ASPIRE is an authoring system that supports teachers in developing Intelligent Tutoring Systems (ITSs) for their courses. Intelligent Tutoring Systems are knowledge-based, adaptive systems the goal of which is to simulate the behaviour of a good human teacher. These systems typically support the student while learning problem-solving skills in a particular instructional domain. An ITS tracks the student's behaviour, analyses the behavioural data and produces/maintains a model of the student's knowledge. This model is later used to adapt instructional sessions towards the needs, learning abilities and preferences of the student. ITSs are knowledge-based because they contain explicitly represented domain knowledge, which can be used to analyse students' solutions against, and/or to solve problems given to students. The generated student model is used to tailor pedagogical decisions, such as selecting/generating problems and feedback.
Although numerous ITSs have been developed, only a few of them are used in real classrooms. This problem comes from the fact that ITSs are complex systems, which require a lot of time, resources and knowledge to be developed. Some researchers estimate the time needed to develop one hour of instruction within an ITS to be around 300 hours. It is therefore not surprising that authoring systems are sorely needed in the area of ITSs. Authoring systems support and/or automate the process of ITS development, by making it possible for a non-computer specialist to develop ITSs.
The goal of ASPIRE is to make the development of new ITSs possible even for people without extensive experience in programming and artificial intelligence. ASPIRE supports the process of developing ITSs by automating some tasks, and supporting the remaining tasks, thus making it possible for tertiary teachers with little background in programming and Artificial Intelligence to develop systems for their courses. The resulting educational systems will overcome the deficiencies of existing distance learning courses and support deep learning.
The ASPIRE project is funded by the e-Learning Collaborative Development Fund grants 502 and 592.