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This course addresses the use of artificial intelligence to create computer-based intelligent tutoring systems.
This course addresses the use of Artificial Intelligence to create computer-based Intelligent Tutoring Systems (ITSs). Students will learn theoretical and data-driven methods for creating ITSs. ITSs have been demonstrated to dramatically enhance student learning in many domains, including, to name a few, mathematics, computer science, medicine, biology and engineering. In addition to discussion and readings about methods and models of problem solving, learning, and tutor design, the course will have a "learning by doing" component.
1. Critique key concepts in artificial intelligence in education and the psychology of learning [WA2, WA10]2. Critically assess approaches to student modelling in ITSs [WA2]3. Develop constraints and production rules for use in ITSs [WA3]4. Develop small-scale constraint-based tutors [WA3]5. Critically analyse current research topics in the area of Artificial Intelligence in Education [WA10, WA12]
This course will provide students with an opportunity to develop the Graduate Attributes specified below:
Employable, innovative and enterprising
Students will develop key skills and attributes sought by employers that can be used in a range of applications.
Subject to approval of the Head of Department.
Students must attend one activity from each section.
Tanja Mitrovic
2024
Domestic fee $1,110.00
International Postgraduate fees
* All fees are inclusive of NZ GST or any equivalent overseas tax, and do not include any programme level discount or additional course-related expenses.
For further information see Computer Science and Software Engineering .