Data-driven Design Evolution

Instructional Designers at FACT support all the instructors from the departments to which they have been assigned. Because the instructor is the Subject Matter Expert and the course facilitator (SME/F), they are involved in all of the ADDIE phases. We have created the Data-driven Design Evolution to guide the process of creating original course designs, and course redesigns, in this unique context.

Here is an excerpt from a chapter that my colleagues and I have in publication:

"An ongoing relationship between an ID and a SME/F may lead to an evolution of the course design. Ideally this evolution would be the result of evidence derived from course data that led to changes in the SME/F's pedagogical beliefs. We have created the term “data-driven design evolution” to describe this process. We propose a three-stage model in which the course design shifts from “SME/F-driven” towards “learner-driven”.

In Stage I, there is an insufficient quality of course data to justify changes to the course design decisions/revisions based on learner feedback. This occurs in courses which have yet to be delivered, but it may also be the result of an insufficient quantity of course data. The ID creates a course design based on instructional alignment between the SME/F's pedagogical beliefs and assumptions about learners.

In Stage II, the quality of the course data is high enough to identify learner characteristics that can replace the SME/F's assumptions. The ID provides the SME/F with evidence based on course data that demonstrates instructional alignment or misalignment. When the evidence produces a shift in the SME/F’s pedagogical beliefs, the ID recommends changes to the course design that will increase instructional alignment, and implements the approved changes.

In Stage III, the increase in the quality of the course data has led to a fundamental shift in the SME/F's pedagogical beliefs. He or she has become willing to learner feedback drive design changes to the course. The ID assists the SME/F in interpreting the learner feedback from the latest cohort of learners by using the entire set of course data to control for anomalies. The ID recommends changes and implements the approved changes."

Reference:


Joeckel III, G.L.; Jeon, T.; Gardner, J. (2009). Instructional Challenges in Higher Education Online Courses Delivered Through A Learning Management System By Subject Matter Experts. In H. Song (Ed.), Distance Learning Technology, Current Instruction, and the Future of Education: Applications of Today, Practices of Tomorrow, Idea Group Publishing, New York. Chapter accepted for publication.

OAR model

The OAR model is an Instructional Design model created for a specific context: distance education courses delivered through a LMS (Learning Management System) in higher education.

This is an excerpt from a chapter which my colleagues and I have in publication:

"The OAR model is a visual tool which represents the components of SME-F (Subject-Matter Expert facilitated) online courses in higher education, and their relationship to each other. The OAR model was developed to meet four criteria: a) maintain a strict focus on our particular learning system context, b) create a simple graphic-based aid which facilitates communication among design stakeholders, c) remain inclusive by avoiding the use of jargon, and d) represent the basic order of operations in our ID (Instructional Design) process. The OAR model has proven effective in meeting these criteria by organizing the components of SME-F online courses in higher education into three domains: Resources, Objectives and Activities.

The OAR model defines resources as the physical, electronic and intellectual assets with which a course can be created. These resources are determined by an analysis of the learners, SME/F (Subject Matter Expert/facilitator), ID (Instructional Designer), learning and performing environments, available instructional technology, and other relevant contextual factors associated with a course. IDs and SME/Fs use the results of this analysis to identify real-world problems and tasks to inform the design of objectives.

The objectives domain contains the learning and performance goals that are designed to guide the course. Objectives determine which resources will be delivered to influence learner behavior under specified conditions to meet defined criteria. Opportunities for learners to accomplish the objectives are created through activities that are as closely aligned with real-world problems and tasks as the available resources will allow.

Activities are the actual events that learners engage in to acquire and develop new knowledge and skills. At a minimum, these events involve an agent (most often the learner, but at times the facilitator) following an objective to engage with a resource. Activities are primarily delivered by a LMS and are facilitated and assessed by the SME/F."

Reference:

Joeckel III, G.L.; Jeon, T.; Gardner, J. (2009). Instructional Challenges in Higher Education Online Courses Delivered Through A Learning Management System By Subject Matter Experts. In H. Song (Ed.), Distance Learning Technology, Current Instruction, and the Future of Education: Applications of Today, Practices of Tomorrow, Idea Group Publishing, New York. Chapter accepted for publication.