Authoring Platform
The Challenge
The new ecosystem relied on machine learning and large quantities of meta-data to create associations between all the pieces of the system. We determined that existing authoring systems were not up to the task. The university had several authoring systems but they had issues. They could create content but they would need significant work to associate the meta-data and make the content reusable. Traditionally content authoring is done in a Learning Management System (LMS). Traditional LMS systems are entirely self-contained: the content is authored, delivered, and assessed, and the achievements are stored. These systems are not designed to be broken apart into more efficient scalable components. Lastly, the university systems had become brittle and we knew that adding more to them would not result in a system that was usable or stable. There were other things that we needed the system to support:
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- Create course modules
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- Create Assessments
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- Support localization
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- Support business logic for course pathways
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- Construct course, certificate, and degree pathways
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- An approval workflow for multiple departments
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- Crowd-sourced content creation
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- Third-party content
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- Construct and maintain meta-data
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- Associations with content, assessments, and pathways
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- Injest and associate careers, degrees, and achievements
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- Injest and associate skills and competencies
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- Construct and maintain meta-data
Constraints
- Greenfield project
- Contract developers
- Six-month deadline
- Built on top of Alpha work for course and pathway structure
Our Users
We knew this was a multi-phase project so for the first phase the authoring platform had three primary users:
- Assessment authors – writing the assessments, and associating the skills and competencies, and the rubrics for evaluation
- Learning experience engineers – assembling the course pathway, the business logic for completion and branching, and creating placeholders for content
- Data architect – build and maintain the canonical lists of meta-data and their external associations
The secondary users for later phases were:
- Registrar – Approval of course, and pathways to meet the requirements for the achievements
- Subject matter experts – Content validation and creation
- Faculty and third-party authors – Crowd-sourced content creation
Solution
Authoring Platform
There are four main workflows in the authoring platform:
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- MetaData Manager – Meta-data utilized across the eco-system that ties content, pathways, assessments, and achievements together
- Content Builder – Building the chunked content of each lesson or module that will be sequenced into pathways
- Assessment Builder – Building summative, and formative assessments that evaluate the skills and competencies of the learners resulting in achievements
- Pathway Builder – Assembling all the pieces along with context objects that provide custom segues for reusable content modules
Each part of this platform builds a specific aspect of the learning experience. In addition, the design patterns used in the pathway builder can be reused to create courses, as well as certificates, or degrees. Each of these is just a set of learning modules taken in a certain sequence to accomplish a goal. In fact, because of the metadata, and the dependency logic, learners should be able to take coursework in any order. As long as the underlying concepts are mastered, it shouldn’t matter which order they take modules in. This flexibility supported the goals of the overall eco-system to provide personalized learning experiences that supported learners in their individual time and learning style constraints.
The critical differentiators in this system from other authoring systems, apart from the robustness and modularity, are the meta-data and the context objects.
Meta-Data Driven
Meta-data associations drive the entire ecosystem. By creating a canonical and extensible data structure we envisioned creating a flexible structure of course content that was loosely associated via the underlying meta-data. This would allow us to swap different courses, and entire pathways, but still fulfill the specific requirements for the achievement. As an example, if two different courses fulfill the same requirement, they can be interchanged. So a learner does not have to take the specific course in the pathway definition, they could take a boot camp course, or bring in external credit from a different university and the system adjusts the pathway to account for these changes. This was the ultimate in personalized learning experiences.
Context Objects
Context objects added a novel flair to the reusable learning object (RLO) paradigm. The training and LMS market has been trying to solve the RLO problem for decades (I’ve worked for multiple companies trying to resolve this issue over the years). The real issue comes down to context. For example, a learning module discussing color theory would be written one way for interior designers, and a different way for graphic designers. You could write the content to specifically address each discipline’s needs resulting in two courses, or write it so generically that it’s not all that useful for either because the use cases would be missing.
Our solution was context objects. If you can swap out specific examples based on the course’s context that course could be reused for both disciplines. The psychology of color and the cultural influences are the same for both disciplines, but mentioning Pantone colors to interior designers, or fabric sheen to graphic designers is irrelevant and distracting. Context objects can be swapped in to make the content more relevant, and targeted to each audience.
Pathway Associations
Pathway patterns were also reusable. The authoring of order and relationships for objects is useful for all the different types of pathways. A content module has a sequence of content, and there are opportunities to assess a learner’s knowledge and allow them to advance. For Learning pathways passing a content module unlocks steps along a pathway, and there are dependancies along the path requiring specific knowledge to continue. These same dependencies apply to courses, and degrees, but on a larger scale.
“Passing” an assessment, or being awarded credit for knowing the content checks the box for the skill, and the competency, and that unlocks, or bypasses steps along the pathway. With all the steps unlocked the learner is awarded the achievement: course credit, certificate, or a degree.
This system also facilitates the stacking of credit/credentials to achieve larger goals, like degrees.
Builder Patterns
During the early design phase, I wireframed some of the patterns and anti-patterns I had worked through on similar projects in the past. These patterns were designed to inform the content authoring design team and give them a head start.
The Results
Phases
This project was mid-design when the university closed the department due to financial issues outside the control of the team. We had completed the underlying strategy and had started designing the main authoring modules, as well as the meta-data structure and management system.
Success Metrics
Our key metrics for success were:
- Are Learning modules reusable?
- Can pathways account for interchangeable content modules or pathways?
- Can meta-data drive the logic of the pathways and achievements?
- Does the authoring system support the business and academic processes of the university?
Reflections
It is unfortunate that this project didn’t get further along. It had such a potential to impact not only the higher-education market but the K12 and LMS market as well. As stated above reusable learning has been the holy grail of LMS systems for decades, and the personalized learning paradigm is being attempted by numerous companies. Our key differentiator was that we were building a system from the ground up to support this instead of trying to repurpose something that was never intended to have this deep interconnectedness built in.