Employers everywhere recognize that training the workforce is a must to equip them with the right skills, keep up with technological advancements and stay ahead of the competition. A future of work projection by McKinsey suggests that by the year 2030, 30 to 40 percent of all workers in developed countries might have to change occupations and/or upgrade their skill sets in order to stay relevant.
But how would L&D managers determine if employees are adequately benefited from the training? How will they ensure that the knowledge transfer is flowing in the right direction so that it positively impacts bottom-line margins?
This is where learning analytics proves to be helpful. Organizations of any size can leverage learning analytics to get more visibility into the outcomes of their training programs. These tools help to design training programs and courses so that they have the maximum impact on learners.
Just as teachers in school measured the progress of their pupils through tests, observations and interactions, and changed their style of teaching accordingly, learning analytics do a similar job in the context of e-learning. By using analytics to track learner progress, courses and assessments can be designed to improve or enhance student progress, and learning methods can be optimized.
Learning Analytics is a marriage between learning and analytics. In other words, it is the use of analytical tools such as statistics, visualization, computer/data sciences, and artificial intelligence in the field of education research, learning, and assessments.
The Society for Learning Analytics Research (SoLAR) defines Learning Analytics as the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimising learning and the environments in which it occurs.
How does it work?
- Data regarding student activity is captured including enrolment, learner feedback, assessment results, time taken, and more
- Data mining, data discovery and other metrics are used to gain insights into the data collected
- Methodologies like Descriptive Analytics, Diagnostic Analytics and Prescriptive Analytics are deployed to discover learning trends and suggest ways to optimise the course material.
What are the benefits of Learning Analytics?
Learning analytics benefit individual learners as well as organizations, allowing them to get detailed insights into the outcomes of the training programs, both in terms of individual performances as well as organizational profitability. Visualization tools and user-friendly dashboards present the data collected in accessible ways that can be easily interpreted even by a layperson.
Not only can this data be used to track individual talent and capabilities, but L&D teams can use the information gleaned from the data to improve training programs and get employee growth on track. A research study by technology media giant IDG Communications indicated that 80% of organizations and 63% of SMBs are already using—or plan to use—learning analytics to enhance L&D outcomes.
Here are some of the benefits of employing Learning Analytics in Employee Upskilling programs.
1. Create a Performance Mindset
Sales-driven organizations require L&D programs that are outcome-based and performance-driven. In other words, they must shift from mere acquisition of knowledge to the delivery of outcomes that offer a measurable ROI.
Learning analytics allow them to map performances and growth using specific sales goals and metrics, and put in place a capabilities model that drives the attainment of those goals. Through integrated L&D content and data-driven sales, integrated analytics could measure the change in capability levels against the progress of the training, clearly measuring the return on the training spend.
2. Use Predictive Analysis on Leadership Development
Leadership development initiatives form an important part of employee upskilling. By targeting potential leaders and grooming their capabilities, organizations can ensure that the top management is equipped to lead growth.
Using predictive analysis to map leader data to business metrics, the outcomes of leadership development programs can be tracked, and learning investments that are most likely to result in business improvement can be prioritized.
3. Predict the Learner's Performance
One of the reasons why learning analytics is such a powerful tool is because it offers powerful insights into the learner’s behaviour.
How is that different from a traditional evaluation? Analytics can help to not just understand about the learner’s current aptitude but also gain insights into their future performance and how they will fare through the progression of the course.
This can help L&D teams to modify or tweak the course or training, suggest methods for improvement, make it more interactive and increase engagement.
4. Give the Learner's a Personalized Experience
Customising courses in accordance with the learning speed of the learner will increase motivation for the learners to remain enrolled and complete their training. Topics that are above their learning level or tough learning paths often demotivate learners and they drop out.
Knowledge creators must know that not all learners are alike. The comprehension capability differs from person to person. Giving the learner a learning environment that exactly matches their needs is a great way to enhance knowledge transfer and ensure that every person gets the learning experience they deserve.
When individual learners are equipped with the right skills, the organization as a whole will grow.
5. Improve Learning Content
Learning analytics will help in the creation of better courses that reach a wider audience base, making it possible to create more comprehensive courses that deliver the right learning at the right time.
The more relevant the course content is, the better it will be received by learners, and the more value it will add to organizations.
6. Lower Training Costs
By understanding what works and what doesn’t, it becomes easier to create learning courses which have maximum efficacy and are mapped to learner needs. If it is found that a particular module is not achieving the required outcomes, it could be modified or improved till it does.
Course creation that is underlined by a solid understanding of the effectiveness of a learning strategy will no longer be based on trial and error, and will reach the desired outcomes. In the long run, this will save on costs and result in happier, more productive learners.
7. Set the Path for Future Learning
Learning analytics are a great tool—not just for current learners but for everyone in the learning pipeline.
Analytics can help to improve aspects of your training or e-learning and set the path for future learning. For example, if learners have found a particular topic difficult to comprehend, it can be designed in a different way, so that future learners do not face the same problems.
Learning analytics have the power to change the way learning content is created and disseminated, and the way in which learners consume knowledge.
With the help of analytics, it is possible to make training more user-focused, personalized and effective. A report by Research and Markets highlights the fact that the global learning analytics market is slated to grow to an astounding $7.1 billion by the year 2023; in step with the increasing need for data-driven decisions in the L&D world.
Learning analytics is indeed the future of learning and teaching; and can be a game changer in the field of corporate training.
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