Learning Technology Services That Connect Your L&D Ecosystem

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Learning Technology FAQ

• What comprises the learning tech ecosystem? ​

  A learning tech ecosystem, also referred to as a learning tech stack, is a collection of interrelated technologies that work together to support learning and development (L&D) initiatives within an organization. It’s more than just a single platform; it’s a  multi-layered suite of tools designed to address various learning needs. Technologies in the stack may include the following components: learning management system (LMS),learning experience platform (LXP),learning content management system (LCMS), authoring tools, learning records store (LRS), and specialty platforms for microlearning, adaptive learning, etc.​

• What Are the Typical Problems with LMS Platforms?

  The Learning Management System (LMS) is often an organization’s single biggest investment in corporate learning and development. This is a problem because, once that investment is made, it is unlikely the organization will reinvest in a new platform anytime soon. These systems not only deliver learning, but they also track learner data, provide reporting, and structure the learning experience. Frustration with the LMS often comes from the constraints and limitations they impose on these seemingly simple functions. They may also constrain user engagement, limit personalization, or struggle to incorporate the full range of learning modalities and formats. Of course, it doesn’t need to be this way. You can solve many of these problems without replacing your LMS.

• With Which Systems Can You Integrate?

  Key integrations in your learning tech ecosystem may include the learning management system (LMS), a learning content management system (LCMS), a learning experience platform (LXP), or a human resources information system (HRIS). These systems may also be integrated with specialty applications for skills management, gamification, microlearning, video learning, adaptive learning, and more. It’s important to realize that there are different strategies for integration and you need to ensure the right strategy to achieve your objectives.

• Are you using AI for learning? ​

  Artificial intelligence (AI) is revamping corporate learning, tailoring the experience to individual needs. AI can analyze learner data to suggest personalized learning paths, with content and microlearning modules that match strengths, weaknesses, and preferred learning styles. This goes beyond static courses – AI can adapt the difficulty and pace of materials in real-time based on a learner’s performance, keeping them engaged and challenged. Furthermore, AI-powered chatbots and virtual assistants are emerging as 24/7 support systems, answering questions and providing feedback on practice exercises. The future holds even more exciting possibilities. Imagine AI automatically creating personalized learning content or crafting immersive VR/AR simulations for practicing complex skills. AI’s ability to predict future skill needs within an organization allows L&D leaders to be more proactive, ensuring training programs stay ahead of the curve. In short, AI has the potential to transform corporate learning into a dynamic and personalized experience that empowers employees to excel.​

• How Can We Get the Learning Analytics We Need?

  One of the best ways to ensure that you have access to the right learning analytics is to align your needs and measurements in the earliest stages of program design. It can be difficult if there are no baseline metrics, but you can use pre-assessments in the absence of a good baseline. Common categories of learning analytics include training efficacy, learner confidence, learner engagement, knowledge acquisition, skills proficiency, time-to-competency, etc. The data that supports these analytics often comes from the LMS but it may also come from external tools, assessment engines, surveys, simulations, or manager evaluations. By analyzing this data, L&D leaders can identify priorities, improve learning programs, personalize learning, and calculate the value of the program, often measured as return on investment (ROI).