Intelligent Learning Material Delivery Agent (ILMDA)
Traditionally, learning materials are delivered in a textual format and on paper. For example, a learning module on a topic may include a description (or a tutorial) of the topic, a few examples illustrating the topic, and one or more exercise problems to gauge how well the students have achieved the expected understanding of the topic. The delivery mechanism of these learning materials has traditionally been via textbooks and/or instructions provided by a teacher. A teacher, for example, may provide a few pages of notes about a topic, explain the topic for a few minutes, discuss a couple of examples, and then give some exercise problems as homework. During the delivery, students ask questions and the teacher attempt to answer the questions accordingly. Thus, the delivery is interactive: the teacher learns how well the students have mastered the topic, and the students clarify their understanding of the topic. In a traditional classroom of a relatively small size, the above scenario can be ideal. However, when e-learning approaches such as distance learning and asynchronous learning are involved, or in the case of a large class size, the traditional delivery mechanism is no longer effective:
- In distance learning, the teacher and the students may participate from multiple locations. The feedback loop between the teacher and the students may sometimes be broken. Thus, there is a need for an alternative delivery that adapts to the students’ behavior.
- In asynchronous learning, the learning materials may be available 24 hours a day, 7 days a week. The teacher is not necessarily present. A student may visit a Website and view a learning module whenever he or she wants. Thus, there is a need to design a software tutor that is flexible.
- In the case of a large class size, not only is the number of students an issue, but the diversity of the students tends to make it impossible for the teacher to cater to all of the students. Some students may need one-to-one attention that the teacher cannot afford to offer. Thus, there is a need for individualized, customized delivery of learning materials.
In the Intelligent Learning Module Delivery Agent (ILMDA) Project, we are attempting to build an agent specifically designed to deliver learning modules. Each learning module consists of three components: (a) a tutorial (e.g., What is permutation?), (b) a set of related examples, and (c) a set of exercise problems to test the student’s understanding of the topic. Based on how a student goes through the module and his or her profile, an ILMDA will pick appropriate examples and exercise problems for the student. In this manner, the ILMDA will customize the learning object. Most software tutors or learning delivery mechanisms are able to do this, with or without agent-based technology. The uniqueness of our project stems from:
- Its modularization of the course content and the delivery mechanism,
- Its utilization of true agent intelligence where an agent is able to learn how to deliver its learning module better, and
- Its own accountability of usefulness for evaluation.
