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Drawn from the SQELT Erasmus+ project, this article explores how learning analytics is implemented at a set of six European universities in the context of their performance data management models, including its multiple functions and ethical issues. It further identifies possible good practice and policy recommendations at decision-making level. Results show that learning analytics is present to a certain extent in all six institutions, although mostly based on traditional data and still lacking predictive capacity concerning students' performance. Learning analytics is viewed as useful in providing more accurate personal data on students' learning, contributing to the establishment of more sophisticated quality management systems. The European General Data Protection Regulation and national privacy laws sufficiently cover the majority of data ethics risks posed by learning analytics. Overall, learning analytics entails both opportunities and threats. The possibilities of a learning analytics approach deserve further attention within universities and quality assurance agencies. [ABSTRACT FROM AUTHOR]

Academics’ support for quality assurance (QA) depends on several factors, including their sense of ownership, which seems to be influenced by academics’ participation in QA’s implementation. This paper aims to understand whether this participation is indeed contributing to academics’ ownership of QA. Findings from a survey of Portuguese academics’ on their participation in study programmes accreditation suggests that this may not be the case. Academics present a partial withdrawal towards effective participation in study programmes’ accreditation, especially regarding external assessment. Furthermore, they do not seem willing to enhance this participation nor are they very critical about it. Since academics’ sense of ownership is essential for the successful implementation of QA, these results may represent a challenge for both institutions and QA agencies. [ABSTRACT FROM AUTHOR]