Use of tech like AI and ML has the potential to transform higher education
We need a shift from knowing to learning because google knows everything; Performance metrics must shift from inputs to outcomes.
George Couras, in his book, ‘The Innovative Mindset’ made an interesting quip, ‘Technology will never replace great teachers but technology in the hands of great teachers is transformational.
”Technologies like AI and ML are rapidly transforming every aspect of human lives; yet, one industry that has seen limited use of this new technology but offers incredible potential and opportunity, is education.
The magic of software applications, where data and rules get the answers is often confused with the magic of artificial intelligence and machine learning that takes data to get you the rules.
We’d like to make the case that use of Artificial Intelligence and Machine Learning may be the magic needed to transform the efficacy and relevance of Indian Higher Education.
Education suffered owing to over emphasis on knowledge at the expense of skill development; acknowledgement of the fact that education without skills leads to unemployment but skills without education leads to lower productivity, has brought forward an education system that focuses both on knowledge and skills. We need a shift from knowing to learning because google knows everything; Performance metrics must shift from inputs to outcomes. Personalization is not about making things easier for the learner but tapping into the motivation of the learner and arousing curiosity.
Assessment must shift to continuous feedback as annual exams haven’t proven their worth. Lifelong learning needs a continuum between prepare, repair and upgrade. Employability is as important and objective an outcome!
AI and data driven platforms today are able to track the learner’s comprehension of the subject and create personalised adaptive pathways through intelligent recommendation engines. Whether the goal is to identify and better support pain points in the student journey, more efficiently allocate resources, or improve student and faculty engagement, institutions are seeing the benefits of data-backed solutions.
Several universities across the world have experimented with chatbots that answer student’s queries – thereby collecting a large volume of data regarding student’s interest and concerns. This data can be analysed by ML enabled intelligent sys tems that can provide feedback, explanations and timely guidance and can enable universities create innovative learning programs and services to improve student experiences.
Experiential immersive education is a challenge with a large cohort due to physical limitations and high costs. AI enabled digital assistants can provide a more personalized learning experience – they can remind students to study, keep track of their study durations, and even analyse their grades; the objective is to supplement teachers, not replace them, and reduce their administrative workload so they can focus on more creative and humane aspects of learning.
AI powered technology offers exciting new opportunities in the form of immersive education; being able to see and interact with the human body or a microscopic cell instead of just reading about it in a chapter of a book will transform how students engage with the material.
If teachers could be stripped of time-consuming administrative tasks, such as passing on acquired information, supervising and answering routine questions they would have more time to mentor, motivate and coach students. A recursive analysis of learning outcomes across students, cohorts and schools would considerably improve the efficacy of flip classrooms where classrooms are used for discussions and students finish the lecture and learning in advance.
Natural language, computer vision, and deep learning could answer student questions whereas machine learning can identify complementary skills that will maximize critical thinking and test students’ capacity to adapt and collaborate.
AI-powered learning analytics, today, bring together the disciplines of predictive and prescriptive analytics, for personalizing communications with students, increasin g retention rates, and improving student experience and engagement.
ML tools gather real time, micro granular behavioral data and provide insightful visual analytics thereby creating a seamless learning experience for the learner. This could empower students by providing them with control over how fast they learn, awareness of how they learn best, and the lifelong feedback of one’s own cognitive and behavioural preferences.
Data driven AI and ML engines provide the opportunity to put an end to traditional testing systems and measure academic abilities and achievement in a more nuanced way; some of them can decipher student’s handwriting, analyse teacher’s grading patterns and grade assignments quicker than a teacher.
Although AI and ML technologies offer many exciting possibilities, we are still in the early stages of capability building. Physical classroom systems, because of the limitations of time and space, often prove limiting. A broad and deep adaptation of AI and ML technologies can help education break the difficult trinity between cost, quality and scale.
With universities facing many financial and demographic challenges and a sea of opportunities including reaching employed learners and online learning, expanding use of artificial intelligence and machine learning may prove beneficial. Here’s an opportunity to build an education system that is both equal and excellent – we must not waste it!
( The article is authored by Prof TN Singh, Director IIT Patna and co-authored by Shantanu Rooj, Founder and CEO, Teamlease, Edtech. Views expressed here are personal.)