Featured Speaker: Dr. Xiangen Hu, University of Memphis
- When: 11:30am-1:00pm, Thursday, January 29th, 2009
- Where: FedEx Institute of Technology, Room 405
Much e-learning content has been produced and is being delivered as uninspiring page-turners. Although advanced learning technologies such as Intelligent Tutoring Systems (ITSs) have been shown to produce signicant learning gains, it is prohibitively expensive to convert existing e-learning content into more interactive learning environments. In this paper we describe a process that may produce greater learning gains with existing e-learning content with minimal conversion time and expense. We call this ITS-enhanced delivery of shared content objects (SCOs). This process was developed by the research associates of the Workforce ADL Co-Lab at the University of Memphis. It is based on years of extensive research and development in cognitive learning theory, human tutoring, ITSs, and other advanced learning systems. The prototype we will present is supported by a contract from the Joint ADL Co-Lab.
The core of this process is a lightweight natural language processing (NLP) component that can be added to any SCO. In this process, the following scenario occurs: A student is participating in page-turning instruction. The learning management system (LMS) asks the student a question about the content. The NLP component understands the students response and oers meaningful feedback. The LMS requires the student to re ect, explain, or otherwise spend more time with the content. The resulting enhanced instructional content is a SCO that can be delivered in any SCORM-conformant LMS. The pedagogical foundation guiding the interaction between the student and the LMS is based on analysis of hundreds of hours of human tutoring and numerous studies of eective ITSs (including AutoTutor, developed by our Workforce ADL Co-lab research associates). Our paper will describe implementation of the NLP component, communication between API and LMS, and the feedback process for the student. We will demonstrate some enhanced SCOs that are used in the current Joint Knowledge Online (JKO) initiative.