One of the United Nations' seventeen Sustainable Development Goals (SDGs) "Goal 4: Quality Education" aims to ensure inclusive and equitable quality education and promote lifelong learning opportunities for all by 2030.
A major threat to the achievement of this goal is the growing education and skills gap, a measure of the difference between the knowledge, skills, and behaviors that are taught at educational institutions with those needed by industry in the workplace. This gap is exacerbated by many factors, including the unprecedented pace of technology developments in the last two to three decades, the pressures on educators to deliver on multiple fronts (e.g. to balance research with teaching at higher education institutions), and the constant pressures on public expenditure.
Bridging this gap is a socio-economic necessity.
Throughout history, technology has often provided solutions to some of humanity's most intractable problems e.g. through automation, standardization and modularization, faster communications and connectivity. As such, one could legitimately posit that technology is going to play a major role in bridging the aforementioned education and skills gap. For once, various digital technologies can now deliver dynamic and bespoke educational content to millions of learners in a scalable manner. Moreover, multimedia technologies such as VR and AR promise to deliver truly immersive learning experiences at scale. Furthermore, collaborative online environments can now connect large numbers of learners and educators from all over the world, spreading knowledge, skills and good practice fast. Last but not least, machine learning technologies today promise to deliver continuous automated assessment and feedback to learners, a key ingredient in elaborative deep learning.
What's more, many of these technologies are available off-the-shelf and hence benefit from economies of scale and scope, which reduce the cost to the end learner massively. The promise of quality education for all is hence within our grasp.
Bridging the education and skills gap also requires close collaboration between educational institutions, governments, industry and the third sector. Industry in particular has a crucial role to play as the party at the coalface of technology development and talent acquisition. Such collaborations cannot be restricted to the supply of technology to educational institutions but should also extend to content and educational technology development, assessment and quality assurance. For instance, industry is arguably better positioned to produce learning materials that match the rapid pace of technology development, which it is often responsible for. Such an approach would alleviate educators of considerable workload, freeing them to concentrate on the key abstractions and fundamentals as well as pedagogy, which is where their unique expertise lies.
As the company that sits at the heart of one of the world’s largest technology ecosystems (the computing ecosystem), Arm is uniquely positioned to help address the education and skills gap in computing and STEM. That is why we set up a dedicated Education team, with a holistic lifelong approach to learning.
This approach is crucial since many of the gaps happen at the interfaces between different stages of education and learning e.g. from school to university, from university to the workplace. Currently, we address the education and skills gap through three programs:
Arm Education works closely with other educational stakeholders at Arm, namely Arm Sustainability, Arm Partner Enablement and Research Enablement.
The Arm University Program's flagship product to academia is the Education Kit, which is a self-contained educational package offering out-of-the-box experiences to educators and learners. It typically harnesses state-of-the-art hardware and software technologies from the Arm ecosystem and includes rigorous learning-outcome-driven teaching and learning materials in core computer engineering, computer science, electrical and electronic engineering topics. Those materials typically include slides with notes, lab manuals with solutions, videos, quizzes and answers, demonstration code, as well as projects with solutions. These are packaged to fit within existing structures at educational institutions, and adopt an experiential approach to learning. The kit harnesses professional software development tools and low-cost yet powerful hardware platforms from the Arm ecosystem.
The Education Kits are targeted to core computer engineering topics in higher education, including embedded systems design and programming, computer architecture, Internet-of-Things (IoT), SoC design, robotics etc.
To keep up with hardware and software developments and changes, the Education Kits have a built-in one-year maintenance cycle and a four-year major revamp cycle (in line with teaching review cycles at universities) thus ensuring our educational materials are always state-of-the-art.
On top of the above, the Education Kits come with train-the-trainer workshops and webinars, which offer an opportunity for the Arm University Program team to learn from educator and student experiences, as well as help educators adapt Education Kit materials to their own needs. We are also investing in the development of various educational services, such as certification and automatic assessment tools.
The content and technology development approach adopted in the more recently established Arm School Program is similar to the Arm University Program's, with a broader emphasis on STEM topics (e.g. physical computing, coding, data science and Maths education).
The uptake of our content and technologies has been growing massively. The graph below, for example, shows the global uptake of Arm University Program's Education Kits since 2013.
The rapid pace of technology development, discussed above, shows no sign of abating and will continue to drive changes in the skills required by industry. The answer to this accelerated pace of demand requires an equally accelerated learning process, which in turn requires the following ingredients, in our opinion:
We are already seeing elements of the above ingredients developing. For instance, there has been an explosion of online learning platforms in the past two decades, with low-cost media-rich educational materials and services offered conveniently to millions and millions of learners from all over the world.
There has also been a trend towards disaggregation/unbundling of block educational packages such as standard degree programs. Dynamic creation of content for adaptive learning is also not uncommon these days, although true machine learning and artificial intelligence is still in its infancy. Nonetheless, the growth of educational packages from increasingly varied sources, coupled with the unbundling of these packages is leading to an explosion of data in education, which will inevitably lead to the development of more sophisticated machine learning and artificial intelligence algorithms and techniques.
It is this convergence of key enabling technologies, namely: IoT, Big Data and machine learning/AI that promises to replicate the human learning process of: encoding, processing, storage and retrieval, using powerful machines at scale. In all likelihood, it is only a question of time before such a virtuous cycle of information encoding, processing, storage and retrieval, leads to deep learning on a par with, or even surpassing, human intelligence. While some might see this as a threat to humans, for perfectly legitimate reasons, another way of looking at this is that we are merely extending human intelligence. Indeed, artificial intelligence often mimics natural intelligence processes, so rather than seeing these two (i.e. natural intelligence and artificial intelligence) as opposites, it is perhaps more fruitful to see them as extensions of each other, leading us to an accelerated learning revolution that might well plug the education and skills gap for good. A common consciousness between humans and machines will perhaps follow...
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