With regard to professional and occupational knowledge and practice, education and decision support have always been close cousins. You may learn your profession as a pharmacist, structural engineer, or urban planner at a university but you will turn to various decision support tools (reference works, manuals, short online tutorials) to deal, in the workplace, with the newest class of drugs, the stress and strength properties of specific materials, or how to implement a geographic information system.
As online, collection-based educational approaches evolve they are converging with systems for professional and occupational decision support. To illustrate the point, I have altered the “ten important concepts” from an earlier post to reflect ten similar (or identical) concepts in collection-based decision support:
- Digital Object – A special purpose calculator, video tutorial, text file, graphic or picture, game, simulation, or other item designed for presentation and often interaction as tutorial or just-in-time learning activity. A good example of a digital object for decision support is this New York Times app for comparing, and learning about, rent vs. buy economics in residential real estate.
- Repositories and Collections – A repository is a location where digital learning objects are stored. A repository may be indexed, like a library or an archive, but is not necessarily structured for a purpose. A collection is a set of digital objects that is structured for decision support purposes. A collection may reside in a single repository, consist entirely of a set of links to digital objects not resident in a single repository, or a blend of both. UpToDate.com is a decision support collection that provides clinicians with “medical knowledge at the point of care.”
- Curator – The person, persons or organization responsible for determining what is included, and what is excluded, in a collection. Like the editor and publisher of a reference work, textbook, or manual the curator of a collection bears responsibility for the scope, currency, veracity, and functional performance of the items in a collection. For example, UpToDate “combines an advanced publishing platform with the rigor of a sophisticated editorial process managed by a faculty of accomplished physician authors and editors, renowned leaders [a.k.a. curators] in their specialties.”
- Content and Media Management Systems – As digital content has exploded, many enterprises have adopted systems to manage the content used in their work. For basic content management, a very common system is Sharepoint from Microsoft but new cloud based models from the likes of Dropbox, Box.net, and Google are increasingly popular. In content management, vendors abound as do open source options. Media management has some similarities to content management but was pioneered by organizations whose product was content. Now also widely used in marketing departments, media management systems are able to gracefully deal with the large file sizes of rich media, their complex intellectual property, the need to track derivative works, and include many other features specifically for managing rich media such as transcoding among formats and packaging multi-part products.
- Decision Support Systems (analogous to Learning Management Systems) – Specialized content management systems with search, recommendation, and cognitive assistance features (see below). Decision support systems organize and present selected digital content as usable knowledge.
- Knowledge Community (similar to a Learning Community)– An online community that enables both peer-to-peer exchange and expert-to-learner exchanges. These are common in customer support, open source software, and corporate knowledge management activities.
- Search and Recommendation Engines (similar to Adaptive Learning Technology) – Increasingly sophisticated search approaches allow an individual to access usable information in digital repositories or collections. A recommendation engine mines search and use data to adapt, customize or personalize the decision support experience for a group or individual. Includes collaborative filtering: “others who bought this item also bought items x, y and z.”
- Gamification – Gamification is the use of techniques and platforms from computer and online gaming for purposes of education or problem solving. It is based on the recognition that computer gaming in all its forms (e.g. online, PC, consoles, casual, etc.) have tremendous reach in terms of usage, and the concomitant technologies of simulation, communication, shared objects, and data can be used to enhance just-in-time learning and decision making.
- Knowledge Representation – Based on a long history as a research field in Artificial Intelligence, Knowledge Representation (KR) focuses on machine readable representation of knowledge such as facts, definitions, relationships, causal factors, and implications. Typically KR systems are able to use a set of facts and knowledge to derive new relationships or knowledge via a reasoning or inference system. In an decision support context, knowledge representation underlies the ability to create question answering capability, derive summaries of material, and form the basis for automated just-in-time learning systems (see Recommendation Engines above and Cognitive Assistance below).
- Cognitive Assistance – Decision support provided by computer-based reasoning, usually manifest as personalized guidance for users in the form of responses to individual queries.
This convergence of the systems for online education and decision support has created a gold rush among publishers, professional societies and industry associations, and professional schools. Just as importantly, as these systems converge and the volume of successful applications grows, the dropping cost and difficulty of system development and deployment opens entirely new areas (smaller markets or those with less ability to pay) to cost-effective application of this technology.