Four ways to personalise learning with and without using technology
Personalised learning, where the learner receives specific training to fill a skills gap rather than enrolling on a series of standard incremental programmes, is gaining traction in learning and development (L&D) circles. For HR departments struggling to recruit new employees with the right skill set, personalised learning enables them to upskill their employees quickly. However, personalised learning often operates outside the framework of formally recognised qualifications.
The language of the day that underpins these efforts is the language of skills, and organisations are eager to find ways to identify, track and develop skills in their people; just as employees are eager to find ways to clearly describe and demonstrate the skills that they have to offer.
When an employee joins an organisation, they are usually known to have skills related to the job they are being hired into but it is likely that they have other skills as well. In today’s tight labor market, it is beneficial for organisations to find ways to uncover and leverage those additional skills. Likewise, when an employee leaves an organisation, they are not only taking with them the skills they were using in their latest role but also other skills. Not much attention has been paid to an employees’ skills outside their current role but it is time for that to change.
Technological innovations are exploding in this area of talent intelligence. For example, artificial intelligence (AI) is being used to identify adjacent skills and propose career paths and personalised learning. The concept of blockchaining, the establishment of an authoritative database that allows multiple groups to contribute and use data in an orderly and authorised way, has been proposed to support individuals in their personalised learning journey as they move between organisations – it’s an efficient way to provide verification of what skills and certification an employee has no matter where or when they obtained them. But there’s still a long way to go before universal adoption of blockchaining or a similar technology makes this a viable resource.
These technologies, though promising, are not yet widely used, nor is there a universal standard that would allow easy transfer of skills intelligence across organisations and even industries. That time is coming, though, and there are some things that organisations and individuals can do even without advanced technology to lay the groundwork for the scalability that technology brings. These suggestions include a mix of no or low technology approach, with a few that include technology.
Four organisational strategies to implement
- Help employees identify the skills they have
The language of skills is still relatively new. Develop fluency by:
- Writing job descriptions using the language of skills, ideally referencing an established skills taxonomy such as O*NET. Connect job tasks with the skills required to perform them, so that employees can describe their current role using the language of skills.
- Offering assessments to determine mastery – This can help prove the presence of a skill, and also can establish skills that an employee may have outside their current role.
- Surveys – ask the skills question. Help employees begin to think about skills by raising their awareness through self-evaluation, as well as multi-rater feedback.
- Help employees identify the skills they need or want
Identifying skills to develop may come from combining what skills the organisation needs its employees to have with those skills an employee wants. To do this:
- Make sure job descriptions across your organisation include clearly named and described skills. This helps the organisation to assess overall skill needs and trends (AI can help here too!), as well as helping individuals clearly identify their skill gaps based on their career interests
- Have conversations. Managers can ask their people both what skills they see as important for their roles now and in the future, as well as what skills they are personally interested in developing. Certainly there are technologies that can analyse and track this, but even a simple spreadsheet is a place to start.
- Help employees find ways to develop skills
Whether you adhere to the 70-20-10 model or some other approach to training and development, it is clear that there are multiple ways that skills can and should be developed. To do this:
- Translate any existing training’s learning objectives into skills developed makes it easier for managers and employees to identify relevant training
- Develop talent marketplace systems. Still fairly new but quickly expanding, talent marketplace systems harness the power of AI to connect employees (and their skills) to projects and roles within the organisation to benefit the org, the individual, or both.
- Help employees to track the skills they develop
A tracking system saves time and effort for both the org and the individual and does not need to be complicated. Organisation can use:
- Assessments. Useful in uncovering existing skills, assessments are also an important part of demonstrating mastery of a newly developed skill
- xAPIs and LRS. Typical LMS systems track traditional training but are not as good at capturing other developmental experiences. xAPIs allow tracking and analyzing of things like project work, mentoring, reading books. They are not yet widely used but are increasing.
- Digital badging systems like Credly or Badgr. Digital credentials through systems like these provide a verification, which can be a benefit over simple self-report.
In his recent remarks at the HR Tech Conference in Las Vegas, analyst Josh Bersin said that the skills technology area has been disappointing thus far because of the sheer size and complexity of the issue but there is cause for hope . He mentioned exciting growth in three families of skills technologies; skills engines embedded into an app, skills middleware that are trying to facilitate sharing of skills data across apps, and talent intelligence platforms that amass data and use AI to infer adjacent skills and career pathways, etc.
While these kinds of technologies may soon be ubiquitous, we are not there yet. In the meantime, use the suggestions above to train yourself and your employees in the language of skills and begin building a foundation for identifying, developing, and tracking skills and needed skills in individuals and across whole organisations. This will provide immediate benefits as well as setting you up well for future scalability in the skills and personalization space.
Dr Tanya Boyd, pictured below, is learning experience architect at Insights