BESC special sessions

Summary form only given. Data mining provides educational institutions the capability to explore, visualize and analyze large amounts of data in order to reveal valuable patterns in students´ learning behaviors without having to resort to traditional survey methods (Hung & Crooks, 2009; Abdous & He, 2011). Turning raw data into useful information and knowledge also enables educational institutions to improve teaching and learning practices, and to facilitate the decision-making process in educational settings. Thus, educational data mining is becoming an increasingly important research area with a specific focus to exploit the abundant data generated by various educational systems for enhancing teaching, learning and decision making (Romero & Ventura, 2007; Baker & Yacef, 2009; Romero and Ventura , 2010). According to the Educational Data Mining community website (www.educationaldatamining.org), educational data mining (EDM) is defined to be "an emerging discipline, concerned with developing methods for exploring the unique types of data that come from educational settings, and using those methods to better understand students, and the settings which they learn in".