Artificial intelligence is fast making its way into mainstream education. I do not infer as part of the standard technical curriculum. But several schools, colleges, universities and other academic institutions are adopting AI in the process of delivering impactful education to students and their numbers are rapidly increasing.

Across the world, we are seeing AI augmentation in different facets of the education system – from automating routine tasks that teachers have to perform to crafting personalised education curriculum that is line with a student’s aptitude and areas of interest.

The education sector in India suffers from deep-rooted challenges that need wholesale solutions. The bulk of our students is compelled to go through archaic pedagogical methods that are employed to deliver static and outdated curricula.

For a while now, Bill Gates and other tech stalwarts have been excited by the idea of infusing AI into the education system. Bill Gates calls this bouquet of technology-driven, impactful delivery of coursework as ‘Artificially Intelligent Tutoring Systems’ and hopes that it leads to better internalisation of course content. This column shares some of the areas where AI can leave its mark on the education system and revolutionise the way the next generation of students learn.

Freeing up Teacher’s Time

Teachers are burdened with several menial, low-value tasks that are ripe for an AI augmentation. These tasks neither deliver better learning outcomes nor improve student experience. The time our teachers spend performing hygiene activities – from taking the attendance of the class, evaluating and grading tests and assignments and performing peer reviews – is enormously wasteful.

The time spent by teachers can be easily unlocked through AI, helping them focus on what they do best – teaching and coaching for success. Bringing in AI into the core way-of-working of schools today will help eliminate these burdensome tasks in the following ways:

• By curating tests for students automatically based on the aptitude of students in the classroom. Rather than relying on teachers to conjure up questions in the classroom, AI can help tutors assess the learning level of students and contextually bring up questions. Teachers will be able to administer tests much more easily by using a gradational question bank powered by AI

• Grading the administered tests and assignments. This is another time-consuming and often low-value task that can easily be taken up by AI administered-tests. AI can help automate the repetitive task of grading tests, thus helping teachers focus more on how they can create a better platform for learning by coaching and solving questions from students. AI-graded tests can also help bring up commonly occurring patterns of errors (ie, are students mainly making the same mistakes?), in effect providing input to teachers on which lesson plans require more impetus in the next class

• Ease out repetitive administrative tasks. Teachers also spend hours over the year submitting periodic reviews to their supervisors and coordinators, taking attendance and peer reviewing the efficacy of other teachers. This workload can also be supported by AI – by maintaining automated attendance logs, summarising the test scores of students and reporting the performance of teachers

Curricula, Content Planning

The present-day curricula delivery process is largely inefficient. The current paradigm requires a teacher to deliver pre-designed, standardised content to a classroom full of students with diverse aptitudes and interest levels. The negative impact of current pedagogical methods can still be manifested through the employability score of the current generation.

By leveraging the variegated applications powered by AI techniques, academia will not only be able to deliver more personalised curricula and lesson plans but also improve students’ understanding and retention of the coursework, leading to an improvement in educational outcomes. Here are a few examples of how we can enable those:

• AI can be instrumental in creating a culture of continuous improvement among teachers. By tracking their performance across different key metrics, the educational system will be able to uncover the areas where teachers need support and coaching more effectively. AI can also help curate the coursework for teacher improvement, thus making sure that teachers are continuously updated and can continuously refine their craft

• By infusing AI into the skills and aptitude assessment process for students, schools will be able to better judge the current level of understanding among students for a particular subject area as well as where their innate inclinations lie. Often, students are unclear or unsure about how they can make the most of their talents and how they can channel them into a trade. AI can help schools map out the data of previous students, their career achievements and tie that back to educational research. This will allow schools to accurately predict the subjects for which a student has a natural inclination and then coach her in that direction

• AI can also use data around student attention, interest combined with their aptitudes and abilities to recommend customised coursework. This will help students build a structured career path. This AI-centric approach will foster personalised training pathways and provide students with the skills needed to succeed in their future professions, rather than burdening them and staggering their confidence as the current system does

Optimising Classroom Experience

To fully unleash the creativity and expertise of teachers, the education system needs to also imbue AI-led applications in the classroom on a day-to-day basis. This will enable teachers to work at full throttle. Time spent on minding students and reorienting classroom methods to ensure better student engagement can be saved by using AI in the following ways:

