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Powering personalized learning experiences with technology

Capgemini
16 Sept 2021

New skills for a new workplace

An organization is only as strong as its people, and people today are facing an unprecedented challenge: skills that were cutting-edge just a few years ago are no longer yielding the same results. Automation and AI are forever transforming the workplace, requiring a comprehensive realignment of abilities. To compete in the near future, most employees will need to master a set of new skills, and they won’t be the same from person to person. How can organizations achieve a personalized learning experience for each employee? The answer lies in technology, and the unparalleled power of data.

In the previous blog of this series, we explored the new trends which are helping organizations to build a best-in-class learning experience by putting learners’ needs front and center. Here we’ll explore how technologies such as VR, AI and data analysis can be leveraged to bring a personalized learning experience to life.

The personalized learning imperative

We live in an age of big data and little time. There’s more information available than ever, but this makes finding the right learning offer very time-consuming. We end up with a scattered sort of knowledge or even give up making the time for learning, which limits long-term growth. The key to each learning experience today is focus. The solution is to use data to target learning at the level of the individual.

The movement towards personalized learning leverages data analytics and AI in order to:

  • identify what the learner needs and which skills he/she should develop
  • suggest learnings for specific skills that will become relevant in the future, or that could simply be of personal interest to this employee
  • measure the impact of certain learning content and formats to drive continuous improvement

By curating learning material down to the level of each employee, organizations can increase workers’ skills faster and with higher engagement. So where does this process of data analysis and curation take place? Here’s where learning platforms come in.

Learning experience platforms – choose wisely

The key channel to bringing an organization’s learning strategy and content to life is its learning platform, and the choice is wider than ever. On the plus side, that means that ever more options are available. However, not all learning platforms are created equal. To choose a learning platform that will succeed in engaging employees, organizations should seek out a platform that is personalized, easy to use and relevant. Consider the learning sources that employees leverage outside of the workplace: employees who are used to checking YouTube to fix their cars have an expectation for well-tested and constantly updated algorithms. If your learning platform lacks intuitive, AI-driven search features and it takes a full minute to load, you have already lost the game (and the learner) to Google. Learning experience platforms integrate and combine credible learning content like skill insights, Learning Management Systems, courses, videos, articles and projects — and match each employee with growth opportunities that fit their unique skills, roles, and goals.

It is also crucial to examine the range of features that a learning platform has before taking your pick. Does it adapt to a learner’s skill level, for example through quick placement testing? Is there a recommendation section similar to Netflix and Amazon? Seemingly small features can make a big difference to a user’s experience, so it’s crucial to test out platforms in advance, and to test them with both trainers and learners.

Transforming complexity into knowledge through personas

Data and AI drive an organization’s learning platform from start to finish. To transform information into practice, organizations need to put a face to complex compilations of data. This can be done using data-based personas. For example, let’s say an automotive company is planning an upskilling program for their team leaders, but they don’t know where to start. In one real-life case, employee data showed that many team leaders in an automotive company were technically savvy, interested in the implementation of new technologies and only have short time slots to learn. They grouped these characteristics into one “person” and gave him a name (let’s say Steven). They went on to create a simple biography for Steven, and a persona was born.  Steven has high technical skills, a broad knowledge of emerging technologies, good interpersonal skills, and expandable collaboration skills. Why is it easier to build a learning journey based on a persona? Steven is more than a collection of traits; we can talk about him like a person, with a defined set of skills and skill levels. Based on this specific gap can be identified and addressed.

Developing personas on a large scale starts with AI and data management strategy, and then moves to the more human skills of interpretation and creativity to flesh out findings. We recommend companies take the following steps:

  • Gather information about learners in terms of general information (e.g. gender, age), skills, knowledge, learning needs and ways of learning. Crucially, this includes information such as how much learning time employees have at their disposal and their preferred learning styles (video, reading, doing)
  • Gain insights from collected learning data using machine learning and AI
  • Segment learners based on skill and behavioral data
  • Create personas for each segment and implement learning journeys for each

A wealth of tools

When it comes to learning technologies, AI and learning platforms barely scratch the surface, and many of the most exciting innovations are just now being developed. Collaborative tools like DEON   or Mural allow employees distributed across the globe to work together on one project in real time. Virtual reality (VR) is enabling chemists to visualize molecules and molecular interactions – aiding in learning and even in the active development of new medicines. It also figures increasingly in training programs, giving learners practice in everything from upcoming technologies to difficult interpersonal situations (without the fear of embarrassment or mistakes that often comes with role-playing activities). On the less exciting but more practical end of the scale, a range of time-management systems help employees make time in their busy schedules to prioritize their learning. All the technology in the world can’t help an employee who doesn’t make the time to use them.

Conclusion

Learners today are trying to drink from a fire hose. They have access to a massive array of innovative learning solutions, but with much to learn and little time, the end result is too often frustration. That’s why today, with all the technological learning tools that organizations have at their disposal, the most important step is to discover and personalize content for each employee, thereby reducing the mass of learning opportunities and making it relevant to the individual. When a learner’s needs and goals are known, the learning tools available today offer an unparalleled learning experience. The fire hose becomes a straw.