Recent advances in information and communication technologies (ICTs) have fostered the development of new methods and tools for exploring the increasingly large amounts of data that come from pedagogical domains [1][2][3][4][5]. These data have the potential to transform education into a personalized experience [6, 7] that meets the needs of each individual student [8]. Educational data research is becoming highly relevant in massive online courses [9], especially MOOCs (Massive Open Online Courses) [10-13] and SPOCs (Small Private Online Courses) [14][15][16]. Educational data are also the basis for learning analytics [17][18][19], with an increasing focus on the way educational data are presented [20][21][22], how users interact with the data [23][24][25][26], and data privacy and security [27][28][29][30].There are many types of data that can support student's learning [31], but the type and nature of the data, how they can be accessed, and who can access them, vary significantly. Whether educational data are collected from collaborative learning environments [32][33][34], course management systems [35,36], gamified training applications [37,38], or administrative systems from schools and universities [39-41], valuable properties, patterns, and insights often emerge. When combined with other factors such as timing and context, these factors play an important role in understanding how students learn [42], the settings in