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) [10,11,12,13] 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 [39,40,41], 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 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 situations in vulnerable groups, ethnic minorities, and people with disabilities [54]. Significant challenges have been reported in the online transformation of educational activities [55, 56], particularly assessment processes [57].

Consequently, it is vital to improve access to educational technologies and reduce gaps in use and literacy [58]. A multi-disciplinary approach is required to deploy technological ecosystems [59, 60] that favor blended or online training, teacher and student training for the efficient use of educational technologies [61], and policies for both government and academic leaders to define strategies and manage uncertain scenarios [62]. In the context of educational data access, it is critical to ensure transparency, ethics, and individuals’ rights.

This UAIS special issue builds on the work started in a number of previous special issues [63,64,65,66] and two international events:

  • The invited session entitled “Emerging interactive systems for education”, in the thematic area “Learning and Collaboration Technologies”, in the context of the 21st HCI International Conference 2019, in Orlando, USA, with 25 papers accepted [67, 68].

  • The organization of the 7th Edition of Technological Ecosystems for Enhancing Multiculturality, in León (Spain), with more than 200 presentations [69].

This special issue focuses on how to improve universal access to educational data, with emphasis on (a) new technologies and associated data in educational contexts: artificial intelligence systems [70], robotics [71,72,73], augmented [74,75,76] and virtual reality (VR) [77,78,79,80,81], and educational data integration and management [82]; (b) the role of data in the digital transformation and future of higher education: Personal Learning Environments (PLE) [83, 84], mobile PLE [85, 86], stealth assessment [87], technology-supported collaboration and teamwork in educational environments [88], and student’s engagement and interactions [89, 90]; (c) user and case studies on ICTs in education [91, 92]; (d) educational data in serious games and gamification: gamification design [93,94,95,96], serious game mechanics for education [97, 98], ubiquitous/pervasive gaming [99], and game-based learning and teaching programming [100, 101]; and (e) educational data visualization and data mining [102]: learning analytics [103], knowledge discovery [104], user experience [105, 106], social impact [107], good practices [108], and accessibility [109, 110].

The special issue comprises the following 11 accepted papers.

Collaborative learning systems are a niche for analyzing educational data. For example, virtual reality and 3D modeling applications can leverage the integration of collaborative approaches in Medicine [111], Architecture [112], or Urbanism [113]. Huang et al. developed a study devoted to construct a 3D modeling practice field based on virtual reality technology, in which students can learn 3D modeling through a new VR design collaboration framework and complete design goals. The proposed design collaboration model includes the concept of a learning community. The results of this study indicate that the system usability of the VR modeling practice field is superior to that of the traditional modeling learning field and learners are more creative and motivated. The authors emphasize that through the new design collaboration model, students can effectively learn 3D modeling in VR. Conde et al. explore the assessment of instant messaging tools for the acquisition of teamwork competence throughout a case study about the use of the instant messaging app WhatsApp. From the results, the authors conclude that students prefer instant messaging tools in teamwork activities over other interaction tools such as forums; and that the use of those tools has a positive impact on students’ grades.

In an effort to demonstrate the potential of virtual worlds in education [114], especially in distance education [115], Krassmann et al. introduce a framework to prepare the implementation of virtual worlds. Their approach emphasizes requirements that distance education students need to meet in order to have a successful learning experience. The authors present an exploratory study and propose eight guidelines to harness the potential of the technology of virtual worlds for distance education.

Pervasive games [116] enhance the gaming experience and level of engagement by including real world aspects into the game space. Arango-López et al. propose GeoPGD, a methodology that integrates the design of geolocated narrative as the core of the game experience. This methodology guides designers and developers through the different stages of building a pervasive game by providing tools for defining the narrative components, places, and interactions between the user and the game.

Gallego-Durán et al. tackle the challenges of learning programming as a universal ability [117, 118]. The authors propose a radically different perspective to this issue, teaching students with a bottom-up approach, starting from machine code and assembly programming. Their results suggest that such a small intervention could have a limited positive influence on the students’ programming skills.

Pazmiño et al. did a systematic literature review [119] to answer the question: What is the baseline of scientific documents on learning analytics in Ecuador? The selected documents were analyzed using Statistical Implicative Analysis after removing duplicates and applying inclusion, exclusion, and quality criteria. The outcome of this research has allowed building up a baseline of scientific knowledge about learning analytics in Ecuador.

User experience analysis in the educational realm is directly linked to the levels of user acceptance and satisfaction [120] of the new wave of educational technological ecosystems and the personalization of learning [121]. Barneche-Naya and Hernández-Ibañez describe the results of a case study intended to compare three different user movement paradigms (metaphoric, symbolic and natural) designed to control the visit to virtual environments for a NUI-based museum installation. The study evaluates the performance of each movement scheme with respect to the navigation of the environment, the degree of intuitiveness perceived by the users, and the overall user experience. The results show that the natural movement scheme stands out as the most adequate for the contemplation of the virtual environment and the most balanced at a general level for the three variables considered. The symbolic scheme proved to be the most efficient. The natural movement and symbolic schemes appear to be the most appropriate to navigate digital environments such as museum installations. In another paper related to user experience, Zardari et al. introduce an e-learning portal for higher education that was assessed from a user experience standpoint using an eye-tracking system. The results emphasize students’ satisfaction with the learning portal. Finally, Toborda et al. analyze metrics to measure effectiveness and engagement levels in pervasive gaming experiences.

Regarding the analytics of accessibility, Martins et al. present a study that assesses accessibility in mobile applications, which may be applicable to education and tourism [122]. Fourteen mobile applications were analyzed using a manual and automatic methodology through an evaluation model based on quantitative and qualitative requirements, as well as the use of features such as VoiceOver and TalkBack. The results show a high number of errors in most quantitative requirements as well as non-compliance with most qualitative requirements. Also, in the context of accessibility, Romero Yesa et al. share a good practice in designing accessible educational resources [123]. The authors developed a new virtual teaching unit for supporting classroom teaching based on usability and accessibility criteria. The goal is to help increase teaching quality by improving syllabus design.