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Map Driven Learning in Enterprise Systems- DevLearn 2013- Precursor

Author: Shrikant Pattathil

Posted On Oct 16, 2013   |   2 Mins Read

How to organize and present a content knowledge base that is sufficiently large and highly unstructured? Also, given the amount of digital data that is getting generated, is this problem only going to get worse over the period of time?

Before we get into the solutions, let’s look at some traditional approaches of organizing and presenting a content knowledge base.

Linear

  • Topics are organized and presented as an ordered list with one or two levels of classification
  • This is the easiest option to implement and highly recommended if the knowledge base is static and not very complex (e.g. curriculum).

Hierarchical/ Tree Based

  • Topics are grouped into categories and sub-categories (n-levels) and presented hierarchically in the form of a tree (e.g. domain specific literature)
  • Tree based navigation is intuitive and applicable almost everywhere. However, as the data grows, the categories also grow and it becomes less and less intuitive for the learner to navigate. Some relationships between topics may not be possible to represent in a tree-based structure.

Tag Cloud

  • As the content grows and topics become more unstructured, hierarchical organization becomes more difficult. In such scenarios, organizing and presenting the knowledge base as a tag cloud can help solve some of the navigation and discovery problems (e.g. Blogs, Websites).
  • This method allows discovery of topics based on trends, recommendations, likes etc. which is a powerful method of discovering relevant and interesting content. The major disadvantage of tag clouds, however, is that there is almost zero navigation and inter-relationships between topics is hard to represent.

All the above approaches can be further extended in terms of accommodating a larger knowledge base by having a powerful “search” feature within the application. Search helps the learner to narrow down the scope of discovery.

Based on our recent experiences, we believe “Map Driven Learning” is the new emerging technique for representing an ever- expanding knowledge base, which is large and unstructured. At the upcoming DevLearn 2013 conference, at Las Vegas, we are speaking about ‘Map-driven Learning in Enterprise Systems’ on October 25, 2013, at 8.30 AM – 9:30 AM at Expo Block 6. We are going to explain how “map driven” approach can help enterprises organize their exponentially growing knowledge base in a very intuitive and discoverable manner catering to the future demands of the learners.

Forward-Deployed Engineering

Additional Perspectives on the FDE Model

Forward-deployed engineering is gaining attention as a way to bring engineers closer to customer problems and real-world implementation. Several organizations describe this model as a way to align engineering work with customer needs, systems, and workflows. Here are a few resources that offer additional perspectives on the FDE model:https://www.griddynamics.com/glossary/forward-deployed-engineering

https://miragemetrics.com/guides/forward-deployed-engineering

https://www.cognizant.com/us/en/glossary/forward-deployed-engineer

https://fde.academy/blog

About Harbinger Group

Harbinger Group is a global Advisory-Led Performance Enablement company. For more than three decades, we’ve partnered with organizations in the people business, helping Enterprises, B2B SaaS vendors, and Digital Publishers close the gap between where workforce and learning performance is today and where it needs to be.
We work across Workforce Technology and Digital Learning domains. In each, we diagnose the friction limiting performance first, then engineer the fix, combining strategic advisory with digital product engineering and eLearning content development to deliver solutions built around the workflows, metrics, and outcomes each workforce owns.
Our pedigree in product engineering and digital learning has built a culture of continuous learning. We apply technologies like Agentic AI where they deliver measurable performance gains for our customers not because they’re new, but because they close the gap.

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