Incorporating a workflow model for individualized online learning
Empire State College/State University of New York
New York, USA
Current online learning management systems are designed to improve students' learning and performance significantly, but most systems are still limited to just being online repositories: course contents are organized in modules similar to a file directory.
This type of organization may be relatively easy to navigate, but it can be difficult to retain the natural relationship and integrity among course materials as they are separated from each other by modules. More importantly, this kind of learning management system does not support individualized learning, as each student needs to go through learning activities module by module in an almost identical fashion. This also discourages individualized teaching, as instructors evaluate all students' learning module by module. These issues have particular significance for online students, as the learning management system is often the only interface for them to interact with instructors.
To address these issues, a workflow model that incorporates both teaching and learning perspectives for an online learning management system is proposed in this research. Course materials can still be organized by modules, but these modules are not independent of each other any more. Instead, they are decomposed into various types of learning objects with relationship among them that are described by the proposed workflow model. Each student will have an instantiation of the general workflow, and their workflows can be generated according to different instantiating rules, such as their learning styles, or the intrinsic relationships between these learning activities. The individual instantiation of the workflow of each student is mapped onto the teaching workflow so that instructors can monitor each student's progress, and have a better understanding of their students' overall performance -- and thus individualized learning and teaching can be achieved.
This paper discusses the proposed workflow model and its pilot implementation on the Angel platform at Empire State College/SUNY.