Education is a key factor for achieving long-term economic progress. During the last decades, the Portuguese educational level has improved. However, the statistics keep Portugal at Europe’s tail end due to its high student failure and dropout rates. For example, in 2006 the early school leaving rate in Portugal was 40% for 18 to 24-year-olds, while the European Union average value was just 15%. In particular, failure in the core classes of Mathematics and Portuguese is extremely serious, since they provide fundamental knowledge for the success in the remaining school subjects.

On the other hand, the interest in Business Intelligence /Data Mining, arose due to the advances of Information Technology, leading to an exponential growth of business and organizational databases. All this data holds valuable information, such as trends and patterns, which can be used to improve decision-making and optimize success. Yet, human experts are limited and may overlook important details. Hence, the alternative is to use automated tools to analyze the raw data and extract interesting high-level information for the decision-maker.

The education arena offers a fertile ground for BI applications since there are multiple sources of data and diverse interest groups. For instance, there are several interesting questions for this domain that could be answered using BI/DM techniques: Who are the students taking most credit hours? Who is likely to return for more classes? What type of courses can be offered to attract more students? What are the main reasons for student transfers?
Is it possible to predict student performance? What are the factors that affect student achievement? This paper will focus on the last two questions. Modeling student performance is an important tool for both educators and students since it can help a better understanding of this phenomenon and ultimately improve it. For instance, school professionals could perform corrective measures for weak students.