How can Big Data Analytics help in delivering personalized learning?

Viren Kapadia February 18, 2021
How can Big Data Analytics help in delivering personalized learning

Data is undoubtedly one of the most powerful tools we have in modern learning. It can empower instructors and administrators with insights, illuminate potential issues, streamline inefficiencies, and help personalize the learning experience for employees. There are building evidence and compelling case studies demonstrating how data analytics can be leveraged to help organizations achieve better results for employees by customizing the learning experience.

As we move into a new decade, the use of AI/Cloud learning system/SAAS/ Cloud LMS is on the rise and set to revolutionize the learning experience for learners and admins alike. Not only does it offer more personalized learning abilities, but, honestly, it will make your job a lot more enjoyable when all of your basic, time-consuming tasks are automated. With technological advancement, Learning Management Systems (LMS) holds the potential to rationalize the corporate training process. Most of the L&D teams are depending on the cloud-based LMS to boost learner engagement, knowledge retention, and organizational performance. The cloud-based LMS caters to the training demands of all.

Preparing the organization

A first step in personalizing learning is to identify the importance of continuous learning in the organization. To truly meet the needs of employees and to become an organization that supports and delivers personalized learning, it is necessary to create, build, and support a learning organization. A learning organization is one that:

  • Continually learns,
  • Supports the learning of its staff,
  • Listens to everyone and openly communicates, and
  • Embraces a philosophy of ongoing improvement.

The modern training management platforms such as AI/Cloud learning system/SAAS/ Cloud LMS are designed to deliver effective learning as it streamlines L&D efforts while saving cost, time, and effort. The robust big data analytics facilitates corporate personalized learning experiences. Several benefits of big data analytics include the following:

  • Adaptive design :

    The easy-to-navigate interface of LMS is a crucial feature to engage maximum employees. An adaptive LMS provides mobile-enabled courses for learning anytime, anywhere, and on the go. Overall, an intuitive UI (User Interface) and personalized UX (User Experience) boost learner engagement, bridge skills-gaps, improve accessibility, and overall learning uptake.

  • Reduced training costs :

    The traditional classroom training approach involves huge costs associated with travel, infrastructure, and more. So, using the modern learning management software, organizations are shifting towards e-learning or blended learning approach to mitigate costs on time and effort.

  • Personalized learning :

    With the changing needs of the new-age workforce, the scope to deliver technology-aided learning to meet the personalized needs is also growing. An LMS makes it easier and more effective for administrators to personalize the user interface (UI) and deliver content that suits varied styles and preferences. Consequently, learning becomes more accessible and personalized when people can choose the most relevant courses that fit their requirements.

  • Better scalability :

    Corporate training aims to align learning to pertinent needs of employees spread across diverse demographic locations. Sometimes, this may drive inconsistency as an extended workforce may not access training courses and assessments at the same pace as internal employees. As a solution, enterprises implement cloud-based learning management software, which is scalable enough to train widespread audiences at the point of need. As a result, it improves overall reach, scalability, knowledge competency, and impact.

  • Reduced maintenance :

    Today, organizations rely on enterprise systems such as CRM, HRMS, and others to train the modern workforce effectively. A technical glitch may hamper the productivity of the system by involving huge costs and effort. So, cloud LMSs enable organizations to track performance and generate progress reports for individuals automatically. Once the LMS is deployed, the learning process becomes smoother through personalized training, automatic notifications, reports, assessments, certificates, and so on.

Personalized Learning Strategies

AI-based LMS, SAAS or Cloud LMS, etc which combines data collection and technologies such as machine learning, can bring automated and personalized learning strategies to reality by being truly responsive to your learners’ needs. Here are some of the benefits AI brings to the table:

  • Close skills gaps: This gives us the ability to more precisely identify employee skills gaps and suggest the best ways to close them.
  • Proactively Support Learners : To start with, virtual coaches will become smarter and more targeted as they support learners with a positive response to personalized learning and development.
  • Uncover Learning impact : As our most important metric, LMS will help us to collect better and more accurate data on how learning materials are impacting individual and business performance.
  • Interpret Analytics Faster : LMS can collect and interpret a vast amount of data, meaning that you will be able to gather key insights easier than ever.
  • Reduced maintenance : Today, organizations rely on enterprise systems such as CRM, HRMS, and others to train the modern workforce effectively. A technical glitch may hamper the productivity of the system by involving huge costs and effort. So, cloud LMSs enable organizations to track performance and generate progress reports for individuals automatically. Once the LMS is deployed, the learning process becomes smoother through personalized training, automatic notifications, reports, assessments, certificates, and so on.

Impact of Big Data Analytics for Better Learning

Data analytics in eLearning delivers the ability to classify learning elements using attributes and statistical tools to evaluate the mapping between these classifications and expected outputs. Let us take an example of automated learning for content delivery, which is taken by adaptive systems. Such systems change responses to inputs based on data and circumstances. Their efficiency is calculated by their ability to collect data, analyze, evaluate, and process decisions to empower learning.

Through Machine Learning, the system uses neural network algorithms to provide personalized learning paths for learners aligned to their business objectives:

  • Designing dynamic courses that take historical data into account from other employees, as well as facilitators.
  • Recommendations on training courses to study, time invested, and refreshers based on employee’s performance level.
  • Providing feedback to employees based on their learning capability.
  • Providing interventions for mentors based on the progress of employees.
  • Giving awards and certificates when an employee jumps to the next level, from slow tracker to fast learner.

Given a large amount of data available to the organizations, it is possible to proceed with adequate knowledge that allows improving the entire structure. The perfect blend of the latest learning strategies with new paradigms of processing (Big Data) enables content to be changed to optimize the existing personalized learning methods.

Today, big data analytics tracks individual performance, automates assessments, boosts knowledge retention, and increase training ROI. Modern LMSs impart training to thousands of users at a single time to deliver engaging content. In broader terms, LMSs support an adaptive design for better scalability, cheaper training costs, and drive profitable outcomes. Unquestionably, innovation in e-learning trends and technologies is the way forward to attain success, align with relevant training needs, and meet performance goals.