• AI can help improve the tracking of students’ attention levels and help teachers intervene before a student loses interest in the classroom content. While teachers are conversant in minding students that actively disrupt the classroom, engaging students who are quietly inattentive is a comparatively difficult task. By employing attention tracking devices, teachers can much easily monitor the attentiveness of the class and mind them before they tune out

• By aggregating the attention scores of the classroom, AI can help teachers devise a more potent mix of teaching, testing and activities – to continuously ensure better class performance and engagement

AI can bring a plethora of benefits to the education system at large, providing improved educational outcomes to all stakeholders – students, teachers and parents. Through personalised curricula, improved efficiency in the time management for teachers and effective in-class monitoring and assistance, AI can shift the paradigm of how the education system works and how coursework is consumed and leveraged by the next generation of students.

The traditional archetype of learning and employment – where students went to university and learned a skill that served them for the entirety of the careers – is rapidly evolving and changing. Today, we are in the age of continuous learning – where there is an inherent expectation on members of the employed workforce to constantly upgrade their knowledge and soft and hard skills. Earlier, executive education used to be a reserve of a privileged few high performers at large organizations, who showed great promise and rapidly rose through the ranks. Now, continuous learning across all the segments of the workforce is increasingly the new normal – almost to the point where it is the mandate for organizations that wish to grow and succeed in the business sphere. There is an expectation now that even the rank-and-file of the organization devote time to learning, unlearning & relearning and apply newfound ideas and techniques into their area of business.

What has been the driver behind this change? Why has upskilling and reskilling become the norm for the contemporary corporate career? A few important reasons underpin this change. The nature of the business today is extremely dynamic. Business environment and competitive landscape are changing faster than ever, with technology becoming the mainstay of the modern business. Tech-enabled startups are moving in and challenging traditional incumbents across industries. These changes are made a further complex with emergent ideas and changing paradigms of organizational management and leadership. In today’s fast-moving world of business, it is a critical priority for executives to keep their organizations nimble, proactive and armed with every arrow in their quiver, to ensure the continued success of their firms

Executive education is an important medium to achieve this goal and helps bridge the skill gap that is almost certain to rise when industries and organizations face structural headwinds. However, for executive education to live up to the promise and deliver value to employees and their organizations, we need to re-look at the programs itself. We need to ensure that the coursework and curriculum are topical, contextualized and relevant, whilst being personalized to the needs of the organization and its professionals. Here are a few perspectives on how executive education can be adapted for the industry4.0 era: 

Expand the Scope of Executive Education and the Courseware

As we dismantle the traditional paradigms of work and education, we also need to rewire our traditional understanding of what an executive education comprises. For years, corporations relied on top-tier management schools and universities to facilitate the essential leadership training for their workforce. In today’s world, rewiring an understanding of leadership is just not going to cut it. Executive education programs need to add more in terms of practical, on-the-job skills, that will help employees perform better and remain relevant to the needs of the business. 

There is now a strong case to expand the scope of executive education beyond traditional B-schools and include even MOOC-based education – which is provided by a plethora of websites today. Coursera, Udemy, LinkedIn Learning – to name a few – provide very tactical, hands-on understanding of essential, practical skills that the workforce can put to use right away, while also facilitating the career change aspirations that employees may have. Organizations need to seek out these MOOC-based providers to augment the executive education curriculum in a way that increases its scope and reach among employees.

These programs could very well help employees refresh their skill sets. For instance, such programs could help coders become well-rounded full-stack developers. Similarly, those with data engineering skills could be moved into areas such as high-performance analytics or artificial intelligence. Team leads could be educated formally in the tools and techniques associated with product management. For mapping current employee skills with the contemporary requirements of the business, MOOCs can be a critical intervention to incrementally upskill employees in their domain of work.

Incorporating the importance of shorter, tactical courses

Whilst there is no doubt about the value provided by a long-form one-year executive education program, companies also need to consider the benefits of short-term tactical coursework. Corporations need to augment their training programs with shorter, time-boxed courseware that can deliver instant impact for the organization. 

