Meet “Amy,” who has been working as a product developer in a technology company. Yesterday, she was promoted into a product manager role and immediately updated her LinkedIn profile to reflect her new job. Today, as she checks her email, she sees a message from her “Lifelong Learning University” (LLU) virtual advisor: recommendations for new professional development content.
When she logs into the LLU portal, Amy learns that her virtual advisor has recommended two learning modules: how product managers can influence people without authority and how to implement a go-to-market plan. One module is from a business school professor while another is from a noted product management author. Amy also receives offers from two mentors willing to work with her one-on-one.
The learning modules and mentors were selected by an algorithm that matched Amy’s profile against a repository of content modules and mentors. After Amy completes the mini-modules, her learning record stored in a blockchain ledger is updated and automatically shared on her LinkedIn profile as well as with her HR department. And it all happens through her $99-a-month subscription to LLU.
Sound like a fantasy? While lifelong learning hasn’t yet reached the level of Amy’s experience with the hypothetical LLU, elements of this vision exist today in the software and online services world. For example, Netflix uses machine learning algorithms in its recommendations systemto offer personalized recommendations for streaming content; Uber matches providers of ride-sharing services with riders in an open marketplace; Adobe sells software as a subscription service, and startups such as Accredible use blockchain technology to create and manage digital certificates for training programs.
By transferring these innovations to the world of learning, we can paint a picture of learning that is personalized, adaptive and ongoing. Here are 5 ways learning institutions can adapt to deliver on this vision of lifelong learning.
- Design: Learning ObjectsCurrently, the basic unit of learning is a “course,” and the only customization is choosing one course over another. In today’s learning paradigm, Amy would have to take a one-week classroom-based course at a business school for $10,000. Or she could enroll in an eight-week online course on product management for $2,000. In both cases, she must sit through content on product development that she already knows. That’s like paying $29.99 for an “all-you-can-eat” restaurant buffet when she only wants a $2.99 cup of coffee. To become more customizable, lifelong learning must be designed using a new unit of learning that I call “learning objects” – a concept that draws inspiration from “object-oriented programming” (OOP). OOP leads to modularity and decoupling of program objects as software is developed in small, relatively autonomous modules. Similarly, courses can be decoupled into smaller units for greater customization. Instead of offering a course composed of ten modules, each with six to eight key concepts, a more granular approach would be to offer 100 “learning objects” on a specific topic—each self-contained in terms of content, exercises, and assessments. These learning modules can be logically sequenced and combined to create larger learning modules.
- Personalization: Recommendation EnginesOnce learning is deconstructed into modular learning objects, they can be matched to learners using recommendation engines driven by artificial intelligence (AI)—just as Netflix generates movie recommendations. Based on how the learning objects are tagged (content, applicability for specific job roles, industries, or seniority levels) and the learner’s profile (seniority, companies, industry, job role, learning credentials and geography), the AI algorithm would match learning objects to learners. It would also take into account consumption behavior and the rating of the learning objects by each learner. Over time, as more learners consume content, the recommendation engine would get “smarter” and improve in accuracy. In Amy’s case, if she changed jobs or changed industries, LLU’s algorithms would adapt and produce new recommendations.
- Delivery: Subscription ServicesLearning today is delivered episodically – you get a degree and then you are “done” for several years, until you enroll in a continuing education course. This mirrors the “premise-based software” model where you pay an up-front fee for a perpetual license and wait for several years to get the new version of the software. The software industry has moved rapidly to software as a service (SaaS). For example, Microsoft sells Office 365 for a monthly subscription fee, which enables users to receive continuous improvements with new features and enhancements. Similarly, learning needs to evolve to allow learners to continuously upgrade their skills and knowledge—and not wait several years for a “knowledge upgrade.” Amy, thanks to her lifelong learning subscription with LLU, receives a continuous feed of updated content. That’s not only beneficial for Amy, but it also allows institutions to gain new streams of revenue and more lifelong learners, especially alumni.
- Content: Open MarketplacesAs an LLU “subscriber,” Amy can tap into an “Uberized” marketplace that allows access to the best providers to match her needs. LLU functions like a third-party learning platform, offering learning objects from multiple content providers. In this learning marketplace, the “best of the best” in terms of content and instructors would rise to the top, allowing learners everywhere to access superior instruction—not just those who attend a particular institution. This is already occurring with online education platforms such as Emeritus, which offers content sourced from leading business schools. As more third-party learning platforms emerge, faculty “stars” will no longer be confined by the walls of their institutions but will be able to reach students anywhere in the world. For institutions, such scalability offers opportunities to reallocate teaching resources. Instead of creating their own content, second-tier and third-tier institutions could license world-class content from leading institutions for a royalty and complement this content with high-touch instructors and teaching assistants.
- Certification: Blockchain LedgersAs Amy completes learning modules, an immutable and verifiable record of what she has learned must prove her credentials to her current and potential employers. Her college degree and list of courses is too monolithic. Certification must become granular with micro-certification for each successfully completed learning object. These micro-certificates can be stored in a blockchain ledger, which can be selectively accessed by employers. One new entrant in the certification space is Blockcerts, developed by MIT and Learning Machine, a learning credential that is cryptographically signed and shareable.
This vision of lifelong learning challenges educational institutions to adapt their development and delivery models and employers to create customized learning journeys for employees. The future of lifelong learning will look very much like the software and content industries look like today. Educational institutions have a choice – they can disrupt themselves or be disrupted by startup companies who can create Learning as a Service (LaaS) by applying software innovations to the learning business.