost in the western world.
Students world over prefer to learn about the latest in their field - from artificial intelligence to genomics to making driverless cars. Anytime, anywhere learning is a reality through mobile apps. Governments are also seeing them as a means to skill a large number of unemployed youth in their respective countries. Enterprises are encouraging employees to upskill via them. Universities have started giving credit to online programmes. But will these continue to drive MOOCs?
As MOOCs transform into a business, they need to adopt the ethos by which a customer consumes a product or a service. What is the output of my learning? Do I get a promotion in my current company? Can I make a career change? Will I get my first job? Will the productivity of my employees improve? These are the real outcomes that an MOOC needs to solve.
As more learners take up to online learning, other aspects of service such as customer support, learner experience and learning experience become critical. Technology companies have realised that the academic intervention at university level can be fast tracked if they work with MOOCs. While universities were the first to launch MOOCs, today, technology companies are partnering with private MOOCs to promote their products and increase usage. Such skill-focused programmes with an industry partner come with clear outcomes for a learner - learn a new skill and work with leading companies.
I believe that MOOC as a phenomenon has reached its peak among early adopters. For sustained growth and impact, it needs to cater to 'early majority’ and the 'late majority’ - this is where the bulk of the population lies. Can these large sets of population learn on their own? Will they demonstrate a similar completion rate to early adopters? Unlikely.
Learnability Quotient should be the key metric that MOOCs should measure themselves against. For most people learning online, regular interventions are needed to improve learnability.
In a country like ours, where school systems have been very traditional, a shift towards technology-enabled learning needs to be guided and hand-held. A faculty intervention is more than desirable. While some corporates have integrated MOOCs with their learning & development strategy, are they measuring the return on investment? Are employees finding time to learn amidst their 'number’ target? Are they clarifying their doubts or practising the exercises when the boundary between work & personal life is wobbling? A planned and targeted faculty intervention can be a potential solution here.
A key aspect of an MOOC is its ability to power experiential learning. While the initial MOOCs were large on theory and concepts, the demand for skilled hands in areas such as Data Science and Computer Science required learners to practice exercises and submit practical examinations. The introduction of cloud-enabled programming environments were key to learning programming languages such as Python. Similarly, simulators and digital labs in non-technical domains such as Digital Marketing have provided hands-on experience to learners.
For any consumer product, customer support needs to be robust and scalable. Investments in customer support and social media are required. Every learner needs to be addressed individually. Needless to say, all of these can be enabled with technology.
Tutor Bots powered by artificial intelligence are emerging as the new norm to provide 24X7 faculty assistance. Integration with regular higher education will be the largest challenge and biggest win for online education providers.
Will MOOCs adhere to their original definition in the future? Will they be massive? Most likely, as companies will prefer them as the best way to create a talent base and universities need additional revenue streams. Will they be open? Yes, while there will be a cost to the learning, it will still be significantly lower than conventional education.
Monetised, outcome-based, selectively open and combined with interventions could potentially define tomorrow’s MOOC.