Scenario-based learning turns compliance policy into decision practice through realistic cases, plausible choices, and feedback that explains the decisive cue.
Browse fresh analysis, customer stories, and best practices to keep your teams audit-ready.
Each year, organizations and thought leaders release their lists of key trends shaping the future of learning and development (L&D). As we examined the 2025 L&D trend articles shared across blogs, newsletters, and social media, three trends consistently emerged as the most popular:
Discover how Drillster adaptive microlearning accelerates progression through the four stages of competence from unconscious incompetence to unconscious mastery with assessment-based learning and spaced repetition.
You are thrilled to have finished a training course. Two weeks later, while trying to apply the new competencies, you seem to have forgotten everything. Do you recognize this?
In today’s rapidly evolving job market, one of the most significant challenges faced by companies across various sectors is the shortage of qualified staff. This shortage exacerbates the need for efficient onboarding and continuous training processes. The traditional model of employee induction and recurrent training is often time-consuming and one-size-fits-all. It treats all employees similarly, regardless of their existing knowledge and skills. This is where adaptive learning technology comes into play as a solution that can significantly shorten the learning curve and anchor and retain crucial competencies year-round. This enhances productivity and reduces the time it takes to get and keep employees proficient.
AI. AI. AI. Everything is AI these days, especially the generative kind. And that’s good because we encourage innovative developments. However, it’s important to talk about didactic AI as well. While generative AI helps you with information, it doesn’t necessarily facilitate better and more effective learning. Didactic AI does. In this article, we explain what it is, why it is useful, and how you can benefit from it.
Adaptive learning, a method where learning content is personalized for the learner, is often associated with ‘directed learning’ or ‘push learning’. People believe that the development, anchoring, and retention of crucial competencies in an adaptive way leaves little room for a learner to choose whether to engage with the proposed learning object. However, adaptive learning can also be used for ‘pull learning’ or ‘self-directed learning’. Let’s dive a little deeper into the applicability of adaptive learning in both push and pull learning scenarios.
