INDIACo m-2009 Co mputing For Nation Development

ABSTRAC

Improving AEH courses through log analysis

Authoring in adaptive educational hypermedia environment is complex activity. In order to promote a wider application of this technology, the teachers and course designers need specific methods and tools for supporting their work. In that sense, data mining is a promising technology. In fact, data mining techniques have already been used in E-learning systems, but most of the times their application is oriented to provide better support to students; little work has been done for assisting adaptive hypermedia authors through data mining. In this paper we present a proposal for using data mining for improving an adaptive hypermedia system. A tool implementing the proposed approach is also presented, along with examples of how data mining technology can assist teachers.This work has been partially funded by the Spanish Ministry of Science and Education through project HADA (TIN2007-64716). The first author is also funded by Fundación Carolina

Impact of different pre-processing tasks on effective identification of users’ behavioral patterns in web-based educational system

Abstract Analyzing the unique types of data that come from educational systems can help find the most effective structure of the elearning courses, optimize the learning content, recommend the most suitable learning path based on student's behavior, or provide more personalized environment. We focus only on the processes involved in the data preparation stage of web usage mining. Our objective is to specify the inevitable steps that are required for obtaining valid data from the stored logs of the webbased educational system. We compare three datasets of different quality obtained from logs of the web-based educational system and pre-processed in different ways: data with identified users' sessions and data with the reconstructed path among course activities. We try to assess the impact of these advanced techniques of data pre-processing on the quantity and quality of the extracted rules that represent the learners' behavioral patterns in a web-based educational system. The results confirm some initial assumptions, but they also show that the path reconstruction among visited activities in e-leaning course has not statistically significant effect on quality and quantity of the extracted rules

Proposta de uma framework para desenvolvimento de sistemas tutores inteligentes

Dissertação de Mestrado em Sistemas de InformaçãoEste trabalho reflecte um levantamento sobre a área dos Sistemas Tutores Inteligentes, focando a sua evolução e características típicas. As arquitecturas propostas por vários investigadores são referenciadas, e a arquitectura clássica é detalhada em cada um dos seus módulos constituintes. É feita uma breve análise ao desenvolvimento de Sistemas Tutores Inteligentes, analisando as debilidades e pontos fortes de cada sistema. Tendo por base o estudo efectuado, é proposta uma Framework de Desenvolvimento de Sistemas Tutores Inteligentes que procura precisamente colmatar essas debilidades, mantendo as boas práticas de desenvolvimento, incorporando as características desejáveis que foram identificadas, no sentido de “apontar o caminho” para o que se designou como uma nova geração de Sistemas Tutores Inteligentes.In this work a survey in the field of Intelligent Tutoring Systems is done, focusing their evolution and main typical characteristics. Some of the Intelligent Tutoring Systems architectures proposed by researchers in the field are briefly enumerated and explained, and the classical architecture is detailed in each of its component modules. The development of Intelligent Tutoring Systems, together with some of the systems developed so far, is used to identify the weakness and strong issues of each system. A development Framework for Intelligent Tutoring Systems is proposed, which tries to address those weaknesses and incorporate the desirable characteristics that wore identified, in order to “show the way” to what was named “The New Generation of Intelligent Tutoring Systems”