Abstract
This chapter presents a visible, explicit, and reusable risk-driven knowledge capture model that defines a process for supporting collaborative online course creation. The model defines the structure and use of a knowledge base of risks and heuristics for risk mitigation specific to transitioning courses to online. The instantiation of the model with known risks and heuristics is the end result of collaboration that takes place among a community of practitioners which includes experienced online instructors, instructional designers, and subject experts. Experienced practitioners hold within their established mental models of instructional design the theory behind such design. This theory consists of the knowledge behind decisions affecting success or difficulty and heuristics established regarding online course design. Without explicit capture of this knowledge, theories expressing mental models of successful design are lost when expert practitioners leave an organization. This presented model defines a structure and method for the capture and reuse of this knowledge.
TopIntroduction
Experienced online course instructors and course design practitioners hold within their established mental models of instructional design the theory behind their successes and failures. This theory consists of the knowledge driving good course design and the decisions affecting success or difficulty as well as heuristics formed to guide future course design. Without explicit capture of this knowledge theories expressing mental models of successful design are lost when experts leave an organization. The model presented in this chapter defines a knowledge base structure, and the method for the capture of this knowledge and its reuse. The knowledge base structure has been defined specifically for use within online course creation domains. Developing a successful online course requires a minimum of the knowledge of both the course subject matter and how to create an online course product. Such domain knowledge may come from a single expert or many. The knowledge of what kinds of instructional methods, what tools to include for collaboration, what assignment types, what lecture delivery methods to use, are all examples of knowledge that make up the knowledge domain of online course creation. This knowledge resides in the mental model of the domain expert; the person, or group, that has created and taught online courses over a long-standing period and has acquired a mental model of expert knowledge regarding such real-world practice. For this knowledge to be applied and reused in the absence of an expert it must be captured and documented. Such a model has not been defined for course creation as it has for product creation within domains such as software development. Within software development domains, critical software development requires the use of prescribed knowledge reuse processes to create successful software products (Drew & White, 1999; White 1996a, 1996b). In these environments, experienced software development domain experts, as well as subject domain experts, are consulted as to what is needed, what has been successfully applied, what is essential to success of the product, and what are the most important issues to recognize (White, 1995, 1996a, 1996b). Such domain knowledge can be collected and documented within an environment designed to support such knowledge capture. One example is the risk driven software development process offered by Fairbanks (Fairbanks, 2010a. 2010b). Another is the spiral process development model developed by Boehm (Boehm, 1986). Boehm’s spiral model made risk-knowledge capture and use explicit and inherent to the model. In general, a risk-driven process for software development prescribes the requirements that must be met from a risk-based perspective as defined by domain experts. The risk knowledge includes the identification of the risks, pitfalls to avoid to reduce or mitigate risks, the probability of risks occurring, and the impact of risk upon the success of the project if the risk occurs. The priority of risk reduction drives the requirements implementation schedule; which requirements are high priority and must be implemented first, later, or last. Risk priority is defined by the domain expert and the expert specifies the requirements that must be implemented to address the risks. This results in a risk driven process for developing a project that is based upon an experts past knowledge of similar projects, increasing the probability of delivering a quality reliable product.
Key Terms in this Chapter
Product Increment: A product can be produced in stages of implementation resulting in parts of a product, referred to as an increment, being completed at a time. Over time the increments combine until the entire product is complete.
Domain: An area of study or field of practice which someone has knowledge of or experience within.
Online Course: A university level course that is taken over the internet without the need for attendance in a physical location to order to access materials or the instructor. All instruction is done with the use of a computer and internet service and interaction may include synchronous as well as asynchronous activity.
Knowledge Base: A stored set of retrievable information representing facts, rules, assumptions, actions, and consequences that can be used to enable problem solving.
Risk Management: A set of activities that are undertaken to recognize risks and to plan for their avoidance, reduction, or removal.
Domain Model: A representation of an area of study or field of practices by way of defining the vocabulary, rules, actors, and actions that take place within that domain.
Risk: A risk is an activity or event that if it occurs, can cause compromise the success of a project.