There are two reasons why this is important. Firstly, given the speed at which technology and business mature, it may not always make sense to put someone in a one-year program and wait for the delivery of associated results. In such circumstances, short form courses help deliver faster time-to-value – with employees able to deliver results in weeks, rather than months. Secondly, shorter-term courses also help reduce some of the inherent barriers people have towards learning. Shortening the learning cycle, putting it to use immediately and seeing real-life results, can help employees see instant benefits of the lifelong learning paradigm and break down mental barriers to learning.

Co-create multiple, personalized career pathways

The key word here is ‘personalized’. We need to move away from the old thinking of one-size-fits-all training to deliver more tailored, fit-for-purpose and relevant executive education to employees. To start, organizations need to develop skill maps and assessments – to identify where the workforce is today in terms of the required skill sets and where they are expected to be. Once this is performed, L&D teams can help create personalized learning journey-maps for their employees – based on the career interests and aspirations of employees. For instance, for some employees, it may make sense to provide a refresher and upskilling in their current areas of work and for others, it may make sense to reskill them in new areas of the business. Either way, developing a personalized training regimen for the executive education of the employees will deliver better results and help them excel in their field and improve the efficacy of learning programs too.

Artificial intelligence is slowly, and steadily, making its way into mainstream education. And not simply as part of educational curricula. We are seeing increasing instances of schools, colleges and other academic institutions leveraging AI as a crucial part of the process in which they deliver education to their students. In the West, numerous examples abound of these educational institutions leaning heavily on AI – from delivering personalized educational curricula to automating routine tasks that classroom teachers have to routinely perform. 

Tech luminaries such as Bill Gates are enthused by the idea of Artificially Intelligent Tutoring Systems – which can ensure impactful delivery of course content and improved internalization of that content among students. The education sector in India, currently reeling from endemic problems – from static curricula to dated pedagogical methods – has much to gain through an AI-driven facelift. Let us look at some of the areas where AI can make its way into education and revolutionize the way the next generation of students learns.

Augment Planning of Curricula and Lesson Plans

The present-day paradigm of a teacher delivering pre-designed, standardized content to a classroom of students with diverse aptitudes and interest levels – is remarkably inefficient. We’ve seen the negative impact that the current pedagogical methods have had on the employability levels of the current generation. To this end, by leveraging the variegated applications of artificial intelligence techniques, academia would be able to deliver more personalized curricula and lesson plans, improve students’ understanding and retention of the coursework and in turn improve educational outcomes. Here are a few examples of how we could enable those:

By infusing AI into the skills assessment and aptitude assessment process for students, schools and universities will be able to better judge both – the current level of understanding among students for a specific subject area and where their innate inclinations lie. Often, students are unclear or unsure about where they see their career graph moving and what they would like to do in the future. Through AI, schools and universities can map out the data of previous students and their career achievements and tie that back to educational research. This way, schools, and universities may be able to accurately predict which subjects a student has a natural inclination towards and then coach them for a career in that direction.

Going in the same vein, AI can also use data around student attention, interest, aptitude, and ability to recommend customized coursework. This will help build the capability of students towards a specific career path and bring better value to the time of students. This AI-centric approach would help foster more personalized training pathways and enable students with the skills they need to succeed in their future professions, rather than burdening our students and staggering their confidence as done by the current system.

Furthermore, AI can also be instrumental in enabling continuous improvement for teachers. By tracking their performance across a variety of metrics, schools will be able to better uncover the areas where teachers need support and coaching. AI can also help curate the coursework for teacher improvement, thus making sure that teachers are continuously updated and continuously refine their craft

Automating Routine, Low-Value Tasks

Teachers today are overburdened by all manner of menial, low-value tasks that neither improve student experience nor deliver better learning outcomes. Enormous time is spent by our teachers worrying about and performing hygiene activities – from taking the attendance of the class, evaluating and grading tests and assignment and performing peer reviews. We can unlock this time spent by teachers and help them focus on what they do best – teaching and coaching for success. By incorporating AI into the core way-of-working of schools today, we can eliminate these burdensome tasks in the following ways:

By automatically curating tests for students based on the aptitude of students in the classroom. Rather than relying on teachers to conjure up questions in the classroom, AI could help understand the learning level of students and fire up the questions. By using a gradational question bank, teachers would be able to administer tests much more easily.

