Abstract:

Data ethics is a key component of the future skill data literacy which in turn is a competency that many acquire through self-directed, lifelong learning. This paper argues that orientation and guidance is therefore key to enable learners to understand the breadth and depth of data ethics and choose fitting learning materials. This orientation and guidance can be provided, so the proposal of this paper, by means of a manually curated learning path which is based on a data literacy framework, current literature in the field of data ethics, and a qualitative text analysis of systematically collected data literacy course descriptions.

On the one hand, this procedure allows to extract the breadth of the ethical topics covered in data literacy courses, especially the ethical questions and problems but also the ethical principles that are under discussion. On the other hand, orientation and guidance is not only a question of gathering relevant topics. It is also about distinguishing different kinds of activities and ways of engaging in data ethics and about identifying a starting point and showing a path through the field. A key distinction here, so the paper will argue, is that between reflection and discussion on the one hand and application and implementation on the other: while we are engaging in reflecting and discussing ethical problems and questions, the question of how to change things for the better and how to implement ethical principles needs to be on hold. And vice versa: the ethical discussion and reflection need to be (temporarily) closed when questions of implementation are on the table. We need thus two separate spaces: one for reflection and one for implementation. This argument will be developed based on a discussion of the current literature and validated by an analysis of course descriptions and open educational resources (OER) that cover questions and topics of data ethics.

The main aim of this paper will thus be to develop a learning path for data ethics which covers the relevant content and proposes a structure to the learners engagement with data ethics.

After introducing the topic and explaining the methodological approach of this paper, the content of the learning path will be presented by giving an overview of the ethical themes to be covered. Then the structure of the learning path will be introduced by carving out the need for two distinct spaces: one for reflection and one for implementation. Eventually the scope and possible applications of this learning path will be discussed and an outlook for further development will be given, especially with a view to adapting the learning path for specific target groups. But also the question of whether such a learning path could be curated automatically with a use of generative AI will be considered.

In conclusion, the paper will argue that learning paths are a powerful tool to help navigate the growing amount of OER available for self-directed learning, however taking careful precautions not to claim authoritative closure to the topic of data ethics but leaving room for new ethical questions arising from new developments in a growingly datafied world and for new approaches to ethical education.

Keywords:

Data ethics, data literacy, learning path, open educational resources, self-directed learning.