Abstract:

In this globalised world, the extraordinary importance of the World Wide Web as e-business platform emphasizes the educational needs related to information retrieval field. Information retrieval may be defined as the problem of selecting documentary information from storage in response to searches provided by a user in form of queries.

Fuzzy Information Retrieval Systems (FIRS) use the artificial intelligence fuzzy logic tools to improve the retrieval activities. The study of these systems is one of the matters belongs to the degree subject Information Retrieval Systems based on Artificial Intelligence at the Faculty of Library and Information Science (University of Granada). This subject deals with the study and analysis of artificial intelligence tools applied in the design of FIRS. The goal of this course is to learn the foundations of fuzzy tools and genetic algorithms and its application in the design of FIRS. As it is known, both are important soft computing tools and are being satisfactorily applied in the development of the Web access technologies.

It is becoming clear that students have to be competent in these systems. The complex skills that those FIRS provide, mainly by the use of weighted queries and fuzzy connectives, make very hard to show the different semantics that could be associated to the weights of queries together with their respective strategies of query evaluation in a blackboard. Furthermore, students have many problems to full understand the semantics of weights and the evaluation strategies, so they need to make many exercises and compare the results continuously.

The use of computer-supported learning tools may provide students with opportunities to promote their understanding of phenomena in science and to facilitate the visualization of abstract and unobservable concepts. In this sense, the information retrieval is a suitable field to put into practice the computer-supported learning systems. The advantage of using these learning systems is that the students get a realistic feeling of the particular information retrieval systems used and they can develop self-learning processes on typical operations of them.

The specific aim of our work was to improve the understanding of FIRS by students of our subject, facilitating their self-learning processes through the use of a computer-supported tool. We searched the Web and peer-reviewed journals for training information retrieval tools, but we found very few of them, which present several shortcomings, and particularly, it does not exist a FIRS training tool. Therefore, we decided to develop a student-oriented application to overcome the understanding problems related to the different FIRS models. Our learning tool provides an environment for demonstrating the use and performance of weighted queries with different semantics and their evaluations using different fuzzy connectives. Furthermore, the application provides a feedback on the evaluation of weighted queries by means of visual tools, showing internal aspects through evaluations trees and allowing the visual comparison of the evaluation of different weighted queries.

Additionally, we evaluate the performance of its use in the learning process using the students' perceptions and their results in the course’s exams. We observe that with this teaching tool the students learn better the complex skills that those FIRS provide, their motivation is increased, and their performance in exams is improved.

Keywords:

Teaching, Education, Fuzzy Weighted Queries, Fuzzy Connectives, Fuzzy Information Retrieval.