New methods and technologies for enhancing usability and accessibility of educational data

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EDITORIAL

New methods and technologies for enhancing usability and accessibility of educational data David Fonseca1   · Francisco José García‑Peñalvo2   · Jorge D. Camba3 

© Springer-Verlag GmbH Germany, part of Springer Nature 2020

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 [1–5]. 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) [14–16]. Educational data are also the basis for learning analytics [17–19], with an increasing focus on the way educational data are presented [20–22], how users interact with the data [23–26], and data privacy and security [27–30]. 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 [32–34], 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 * Francisco José García‑Peñalvo [email protected] David Fonseca [email protected] Jorge D. Camba [email protected] 1



La Salle, Ramon Llull University, Sant Joan de la Salle 42, 08022 Barcelona, Spain



Computer Science Department, Plaza de los Caídos s/n, 37008 Salamanca, Spain

2

3



Department of Computer Graphics Technology, Purdue University, West Lafayette, IN, USA

which they learn [43], and the effectiveness of the educational approaches [44]. Extracting information from data to ultimately turn it into knowledge [45, 46] can contribute to draw a more comprehensive picture of student’s learning, which can empower students, parents, and educators as well as education stakeholders and policymakers [47]. Educational data usability and accessibility is even more relevant in the context of the global pandemic due to the SARS-CoV-2 virus, which causes COVID-19 disease. This situation is having an unprecedented impact on education. According to UNESCO [48], in the first months of 2020, the pandemic has affected 91.3% of the total number of students enrolled worldwide: over 1.5 billion people have been unable to receive face-to-face instruction because of the closure of schools and universities [49]. The consequences are more severe in emerging countries [50, 51] and to families affected by poverty and risk exclusion [52], presenting digital inequalities [53], and causing exclusion and inequality sit