The other related time-consuming area for teachers tends to be grading the administered tests and assignments. These tasks can much easily be eliminated by using the AI administered tests. AI can help automate the repetitive task of grading tests, thus helping teachers focus more on coaching, solving questions from students and helping create a better platform for learning. AI-graded tests can also help surface patterns of errors (i.e. are students mainly making the same mistakes?), thus providing input to teachers on which areas of training require more impetus in the next class.

Among other several administrative tasks – teachers also spend hours over the year taking attendance, peer reviewing the efficacy of the other teachers and submitting periodic reviews to their supervisors and coordinators. This workload can also be supported by artificial intelligence – by maintaining automated attendance logs, summarizing the test scores of students and reporting the performance of teachers.

Optimizing the Classroom Experience

AI in education can go well beyond simply personalizing course content and unburdening teachers. To fully inform and unleash the creativity and expertise of teachers, we also need to imbue AI-led applications in the classroom on a day-to-day basis so that teachers can work at full-throttle. Time spent on minding students and reorienting classroom methods to ensure better student engagement can be saved by using AI in the following ways:

AI can help improve the tracking of students’ attention levels and help teachers intervene before students lose interest in the classroom content. While teachers are conversant in minding students that actively disrupt the classroom, engaging students who are quietly inattentive is a comparatively difficult task. Using attention trackers, teachers can much easily monitor the attentiveness of the class and mind them before they tune out.

Finally, by aggregating the attention scores of a particular classroom, AI can help teachers devise a more potent mix of teaching, testing, and activities – to continuously ensure better class performance and engagement

Using AI to augment classroom and educational institutions is of interest to everyone – students, teachers, and parents – and can help bolster educational outcomes. By personalizing the curriculum, optimizing the time of teachers and effective in-class monitoring and assistance, AI can be a game-changer in the way coursework is consumed and leveraged by the next generation of students. 

A combination of economic, business and technology factors have led to a steady rise in synergistic partnerships between industry and academia in India. Whilst a strong academia-industry partnership model has existed for several years in USA, UK, Canada, Singapore and few other countries.  India Inc. is catching up quickly to the transformative benefits that academia-industry engagements can bring to both parties. Rather than co-opt existing technology, corporates are under increasing pressure to incubate and deliver bleeding edge technology solutions to ensure continued competitive advantage and they are turning to some of the brightest minds in universities today for ideas on how to do that.

While there may be several drivers for corporates inking strategic, operational partnership modes with an academic institution; I see three common themes: First, academic institutions are under increasing pressure to deliver bleeding edge research that has commercial viability and real-world applications. They simply cannot ignore events in the business spheres anymore. For this, they rely on enterprises to provide contextualized understanding within which they can frame their problem statements and hypotheses. Second, we are also witnessing a muted public-sector funding for research, combined with the proliferation of private universities. As a result, academics need the patronage of corporates to fund their long-term research endeavors and goals. Lastly, R&D departments at organizations need the bright minds from academia to deliver results in a shorter time-frame and lower cost. These three critical drivers are spurring a healthy interest in developing academia-industry engagements. 

From AI, analytics perspective; research and innovation are the key differentiators. Let us dig deeper into the academia-industry engagements and dwell on building robust and synergistic engagement model and framework between academia-industry: 

Collaboration for Data Sets

This engagement is primarily intended for gaining access to data for running analysis and hypothesis building. Usually, an organization may need access to multiple varieties of data sets that are available with universities, to refine and improve their statistical models. These engagements can be often seen between enterprises and university hospitals – a hot-bed of structured and unstructured patient data. Healthcare-focused technology companies typically need access to tons of data to build and improve their AI systems – to capture every possible variation of the data and ensure that their model accounts for the best results.

An example of such a collaboration can be seen between Google DeepMind and University College London (UCL) for the use of AI in radiotherapy. The key to this partnership is UCL’s hospital and the availability of researchers in a real-world medical environment. 

Applied Research

The second area of collaboration is for industry and academia to create real-world applicability for research. Academics tend to be extremely visionary in their ability to add to a body of knowledge through thorough and intelligent research but may often lack visibility into challenges faced by businesses. By leveraging business context provided by corporates, they can add a flavor of high applicability to their research. Additionally, solving relevant, business-critical problems, researchers can also improve their visibility among their community, while potentially improving their H-Index scores through highly citable research.

