e-learning

Personalisation, on-demand and predictive analytics: e-learning’s next leap forward

Introduction:

While online learning gained popularity in the 90’s, off late it has gained further traction. With the Covid-19 pandemic and its associated lockdowns, e-learning has emerged as one of the prominent uses of technology in the 21st century. E-learning as an educational experience is delivered electronically. It comprises many elements such as live or pre-recorded lecture content, videos, quizzes and other interactive elements.

While schools, colleges and other educational institutions shut down in early 2020, e-learning emerged as a saviour. With the gaining reputation of e-learning, many students and working professionals have started finding the easy, accessible and ‘at your own pace’ learning mode a friendlier way of educating self and others. Thus, it can be safely assumed that the e-learning market is well poised for a boom; researchers conclude that the market size of the industry will grow by 10.85% by 2025.

To make learning a holistic and egalitarian experience work for all, it is important for e-learning companies to create a personalized and accessible user experience. Big data tools such as personalization, on-demand learning and predictive analysis are helping the e-learning industry today to multiply, both in terms of scale and impact. Before we move onto exploring what role they can play in the future of education, let’s first take a deep dive into what these terms mean.

Personalization:

The word ‘personalization’, mostly used in sales and marketing is a popularly used term. Simply put, it means, one size does not apply to all. Firstly made popular by brands like Google and Amazon, personalized experience became a raging success with custom made services and communication for customers. The same personal details like name, birthdays and favourite colours that are used to tailor gifts for spouses and friends are amplified today by e-learning companies to tailor learning experiences based on learner needs. This has entailed higher learner engagement and improved performance.

On-Demand:

While the meaning of ‘on-demand’ is self-explanatory, in the realm of e-learning it would imply ensuring availability of learning solutions to the learner, anywhere and at any time. Post pandemic, millions of students are out of school. On-demand e-learning solutions guarantee easy access to quality course content and premium educators to learners from around the world

Predictive Analytics:

‘Predictive analytics’ is a tool that uses data, statistics and machine learning techniques to predict the likelihood of future outcomes based on available data. It has transformed e-learning by leaps and bounds. Educational institutions have been managing data for many years. Predictive analytics is a technology breakthrough when it comes to capturing educational big data.

E-learning’ next big leap :

The rapid proliferation of mobility devices has resulted in a situation where nearly all school students have a mobile device. With an explosion of the world wide web, innumerable small mobile devices have access to the internet. The affordability, accessibility and common usage of mobiles/ other internet devices makes e-learning a highly plausible vehicle of learning. So how can it become more democratic?

While personalization has existed in people’s lives for a long time, personalised learning has evolved as a new novelty in e-learning. It is the first step for tailoring content, pedagogy and learning environments to meet individual learning styles and learner needs. More than just individualization or differentiation, a personalized e-learning process enables students to customize several learning elements in their online learning process. This usually means that they set their own goals, pace and communicate with instructors to proceed as per their comfort. Ideally this indicates that the student is in charge of his/her learning and has a direct say in their education.

So, why is personalization important?
  • Each learner is different. For example – some learners perceive audio better and others video;
  • Every learner has a different coping speed. Some can learn large materials in a short time while others can cope only with small amounts;
  • Most learners have an independent and individual learning style. While some may like studying on the PC, others prefer a mobile phone or a tab.
  • One size does not fit all. Each learner is different and comes from a different place of learning.
On-Demand Strategy

On-demand is a strategy for learners to access knowledge based content anytime, anywhere. With ongoing education and learning an imperative for every organization, the question for professionals globally is: what are the best ways to deliver relevant and meaningful learning to multi-generational learners in today’s highly competitive world?

Technology, as always, has the answer to this question. Consumers and companies dominate the world in exchanging data. This data consists of millions of questions pertaining to multitudes of products and services, everyone expects information whenever they have an internet connection.

In the context of e-learning and especially with millions of learners, where each one of them differ from one another, on-demand e-learning contains elements such as flexibility, effective user engagement and leveraging the on-demand nature of the content, be it with respect to business or education.

The on-demand economy is here to stay and is yet to reach its fullest heights. However, technology will continue to revolutionize e-learning by conjoining it to on-demand learning. Whenever that happens, guided, self-paced learning formats and addressing the growing need to learn in a time-crunched world, will continue to be a priority.

In the context of e-learning, predictive analysis, a form of big data, is generated when a user engages on the Learning Management System, LXP or mobile app solution. For example – when a learner completes an assignment, their progress or results generated becomes a part of the “big data”.

Globally this data is gathered, analysed and decoded to be turned into intelligence.

Some insights gathered:
  1. Gain insights on learning and knowledge gaps.
  2. Preferred methods and modes of conducting learning events for learners of all age groups
  3. Understand and approach strengths and weaknesses for future learning strategies
  4. Understand how to personalise and customise an individual’s learning journey to improve the ultimate user experience along with the desired results.

Final Thoughts:

The world around us is rapidly transforming alongside a growing number of diverse students. All the three tools and processes mentioned above are useful for educational and professional organizations that work on complex data. This in turn is making best learning solutions available to students. It also provides tailor made learning that is accessible, with data insights that can improve learning for the future generations.

Like other businesses, if you too are looking to develop IT Solutions in e-learning industry, Mindfire Solutions can be your partner of choice. We have gained significant experience over the years working with Edtech Companies. We have a team of highly skilled and certified software professionals, who have developed many custom solutions for our global clients over the years.

Here are a few interesting projects we have done. Click here to know more:

Case study on site setup for selling online courses.

Case study on learning management system.

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