This contribution aims to investigate and explore the connection between studies in the field of Learning Analytics (LA) in academic education and the ethical principles and guidelines for data processing, presenting some of the initial findings from the Project of Significant National Interest (PRIN) titled “Learning Analytics. Across data processing ethics, instructional design, and academic policy,” funded by the European Union–Next Generation EU, Mission 4 Component 1, CUP H53D230095900.

The research project is carried out in the field of LA, an area that combines technical data analysis with ethical and policy considerations for the use of educational data. The goal is to create a model that ethically uses data to improve education quality, particularly in the context of lifelong and university learning, where e-learning has expanded the use of data to evaluate course effectiveness. By integrating machine learning techniques, LA analyze student interactions on educational platforms but also raises ethical concerns regarding the handling of sensitive data. In this sense, the project aims to define a balanced approach that meets the needs of researchers, designers, academic policymakers, students, and European regulations.

Specifically, this contribution reports on a literature review aimed at exploring the close relationship between LA and ethics in data processing, as well as the implications and impact of this connection in the field of academic policies.

The potential of LA in higher education has long sparked growing interest in academic contexts. LA, primarily designed to analyze and interpret student behavior within educational settings, provide integrated data that can guide the adoption of innovative teaching-learning models, the organization of educational contexts, and strategies for personalization.

In recent years, an increasing number of universities have adopted LA systems to monitor students' academic progress, predict potential future behaviors, and even identify potential issues at an early stage. However, the use of these systems requires adherence to and respect for ethical principles and values, which primarily concern the data ownership and the privacy of students, in compliance with current legislation.

These aspects require reflection on the regulatory frameworks that may impact the use of LA in the European academic context. Regulations in this field aim to ensure that the adoption of LA technologies complies with ethical principles and data protection regulations, safeguarding the rights of those involved. In this regard, the General Data Protection Regulation (GDPR) serves as the main reference in Europe for the management of personal data, imposing stringent obligations in terms of informed consent, transparency, and data protection. Academic institutions must therefore collect and process student data responsibly, ensuring that students are informed about the intended use of their data and that they can withdraw consent at any time.

This highlights the need to delve deeper into the implications of these issues to develop guidelines for academic institutions to regulate the use of LA techniques in compliance with ethical principles.

Keywords: Learning analytics, higher education, data ethics, education quality.