An example of this collaboration is CA Technologies and IIIT Hyderabad engagement, they recently signed an agreement to set up a co-innovation lab. They intend to work together on topical problems in areas of Natural Language Processing, AI and Machine Learning, as per the company statement. For the researchers, this agreement would help improve their visibility through publications in scientific journals and CA Technologies can identify reference architectures and prototypes that will enable faster development timelines.

Co-Curriculum development and learning programs

This alliance between industry and academia is for cross-pollinating and co-creating AI, analytics academic curricula. Given the dynamic nature of business today, enterprises are collaborating with universities for providing continuous AI, analytics training to their employees across disciplines. This ensures that their employees have a contemporary understanding of the best practices in their field of work, while also promoting employee satisfaction. On the other hand, universities carry this understanding of the needs of the corporate sector and incorporate the same into their AI, analytics academic curriculum. For universities, this is a critical way in which they can create a comprehensive coursework that is exceeding relevant in the job market today.

Whilst, these are few prevalent areas of collaboration; other ones may look at mutually inking long-term strategic initiatives that involve academic institutions adding a cross-dimensional flavor to multiple analytics projects and requirements at organizations. The journey between academic – institutions collaboration has evolved and will witness several novel engagement models in the future. The continuous evolution of learning, unlearning and relearning phase will usher a new paradigm in academia-industry collaboration  

Technology proliferation and changing socio-economic factors is ushering tumultuous change in the old paradigm of work. Today, with the anvil of ‘gig-economy’ – a collective talent marketplace of independent workforce working on recurring short-term assignments; we are now at the definitive cusp of a new reality of the workforce – working professionals will not only change jobs but will take multiple career switches while being expected to continuously unlearn and relearn new skills along the way. 

The future of work is here. It is time to shape the future of education.

According to multiple studies, success in the gig economy will be centered around 3 competencies which I call the 3 C’s – Creativity, Curiosity, and Collaboration. While children are naturally curious and creative, it is more important than ever before for academia nurture and sharpens these two qualities, while adding a core competency of collaboration, by imbibing them in their teaching methods. 

In the continuum, I strongly believe that education in the time to come will go in for a fundamental change. Here’s my take on the future of education: 

Gamified Education

According to a World Economic Forum report, there is enormous potential to improve the social and emotional skills of students by incorporating the use of play in their education – which in turn can provide a boost to their collaborative skills and drive curiosity. Developing these skills will require three types of games, namely 

Role-playing Games -creating a narrative arc through a sequence of events and providing them with a variety of options for interacting with the game through their characters. Role-playing games also allow students to explore multiple paths and revisit previously explored times and experiences.

Strategy Games -multiple students partaking in a quest to manage the strategic planning and deployment of scarce resources

Sandbox Games – focusing on open-ended exploration, being resourceful and taking initiative among a group of players to achieve a shared goal.

Unbundled Curriculums

It may no longer be productive to attend 3 -4 years of graduate school, followed by post-graduate education. In the gig economy, students and corporates will unlock shared benefits of skills-centric learning, followed by a stint at the workplace, before going back to school and acquiring new skills. While this will reduce the time and cost of learning; it will also help students apply their skills in the workforce and gain the much-needed hands-on experience. By seeing their classroom learnings in action, it will also spur curiosity to learn more and do more in the future.

Increased Mobility Between Institutes

While our generation uses MOOCs for furthering our education, MOOCs will become mainstream for future generations. MOOCs provide a wonderful counterweight to the natural curiosity of students while helping institutions extend their curricula into subjects they currently do not have the capacity to address. MOOCs will also become more social and collaborative, encouraging students to learn with each other and improve their overall performance.

Technology Augmentation

We will also see a rise in Virtual Reality (VR) and robots in the classroom. VR will help create more immersive learning experiences for students, thus stroking their natural curiosity to learn. Robots, on the other hand, will take the scud work from teachers – and provide inputs on skills assessments, personalized curriculum pathways, and attention tracking – allowing teachers to focus more on coaching and mentoring.

The future of education will define how our next generations shape up and succeed in the workplace. It is critical that we understand the value of developing the 3C’s – Creativity, Curiosity, and Collaboration – from an early age so that our next generation can achieve their full potential and value in the workforce.