How to Use Data Analytics to Improve Development and Design of e-Learning Platforms
Learning, development, and training programs are critical parts of an organization that wants to keep its workforce on its toes with the latest market trends and technological evolutions. However, successful and impactful learning and training programs are those that are designed, developed and managed in a way to increase employee productivity.
The impact often measures the success of an e-learning platform it has on improving employee engagement, employee retention, and employee performance and productivity. All of this translates to a better run and a more efficient and competitive organization.
Traditional methods of training and learning like PowerPoint presentations and self-assessments are no more sufficient in today’s age of rapidly evolving advancements in technology especially in fields like AI, Big Data and Data Analytics. Companies that rely solely on these traditional methods in today’s world are bound to find themselves at a significant disadvantage when compared to their peers.
According to research, students and, employees today require and demand intuitive and responsive learning and training opportunities from their institutions and employers respectively. The massive amounts of data available today allow for institutions and organizations to mold their learning platforms and present advantageous and pinpoint learning opportunity with a new level of ‘personalized e-learning’.
With the help of data analytics, the information available today can be collected, interpreted, analyzed and presented in a way that turns a mediocre and mundane training program into a highly personalized, interactive and absorbing one.
Here are some ways to use data analytics to help improve the way e-learning programs and platforms can be designed and developed with today’s requirements in mind.
Strategic Solutions for Digital Learning Development
The benefits of institutional and corporate learning programs are best realized when learning program developers can modify and make use of data analytics to get a better and more detailed insight into the exact requirements. This acts as a guide to improve e-learning materials and make ensure education and training delivery is more efficient and yields better results.
According to Training Industry, data analytics and predictive analytics allows educational and business leaders to customize their training content to match the preferred learning method and style of each. Aptara’s advanced algorithms of e-learning tools are some in the market that allows leaders to get this done.
Using data analytics to improve the effectiveness and engagement of e-learning programs, especially in the corporate arena, allows organizations to enhance employee participation, interaction and engagement. This leads to a higher retention rate and, therefore, a higher return on investment for the organization.
Setting up a cloud environment can also help you boost the architectural design of your application. You no longer have to maintain a self-hosted server. Instead, you will have high-performant compute instances that scale horizontally and vertically. If you’re running on traditional servers, you will need a solid cloud migration strategy to help you through. You can run your analytics, data processing and batch jobs on your cloud server. The storage spaces are also cheaper and you can push your releases faster using the right workflow.
Making Use of the Right Data Analytics
Perhaps the crux of the problem is not that educational and business leaders lack a general understanding of the benefit of big data and data analytics in e-learning solutions. The problem may indeed lie in the knowledge of how to analyze, aggregate, and utilize the correct set of information to their advantage.
According to a research conducted by Forbes, about 60% of survey participants said that limited access to data insights and data scientists and related skills has hampered them from efficiently realizing the advantages of big data and analytics.
PC Magazine recently published an article which detailed the usefulness of using data and predictive analytics for a better insight into business intelligence for corporate as well as educational institutions. More importantly, it also discussed how the learnings from the various analytics exercises can help improve learning and training programs.
Technological advancements in the field of deep learning, neural networking, and related machine learning areas can now take raw data and process them at a higher speed and accuracy than data scientists previously could. Teach leaders like Google and IBM have taken the lead in using these advancements to improve upon their internal and external e-learning platforms.
Harness the Expertise of a Third-Party Supplier
Many organizations and institutions are strapped for resources, time and skills to make practical application of innovations in e-learning software and tools. As mentioned before, the development and design of learning programs and corporate training needs to be specific and tailored to the individual’s needs.
Initiatives concerning instructional design should not be kicked-off without first ensuring that the technology, tools, and analytics related to content development will result in learning and training material that will be beneficial to all members.
Just by providing training and learning material does not necessarily mean that members of an institution or organization will glean the information required of them. To ensure that these materials translate into successful learning for users, the right content needs to be used in an engaging format.
A variety of modalities need to be used for different e-learning platforms that can offer many simulations and formats of content delivery. This would make sure that the appropriate audience can access the required material via a form or channel that they connect with the most.
Thinking Design when Developing e-learning Platforms
The recently popularized idea of combining design thinking with decision science results in an intuitively designed, interactive and engaging e-learning platform. It not only provides a practical as well as a creative way to impart information but also ensures the audience using the learning and training platforms remain at the focus through the entire development stage.
The challenge, however, lies in the fact that following an analytics-driven solution instinctively uses statistical techniques, data, and solutions. If we ensure that the design in any analytics-driven e-learning projects is a priority from the get-go, we should be able to get the right balance of technical feasibility, sensibility, consumer requirements as well as business viability.
Design thinking is not a new concept per se and has been included in the development of many different products and platforms other than e-learning. The essential principle of design thinking is that it keeps the user and their requirements as the focal point when developing a new product, solution or platform. It considers questions like ‘who are we designing for?’, ‘what is the problem the user is facing?’, ‘how can we improve the productivity, effectiveness, and engagement of the existing product or platform?’ etc.
Blending Designing Thinking with Analytics
Design with data analytics can influence the user’s engagement level while also ensuring that the right audience is reached using the format they are most connected with. The end product can be incredibly revolutionary and uncover earlier unknown opportunities for institutions and organizations to reach & engage with a larger user base at a more emotional level.
Use high quality and profoundly analyzed data and use it to create a product or platform that addresses the requirements of users at an individual level
Unlock potentially fantastic business benefits as well as opportunities
Ensure user focus and centricity at all times.
Use Cases for Analytics and Design
In addition to educational and training platforms, many different industries from financial services, to manufacturing, to retail and telecom are starting to understand how crucial design is especially when used in conjunction with big data and analytics. This is mainly in the field of customer focus, reach, engagement and retention.
For example, IBM is collaborating with different organizations to deploy IBM Design Studio and IBM Big Data Platform. It has also developed an innovation framework known as IBM Design Thinking which places the user at the forefront of innovation efforts to solve existing problems.
The combination of Analytics and Design has helped users and customers become a part of the innovation process. From the initial stage of envisioning customer experience to the stage of product planning and release, design thinking and analytical solutions help churn out answers from ideas.
To conclude, the idea of analytics and design thinking is focused mostly on action-oriented solutions and processes. The two can be applied quite easily by people who may not be designers or data scientists.
In addition to e-learning platforms, analytics and design can help in a big way in a multitude of different businesses, industries, and verticals that wish to keep the user or consumer at the forefront of their offerings.