Cognitive Education: The tipping point

This article reviews some of the key challenges and discusses how technological advances—from digitization to cognitive computing—finally provide us the tools to address the challenges and fundamentally transform the learning journey.

Bikram Sengupta Oct 05th 2017

The Education industry has reached an interesting tipping point, where it continues to be plagued by several significant challenges; but on the horizon are enormous growth opportunities spurred by digitization. In this article, we will review some of the key challenges and discuss how technological advances—from digitization to cognitive computing—finally provide us the tools to address the challenges and fundamentally transform the learning journey.

Education industry: A few key challenges
The challenges in the Education industry are aplenty and well-documented. Below, we consider a few key ones.

There are huge gaps in demand-supply of education, especially in developing nations. For example, based on data collected in 2014, India had around 677 universities and 37,204 colleges. However, India was expected to have 45 million more 10th graders in 2020, which meant around 50,000 more colleges and 800 more universities were needed to push the Gross Enrolment Ratio (GER) to 30%.  Clearly, it is not possible to bridge such massive gaps by continuing to build more brick-and-mortar institutions.

Second, skyrocketing costs have been placing a huge financial burden on learners. For example, in the US, the rate of increase in college costs has been four times faster than the increase in the consumer price index (a measure of inflation), and students are well over $1 trillion in debt. Even in an emerging economy like India, the costs of getting a degree in virtually any discipline, have grown manifold over the last two decades. The space afforded by the demand-supply gap is providing lucrative commercial opportunities for private institutions who charge a premium for services that are often of highly questionable quality.

Third, misalignment between education and industry needs, coupled with poor quality pedagogy and learning, is creating large unemployable populations. By some estimates, 47% graduates in India are considered unsuitable for any job. In the EU, 27% employers left entry level positions vacant as they cannot find the necessary skills. In a knowledge-driven economy spurred by rapid technological advances, existing workers are also often finding their skills outdated and their jobs under threat.

Finally, continuation of the one-size-fits all model for education, which efficiently produced large batches of factory workers in the industrial age, is leading to widespread disengagement with the education system—especially, when getting a degree or diploma is no longer a ticket to a secure employment and a stable life. For example, in the US, 8300 high school students drop out of school every day on an average, thereby causing $320B of lost lifetime-earning opportunity annually.

Digitization and its far-reaching impact on Education
The significant (and long-standing) challenges notwithstanding, there has never been a better time to address the problems and transform the education industry than now. The fundamental reason is that worldwide, we are witnessing a rapid adoption of digital content, platforms and processes for teaching, learning and administration. This is a welcome change in an industry that has traditionally been conservative in embracing technology.

Dependence on government spending and old-world policies often meant that technology was perceived as a good-to-have capability to be considered after addressing more pressing problems of the education industry, rather than as strategic a tool to overcome many of the deficiencies or provide a competitive advantage. This perception is changing with even emerging economies leapfrogging into the digital age through massive deployment of low-cost laptops and tablets, and expansion of broadband technologies. The availability of cloud-based platforms for disseminating content and delivering pedagogy at scale—as evidenced, for example, in the rise of the MOOCs—means that we can expect significant progress to be made in the coming years in lowering costs and increasing access to quality education.

Recently, the Georgia Institute of Technology announced its second low cost MOOC-inspired masters degree program at less than $10,000, about a fifth of the cost students usually pay for the year-long residential program. Other institutions are certainly going to experiment with this model soon, as it will let them generate significant new revenue streams without the large capital overhead associated with building new campuses, while helping meet a huge global demand for education.

However, while digitization lowers the barrier to accessing education, by itself it is not a panacea. A lecture that is difficult to follow in class will appear even more complex when listened to over a tablet; a teacher struggling to manage a class of 30 will be severely stretched if asked to additionally manage 200 remote students; a student graduating with a low-cost online degree or certification will still struggle to find a job if the program has not been designed keeping the needs of the market in mind.

This is where the power of data—the by-product of digitization—comes in. As the learning eco-system gets instrumented end-to-end over digital platforms, enormous datasets are being created whose analysis can yield rich insights about pedagogy, learning and learners, and can help place individuals on personalized learning and career pathways.

Consider, for example, analysis of student browsing patterns to detect possible areas of confusion, and proactive alerts sent to the lecturer with a heatmap of the video showing areas where most students have struggled; or, a cognitive teaching assistant that can answer questions as effectively as human TAs do and drastically reduces the load on the lecturer, while keeping remote students happy and engaged; or a career counsellor that can ingest and analyse huge volume of labour market data every day to detect skills in high demand, advises training institutes on revamping their curriculum, while assisting candidates find the most appropriate job, training or mentor.

With advances in big data and analysis, and cognitive computing systems, these scenarios are not only feasible, early versions have demonstrated promise (e.g. IBM Watson powered Teaching Assistant, “Jill Watson”) and we can look forward to seeing such systems becoming mainstream in the not-too-distant future. To this, we can add the tremendous progress that has been achieved in human computer interaction technologies, which are fostering new forms of interactive learning through multi-modal systems, gamification, physical-digital interaction, augmented and virtual reality etc., and leading to new ways of engagement and fundamentally new learning experiences.

The confluence of these trends will define the next generation of cognitive learning that can transform outcomes and re-shape the education industry. In future articles, we will delve more deeply into how these advances are opening up the possibility of delivering personalized learning at scale, and providing the foundation for individual and societal success.

The author is a senior technical manager at IBM India Research Laboratory and leads the Cognitive Education division.

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