Learning content discovery is a complex challenge. Employees can access thousands of courses through licenses with content companies. As internal learning teams develop more content with easier-than-ever-to-use authoring tools, libraries grow even larger. And then there’s the internet.
If you’re investing in your company’s learning programs, it’s important to think about how employees will find the programs they need. This is how the learning experience platform market came to be.
I want to cut through some of the hype and give you a sense of how complex this challenge has become. Google has thousands of engineers optimizing search. LXP companies, which may have 10 engineers at most working on this, have to make some choices. Let’s examine our options for guiding learning.
By far the simplest and most useful way to find what you need is to have the company tell you what to learn. This is where most L&D departments start. They build a curriculum of content and tell employees, “Here is your learning path.” This is actually the most powerful step you can take. If you take the time to study the domain, you can build or buy a curriculum, learning path or certification program that gets people to where they need to be.
The focus on self-directed learning has gone too far — most of us simply do not know what we need to know. I also believe the LXP market has gotten way ahead of itself. We now have companies building “flea markets” of learning content, making it harder than ever for employees to decide what to learn. Take the time to validate, build and update your structured (and mandatory) learning paths.
The second option is to guide learning according to skills. Some vendors are now tagging content according to skills categories. But there are pitfalls to this approach. For instance, searches on “Java coding” or “Excel” could turn up hundreds of resources.
Degreed, LinkedIn, EdCast, Percipio and IBM have started to add skills-based discovery tools into their systems. They use other data to inform as well, such as length, media type and popularity. But with the exception of Volley, none attempt to see how deep or complex the content is, so learners have to guess by title how relevant the content will be.
Pluralsight, one of the leading providers of software technical skills programs, has its own learning portal and has built a skills assessment engine called Skill IQ to help match content to an employee’s skill level. IBM, Workday and Gloat try to infer employee skill levels by analyzing job descriptions, emails and other data to recommend content.
While all of this sounds great, it’s very new technology. Ultimately, skills-based discovery is limited by media type and the fact that microlearning is still lacking in most libraries.
The third option is to use Google’s idea of page ranking for learning recommendations. Vendors such as EdCast, SkillSoft, Cornerstone, LinkedIn and Fuse aggregate massive amounts of data to recommend learning based on content use.
This approach also has challenges. When a program is widely used, it also then becomes widely recommended and it starts to “crowd out” other content that might have more value and credibility. The most popular article or course may not be the most useful.
When EdCast started working with NASSCOM and other major institutions, its goal was to create faster and better machine learning recommendations. Edcast now does customized recommendations for each client, as do Degreed, Valamis and CrossKnowledge. Degreed’s new OEM relationship with Harvard Publishing promises to help better understand patterns of use for Harvard’s content. Wiley, the owner of CrossKnowledge and one of the biggest book publishers in the world, is embarking on a data lake project to better recommend content. Fuse lets teams segment themselves into communities so the system can recommend the most popular content within that group. Its clients have found this to be far more relevant than recommendations based on enterprise-wide use.
The fourth approach to discovery is far more innovative and powerful. Volley, Valamis, IBM and Docebo all offer solutions that actually ingest instructional content (text, video, audio), identify and categorize the instruction contained within it, and then create microlearning and personalized recommendations.
Volley’s system can crawl through cybersecurity documentation and “create” training, microlearning and assessments on security procedures for each institution. This approach has enormous potential as its knowledge engine identifies level of expertise and credibility of content through pedagogical analysis. Valamis, which is used by Boeing, can fast-forward to a video segment and show you precisely what to watch based on instructional needs.
Over time, we can expect more learning platforms to do this. But the technology is new and yet to be perfected.
The fifth way to recommend content is through human support: Ask the learner. In an ideal world, your learning platform would know the role and experience of each employee, their learning preferences and goals, and the content they have consumed.
Degreed has worked with clients such as Bank of America to map specific job roles to learning recommendations. IBM’s YourLearning platform does this using IBM’s Watson Talent Frameworks. Filtered’s product Magpie asks employees questions when getting started to inform its engine about the individual’s role, interests, learning needs and skills profile.
The final approach to discovery is to embed learning into mandatory practices at work. Consider programs like anti-money laundering, sexual harassment training or annual compliance programs. These required courses are part of any company’s success, so don’t forget to include them in learning discoveries.
The LXP is not the solution to everything. Creating the right form of discovery is where you earn your pay. As the LXP space grows, make sure you are creating the right types of discovery for the best content you can find. Don’t let your L&D department turn into the training flea market.
Learning technology is changing faster than ever, but the role of humans has not gone away. Only you can build the academy, learning paths or in-the-flow experiences that are right for your company.