Jeepers. L&D Had It Right for the Market

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A revolution isn’t coming to L&D. It’s already here. If you’re reading this, you’re probably already looking to overhaul antiquated processes and systems to deal with new learning paradigms. But you don’t have to toss out everything you know about L&D just yet. For all the talk about what needs to change, I’d like to focus a moment on what L&D has been doing right for years: concentrating on the details of learning design.


The Learning Model Canvas

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For the past several weeks in the Saltbox Savvy blog series, I’ve outlined the most prevalent corporate learning models, including the challenges and benefits businesses face implementing them. Organizations can always pick and choose components of different models that work for them, and individual divisions and business units may pursue different learning goals. But the most successful learning organizations align around a primary model.


The point is not that one model is better than any another; every business has different training needs. What is important is that the chosen model is planned, realistic, and achieves the desired business outcome. The increasing ubiquity of technology in the workplace has changed user expectations for faster and deeper learning experiences. Businesses have responded by exploring and adapting to new learning models. But that begs the question: How does an organization choose a model, and how do they get there once they’ve chosen?

Setting Up and Managing Multiple LRS Accounts

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Using a single LRS account for development, production, or multiple customers can be quite complicated and lead to unintended consequences. Your data is not properly separated, reporting is not accurate, and you probably don’t want development and production data mixed together in the same LRS.

Wax LRS sub-accounts make it possible for you to manage multiple LRS sites under the hood of a single billed parent LRS account. You can logically separate your LRS data for development, QA, production, or per customer, and each sub-account inherits all the features and capabilities of the parent account. It’s as easy as picking a name and clicking a button.


Introducing Wax LRS for Learning Platform Providers: A White-Labeled LRS and Reporting Engine

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You offer your customers a tried and true learning platform like an LMS, corporate university, customer training portal, or training delivery system. Your platform does a number of things really well, but Learning & Development (L&D) organizations are beginning to look for solutions that incorporate learning beyond the traditional boundaries of your platform. Customers are asking if you support the Experience API (xAPI) or if you offer a Learning Record Store (LRS). You’ve probably even started exploring your options to integrate the xAPI and and LRS, but not sure how to proceed. What you really need is a way to support your customer needs and differentiate your platform in a sea of others.

That’s why we’re offering a new and unique solution, specifically tailored for you. Announcing Wax LRS for Learning Platform Providers.


A Data Lover Reads ‘Telling Training’s Story’ (Part One)

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TL;DR — first in a read-along series; tension between high worth of training and development, low esteem held for L&D sustained by difficulty communicating results effectively; existing complicated methods make that even harder even if they work, but that doesn’t mean give up on data.

I recently read Robert Brinkerhoff’s Telling Training’s Story for the first time, some months after flipping through and being impressed by another of his books at a conference. The book details Brinkerhoff’s Success Case Method as a framework to approach L&D program evaluation, including step by step processes, then explicates via case studies. I really like how the book’s strong theoretical model rests on very practical foundations that integrate the need to check data for accuracy, construct a viable business narrative, and motivate specific steps for improvement. Many other theoretical models for learning are weak in exactly these areas, which hamstring their applied use.


The 5 Learning Models: Mass Distribution

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Last week I introduced the Performance Support learning model with its emphasis on Information Dissemination under urgent time constraints. Meanwhile, other organizations may similarly spend the majority of their resources on providing content, but do so on somewhat longer time frames. They are likely operating in the Mass Distribution learning model.