Why Content Management is the Bottleneck to Life-Long Learning Courses & How to Fix It

It’s no secret that the global demand for higher education is accelerating. In parallel, we are witnessing rapid growth in the demand for online programs that offer new degrees and certificates in emerging fields. Driving this demand is a workforce skills gap marked by two broad groups: a large population of adults without a degree, and those with degrees who need to reskill to remain relevant in the workplace.

Tim Cook noted last year that nearly 50% of the people Apple hired did not have a college degree. While Cook doesn’t believe that they all need a college degree — Apple was founded by a college dropout as he points out — he does believe that they would all benefit from further education and training for the knowledge and skills businesses are demanding. For Apple, this is software development.

In other industries, it will be other skills that are in demand – many of which cannot be predicted today. Labor-market analysts estimate that 65% of students entering elementary school today will be working in careers and jobs that do not currently exist.

But even without trying to predict what knowledge and skills will be needed in the future, universities are working fast to align their degree and certificate programs to close the gap between skill and career requirements.

Universities are a part of the solution, yet challenges abound.

Innovative universities and colleges are beginning to respond to these issues by embracing lifelong learning models. Many are providing new, agile degrees that are more workforce and student-friendly. They see the rising need for existing workers to nimbly step into the college system in order to re-skill, then nimbly step back into the workplace.

When faced with this rapid innovation cycle, however, universities quickly find themselves face-to-face with seemingly insurmountable obstacles:

  1. Static content with interoperability challenge.
  2. Aligning content to outcomes and measuring those outcomes.
  3. Digital content authoring challenges.
  4. Content discoverability and reuse challenges.

High-quality, university-approved content is expensive and time-consuming and once paired with a delivery platform, becomes even more expensive and time-consuming to move and re-purpose.

Instructional designers face this issue daily – dealing with multiple sources and formats of content, often spending more time copying and pasting content from one delivery platform to another, fixing broken links, and updating outdated material in multiple locations. It’s an inefficient process at best and severely cripples the university from being able to boldly address the issues outlined above.

Universities need a rapid cycle of innovation to bridge the college-workforce gap, improve student outcomes while maintaining affordability, and to make better use of faculty time. Universities need to leverage new learning models to achieve career alignment and application skills. Micro-credentialing, badging to demonstrate industry competencies and standards, competency-based education allowing for personal and accelerated credential attainment, and a recurring revenue business model.

Image 1 - Next-Generation-Learning-Enterprise-Challenges

When it comes to digital content creation, acquisition and storage, universities face many challenges

  • Different types and formats of content
  • Multiple sources
  • Content not tagged or adequately aligned
  • Variety of authoring and assembly tools
  • Accessibility challenges
  • Distributed teams and course development workflows
  • Copyright management
  • Multiple and changing delivery platforms
  • Multiple content stores with no single source of truth
  • Difficulty in centralizing content usage data

Unfortunately, the current technology infrastructure at most institutions doesn’t lend itself to supporting agility and continuous innovation. Institutions face numerous challenges when addressing budget pressures, accreditation needs, and content management, including authoring, storage, and delivery.

Rethinking content architecture and the next-generation learning enterprise.

Image 2 - Foundations-for-Rethinking-Content

So, how can institutions evolve to overcome these challenges? They can achieve this by rethinking content architecture. Online learning is growing, but so is the pressure to improve engagement and demonstrate efficacy and outcomes.

Here are five guiding principles that a university can follow that can result in more agility and flexibility with their content.

  1. Centralized database of taxonomies – Institutions need to create a centralized database of all subject taxonomies, program and course outcomes, and external standards. They need to build relationships between these various taxonomies and create a rich library of metadata. Finally, they should align content to these taxonomies, standards, and outcomes to facilitate search, adaptivity and personalization.
  2. Decoupled Content – Content and data should be decoupled from the content applications and point solutions. This helps make the content flexible and agile. One way to do it is by centralizing content management with a LOR (Learning Object Repository) solution. In the LOR, you can store all published content and references to content that reside in other repositories and in third-party environments. This also allows for easy search and retrieval of content to be used and reused in different product and learning models.
  3. Tagged Content – The next key element is the ability to tag content according to students and events and track them throughout their learning journey. This enables the creation of meaningful content usage data that can help in strategic decision making around instructional design, program design, and content efficacy.
  4. Centrally managed content and data – Centrally managing content and data is key to creating a single source of truth and allows for easy reporting and decision making. The centralized content and data store can be leveraged for creating custom reports and performing data analysis by various stakeholders.
  5. Interoperability – Last but not least is leveraging interoperability, data, and integration standards. The 1EdTech™ Consortium and their member organizations have made valuable contributions with standards like QTI, 1EdTech™ Consortium Common Cartridge, LTI, LTI Resource Search, CASE, and Caliper. Data and content interoperability directly lead to better ROI.

Higher education is at a crossroads and so is online learning. Effective content, data management, and interoperability is the key to creating a highly-sustainable and flexible digital content for next-generation learning models. The optimal approach is taking small, sequential steps in the right direction rather than trying to do it all at once. Adopting a rapid innovation cycle is crucial and the current status quo is no longer an option.

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