Title: Reading: Aspects of trustworthiness of learning analytics
Course: Learning Analytics > Section: Ethical aspects and personal data protection

Trustworthiness of learning analytics

Based on:
Svetec, Barbi; Divjak, Blaženka. (2025). Trustworthy Learning Analytics for Smart Learning Ecosystems. Interaction Design & Architecture(s).

Svetec, Barbi; Divjak, Blaženka; