Shahnaz N. SHAHBAZOVA
Biography
Shahnaz N. Shahbazova is an associate professor in the faculty of Information Technology and Programming at the Azerbaijan Technical University. She became a Candidate of Technical Sciences in 1995, and associate professor in 1996. She is a member of Berkeley Initiative in Soft Computing (BISC) group. Doctor of Philosophy in Engineering Sciences, International Personnel Academy UNESCO, since 2000. Starting 2002, she is an academician of the Azerbaijan Modern National Academy named by L. Zadeh.
Her research interests include Artificial Intelligence, Soft Computing, Intelligent System and Fuzzy Neural Network.
Award Grants: India (1998), Germany-DAAD (1999), Germany-DAAD (2003), USA UC-Berkeley Fulbright (2006/2007), Germany-DAAD (2010).
Talk
Intellectual Information Learning and Control of Knowledge System (IILCKS): Overview and Implementation
Abstract:
This talk is about the application of mathematical technologies and methods of analysis, as well as information modeling techniques to development and implementation of a system for comprehensive learning process. The system uses intelligent models and methods for continuous guiding and monitoring of students’ learning processes.
The presentation focuses on the description of main building blocks responsible for practical effectiveness of the learning procedures offered by the system. These blocks “provide” intellectual instructions and exercises for a student with the minimal involvement of teachers and educational institutions.
The talk describes the selected solutions for determining the students’ levels of knowledge. It presents the algorithm for estimating knowledge levels based on a set of sample questions corresponding to the current levels of knowledge of participated students. The algorithm also allows for determining the basic misconceptions and knowledge gaps.
The performance of this algorithm – using the smallest possible number of questions – is comparable to the traditional survey methods conducted by teachers.
The proposed algorithm is based on the FNN and is coupled with a knowledge base. Its decision-making power brings a new level of quality to the decision and selection processes. Thanks to the flexibility and transparency of its logic, it can be easily adopted to virtually any educational material.
The IILCKS presents the outcome of the learning process in a visually appealing way – a student card. The card allows an instructor to assess the volume and quality of student’s learning processes in a matter of seconds.
The results of analysis of the IILCKS system are presented.