Alberto Salguero

Factors influencing university drop out rates

This paper develops personalized models for different university degrees to obtain the risk of each student abandoning his degree and analyzes the profile for undergraduates that abandon the degree. In this study three faculties located in Granada, South of Spain, were involved. In Software Engineering three university degrees with 10,844 students, in humanities nineteen university degrees with 39,241 students and in Economic Sciences five university degrees with 25,745 students were considered. Data, corresponding to the period 1992 onwards, are used to obtain a model of logistic regression for each faculty which represents them satisfactorily. These models and the framework data show that certain variables appear repeatedly in the explanation of the drop out in all of the faculties. These variables are, among others, start age, the fathers and mothers studies, academic performance, success, average mark in the degree and the access form and in some cases also, the number of rounds needed to pass. Students with weak educational strategies and without persistence to achieve their aims in life have low academic performance and low success rates and this implies a high risk of abandoning the degree. The results suggest that each university centre could consider similar models to elaborate a particular action plan to help lower the drop out rate reducing costs and efforts. As concluded in this paper, the profile of the students who tend to abandon their studies is dependent on the subject studied. For this reason, a general methodology based on a Data Warehouse architecture is proposed. This architecture does most of the work automatically and is general enough to be used at any university centre because it only takes into account the usual data the students provide when registered in a course and their grades throughout the years.

Easing the Definition of N---Ary Relations for Supporting Spatio---Temporal Models in OWL

There are many issues to overcome when integrating different data sources due to the number of variables that are involved in the integration phase. However we are interested in the integration of temporal and spatial information due to the nature of modern Information Systems. We have previously developed a model, called STOWL, which is a spatio-temporal extension of OWL. We use this model as the common model for defining the schemes of the data sources in order to ease their integration. This paper presents the part of STOWL which has to do with the definition of n-ary relations.

Fuzzy integration of web data sources for data warehousing

In this paper we show our work related to an approach for monitoring web sources on the World Wide Web using its temporal properties in order to integrate them in a temporal Data Warehouse. We use these temporal properties obtained for integrating data more efficiently from different data sources according to the requirements of the Data Warehouse administrator. For this integration process we proposed a parallel fuzzy temporal semantic algorithm based on a flexible query language called FSQL in order to obtain more precise data in the Data Warehouse. In addition, we show an application applied to tourism area where data integrated into Data Warehouse can be used to schedule personalized travel as a value-added service for electronic commerce.

Application of data warehouse and Decision Support System in soaring site recommendation

Data Warehouse (DW) technology is a new discipline, which has not yet been broadly applied to tourism area, and in the soaring field (paragliding, sailplane, hang gliding, etc) in particular. Site selection process depends on a number of factors, making it a complex decision-making task. It is common for the decision makers to use their subjective judgment and gut feelings based on their experience in selecting the most appropriate place for soaring. The reason is that data for place selection originate from varied sources and are not organized in a format that decision makers can readily use to derive any meaningful information. To solve this problem, the integration of a data warehouse and a Decision Support System (DSS) seems to be efficient to help retrieve data from different databases and information sources and analyze them in order to provide useful and explicit information. Data warehousing is based on online analytical processing (OLAP) concept. The users can also generate data trends over a period of time to make any forecasts. In this paper we will describe how new information technology techniques as data warehousing can be used in the tourism industry. How to analyze the successes and failures of finished gliding routes and how to use the existing data to analyze patterns and trends for new gliding are the problems we have to face.

dmFSQL: a Server for Data Mining

At present, we have proceeded to extend SQL into a new language called dmFSQL (data mining fuzzy structured query language) which can be used to solve real problems of data mining. In this paper, we present an architecture that presents us to use this language dmFSQL for Oraclecopy database. This enables us to evaluate the process of data mining at both a theoretical and a practical level. Thus, we use the proposed system to solve a real problem of direct marketing management. We consider that this model satisfies the requirements of data mining systems.

E-learning platform as a teaching support in psychology

Increasingly, e-learning platforms are being implemented at various educational levels as a form of teaching support. In addition to promoting flexibility in teaching and to permitting the incorporation of new educational materials and resources, e-learning aims to familiarize students with the use of the computer as a work tool. The present paper describes an experiment involving the construction and adaptation of an e-learning platform to the teaching of psychology at university level. The paper presents findings concerning the use of the platform by students and the relation between this use and academic performance in two courses over two complete academic years. Results show that students who take advantage of the virtual educational platforms generally present a higher level of participation and academic achievement.

STOWL: An OWL Extension for Facilitating the Definition of Taxonomies in Spatio-temporal Ontologies

The spatio-temporal information is becoming more popular day by day. Well known web services (google maps, virtual earth...) make this type of information available to the public. On the other hand the Web is tending to the Semantic Web. The OWL language, the ontology description language the Semantic Web is based on, lacks some of the desired features for representing spatio- temporal information. We have developed an OWL extension which tries to encompass this issue. In this work we focus on how the OWL language has been extended in order to consider properties for defining taxonomies.

Applying fuzzy data mining for soaring area selection

Soaring is a recreational activity and competitive sport where individuals fly un-powered aircrafts known as gliders. Soaring place selection process depends on a number of factors, resulting in a complex decision-making task. In this paper, we propose the use of the dmFSQL language for fuzzy queries as one of the techniques of Data Mining, which can be used to solve the problem of offering the better place for soaring given the environment conditions and customer characteristics. After doing a process of clustering and characterization of a Customers Database in a Data Warehouse we are able of classify next customer in a cluster and offer an answer according it.

Fuzzy logic for the performance assessment of the innovation management in tourism

The innovative performance of companies has been studied quite extensively for a long period of time. However, the results of those studies have not yet led to a generally accepted indicator of innovative performance or a methodology to assess Innovation Management. This paper assumed the multidimensionality of the Innovation Management as an outcome of complex interactions. Because of this, it is proposed a design of a methodology to assess Innovation Management based on principles of the Fuzzy Logic. The established methodology stages constitute a guide to develop Innovation Management assessment. In the research development, it was necessary to contextualize, in the conditions of the touristic sector, the theories, models and systems used in the analyzed subject.

System of Indicators in the Innovation Management: Business Intelligence Applied to Tourism

The work presents an approach to study mechanisms that allows managers the Innovation Management (IM) measurements. It is assumed, as main motivation, the analysis of patterns for the design of an integral system of indicators. A methodology that integrates the thought process, focusing on the Business Intelligence and the Balance Scorecard will be presented. A group of indexes based on the multidimensionality of IM in organizations of the sector of tourism is proposed. To approach this quality it is necessary to contextualize, in the conditions of sectoral operation, the theories, models and systems used in our approach. It has been used intervention methods like experts’ criteria, consensus search techniques by means of surveys, consultation of documents, and statistical methods such as analysis of the main components.