داده کاوی آموزشی: بازبینی فرایند ارزیابی در یادگیری الکترونیکی Educational Data Mining: A review of evaluation process in the e-learning

1 Introduction Currently, the process of teaching-and-learning (TL) is strongly supported by educational technologies, which are used in educational environments both in traditional face-to-face classrooms and in online learning platforms (i.e. e-learning). In the last years, technological advancements have given assistance in providing relevant information for all educational actors (students, teachers, coordinators, and administrators) acting in different educational environments, and thereby promoting the quality and innovations in the educational context as highlighted by Wang et al. (2012); Qiu and Lee (2013); Liu and Peng (2013); Yu and Jo (2014). In order to consolidate and achieve the better quality levels in the e-learning environment, it is necessary to continuously evaluate the teaching and learning process by observing its different aspects, such as the level of interaction of the actors involved, the effectiveness of pedagogical actions from the student’s own response and initiative, the use of multimedia resources, the administrative management responsible for institutional policies, and other aspects that influence the learning and development of better cognitive skills and collaborative work, as emphasized by Sankar and Clayton (2010). Due to its relevance, the problem of evaluation of e-learning has attracted the attention of several authors, among them we can cite Liu (2005); Chen (2005); Mahlow et al. (2007); Calinger and Howard (2008). For example, in Liu (2005) the author emphasizes the need to evaluate the learning process in e-learning through factors such as achievement, motivation, and level of student anxiety during the learning process. In Chen (2005), the authors evaluate the student’s learning through their experience, perception, and attitude during learning. The web-based instruction requires a broad and continuous process of evaluation of teaching and learning to ensure its effectiveness, as highlighted by Yubing and Jianping (2010). Nowadays, it is possible to generate a great volume and wide variety of data from educational environments such as those related to academic records, monitoring and assessment, and the records of interactions by e-mails between students and educators/teachers, discussion forums and chats (Romero and Ventura, 2010; Zaiane and Luo, 2001; Adeva et al., 2006; Wang and Meinel, 2007; Sun and Zhao, 2009; Liu et al., 2010; Kechaou et al., 2011). The generated data by educational environments, specifically the data generated by the e-learning platforms, are important sources of information for decision support and improvement of the TL. The improvements can be reached from the students’ data analysis through of their behavior, satisfaction, and performance. The objectives are always addressed to the expansion and advancement of the educational horizons, in order to contribute to the evolution of the educational process.