Big data for monitoring educational systems

This report considers “how advances in big data are likely to transform the context and methodology of monitoring educational systems within a long-term perspective (10-30 years) and impact the evidence based policy development in the sector”, big data are “large amounts of different types of data produced with high velocity from a high number of various types of sources.” Five independent experts were commissioned by Ecorys, responding to themes of: students' privacy, educational equity and efficiency, student tracking, assessment and skills. The experts were asked to consider the “macro perspective on governance on educational systems at all levels from primary, secondary education and tertiary – the latter covering all aspects of tertiary from further, to higher, and to VET”, prioritising primary and secondary levels of education

User Consent in MOOCs – Micro, Meso, and Macro Perspectives

While many strategies for protecting personal privacy rely on regulatory frameworks, consent, and anonymizing data, they are not always effective. Terms and Conditions often lag behind advances in technology, software, and user behaviours, and consent to use data for a range of unclear purposes may be provided unwittingly. As the commercial market for (student) data expands, so does the number of brokers who move, share and sell data across continents and legislative environments. This paper reviews four Massive Open Online Course (MOOC) providers from different geopolitical and regulatory contexts. It explores how consent to collect and use data is described to potential users, and how that consent applies at micro, meso, and macro levels. This paper proposes a need for greater transparency around the implications of users granting consent at the point of registration. Further, it highlights that though MOOC providers have a responsibility to make clear the potential uses and sharing of user data, users themselves should also be more aware and consider how meaningful student agency can be achieved

Modeling intrinsic factors of inclusive engagement in Citizen Science:Insights from the participants’ survey analysis of CSI-COP

Inclusive citizen science is an emerging research topic that has been extensively studied in recent years. However, most of the previous studies focused on the development of theoretical models and practical strategies that scholars can employ to attract diverse populations to their citizen science (CS) projects. Their findings were mostly based on either conceptual ethical frameworks or empirical observations of the scholars after the completion of the specific CS project. Few studies collected socio-demographic and behavioral data of the active citizens involved in a CS project to analyze the diversity of citizens in CS. However, to the best of our knowledge, having reviewed numerous peer-reviewed papers, none of the previous studies attempted to use prospective citizen scientists’ traits to investigate intrinsic factors that may help increase the active engagement and diversity in CS. This paper presents a new inclusive citizen science engagement model based on quantitative analysis of surveys administered to 540 participants of the dedicated free informal education course ‘Your Right to Privacy Online’ (MOOC - a massive online open course) from eight countries in the EU funded project, CSI-COP (Citizen Scientists Investigating Cookies and App GDPR compliance). The surveys were filled out just after completing the training stage and before joining the project as active citizen scientists. Out of the 540 participants who completed the surveys analyzed in this study, only 170 (32%) individuals actively participated as citizen scientists in the project. Therefore, the study attempted to understand what characterizes these participants compared to those who decided to refrain from joining the project after the training stage. This study’s findings revealed several important relationships and predictors for becoming a citizen scientist based on the surveys analysis, such as age, gender, culture, education, Internet accessibility and apps usage, as well as the satisfaction with the MOOC, the mode of training and initial intentions for becoming a citizen scientist. These findings lead to the development of the empirical model for inclusive engagement in CS and enhance the understanding of the internal factors that influence individuals' intention and actual participation as citizen scientists. The devised model offers valuable insights for designing inclusive recruitment strategies, fostering positive learning experiences, addressing technological barriers, bridging the intention-engagement gap, and tailoring engagement strategies to accommodate ethnic and cultural diversity

Internet of Things nella società: ambiti applicativi e problematiche

Con il crescente sviluppo delle tecnologie IoT e la connessione di un numero sempre maggiore di oggetti alla rete, si stanno aprendo nuove possibilità per le aziende e i consumatori, dovute anche all’abbassamento progressivo dei costi di beni e servizi. Questa tesi tratta dell’evoluzione dell’Internet of Things fino ad oggi e delle possibili applicazioni future, evidenziando le soluzioni orientate ad una gestione collaborativa di beni e servizi e considerando, anche da un punto di vista giuridico, le problematiche che più rischiano di frenare lo sviluppo di queste tecnologie in futuro, quali la sicurezza dei sistemi IoT, le questioni di possesso e accesso ai dati di tali sistemi e le preoccupazioni relative alla privacy dei soggetti interessati

Algorithmic Discrimination : A Blueprint for a Legal Analysis

This paper is co-funded by the Erasmus+ Programme of the European Union. The paper reflects the views only of the authors, and the Commission cannot be held responsible for any use which may be made of the information contained therein.Peer reviewedPublisher PD

The Educational Intelligent Economy – Lifelong Learning – A vision for the future

Almost every detail of our lives, where we go, what we do, and with whom is captured as digital data. Technological advancements in cloud computing, artificial intelligence, and data analytics offer the education sector new ways not only to improve policy and processes but also to personalize learning and teaching practice. However, these changes raise fundamental questions around who owns the data, how it might be used, and the consequences of use. The application of Big Data in education can be directed toward a wide range of stakeholders, such as educators, students, policy-makers, institutions, or researchers. It may also have different objectives, such as monitoring, student support, prediction, assessment, feedback, and personalization. This chapter presents the nuances and recent research trends spurred by technological advancements that ave influenced the education sector and highlights the need to look beyond the technical boundaries using a socio-semiotic lens. With the explosion of available information and digital technologies pervading cultural, social, political as well as economic spaces, being a lifelong learner is pivotal for success. However, technology on its own is not sufficient to drive this change. For technology to be successful, it should complement individual learning cultures and education systems. This chapter is broadly divided into two main sections. In the first section, we contemplate a vision for the future, which is deemed possible based on ongoing digital and computing advancements. The second section elaborates the technological, pedagogical, cultural, and political requirements to attain that vision

Compliance of MOOCs and OERs with the new privacy and security EU regulations

[EN] Since their appearance in the early 2000s, Massive Open Online Courses (MOOCs) and Open Educational Resources (OERs) arose among the most important educational priorities. Many top universities worldwide have been involved in the research and direct implementation of this innovative pedagogical approach. Simultaneously with the development and massive deployment of the new learning and teaching method, European regulations responsible for data privacy and protection, and information security have significantly evolved. This paper assesses the compliance of the ten most popular MOOCs and OERs with the General Data Protection Regulation (GDPR) and the Directive on security of network and information systems (NIS Directive). In order to systematically examine their online platforms, a few privacy indicators were outlined and thoroughly observed. Alongside this, the involvement of the open education providers in the NIS Directive was examined. Research findings are presented and elaborated in a way that it makes easy to generate recommendations on how to anticipate the future of open education as a reasonable reaction to global change in the era of rapid technological growth, and at the same time to obey the crucial ethical principles defined by this development.Zdravkova, K. (2019). Compliance of MOOCs and OERs with the new privacy and security EU regulations. En HEAD'19. 5th International Conference on Higher Education Advances. Editorial Universitat Politècnica de València. 159-167. https://doi.org/10.4995/HEAD19.2019.9063OCS15916