Abstract:

Adaptive learning environments are a subject of recent research in the world. These environments with specific architectures and algorithms are designed to provide instructional materials, similar to learning objects, considering the individual characteristics of each student, such as learning styles, pre-acquired knowledge, student interaction with the access device and material, among others. Examples of such environments are MASPLANG, ARTHUR, iWeaver, CS388 and AHA!.

In the context of such research, we have developed the AdaptMLearning architecture that was designed to be a learning infrastructure for mobile and non-mobile platforms. This architecture provides a selection of learning objects that takes into account as adaptation criteria the following data: the mobile device's technological specification; the student's learning style information, his/her performance and spent time associated to the student's interaction with the learning object; previously acquired knowledge by the student related to the course's content. In addition, it also allows the teacher to interfere in the adaptation criteria used during the study simulation, and allows the student to indicate his/her preferences for media types.

To implement the AdaptMLearning architecture some algorithms using the FSLSM model related to the student's learning styles were developed. The algorithms use the IEEE 1484.12.1 for cataloging learning objects and some of its categories and attributes associated with dimensions of learning styles FSLSM model, are used to compute a weight of an object in each dimension allowing a search of the most appropriate object according to the student's learning styles; and the use of fuzzy computing, considering that the student's learning style can change, determines if the student has to receive reinforcement or need a new study in a particular subject of a course, when the student gets unsatisfactory results in terms of timing and performance in a course's subject.

This paper presents the development and evaluation of a simulator for the AdaptMLearning architecture and their algorithms.

The development of the simulator was performed using: the use case and class diagrams of UML modeling, constructed with astah Community; Java technology with the NetBeans IDE, to create the simulator with graphical user interface for desktop; JFuzzyLogic package, which enables the use of fuzzy computing in Java applications; MySQL Workbench for data modeling; and MySQL as database.

The evaluation of the simulator was done by means of many simulations scenarios considering students with different knowledge, learning styles and preferences for media types; learning objects with several characteristics and types of media; courses with different workloads, number of subjects and keywords; many different access devices as: tablet, smart phone and notebook; several combinations of adaptations involving the student's learning styles, pre-acquired knowledge, performance and technology used access the course's content; and considering different student's timing and performance obtained in the subjects of the courses.

Based on the results obtained from the evaluation it was possible to discuss, analyze and identify the potential use of AdaptMLearning architecture and their algorithms in a real situation for developing a Virtual Learning Environment or its aggregation to an existing environment.

Keywords:

Adaptability, learning objects, learning styles, simulator, fuzzy logic, performance, pre acquired knowledge, technology.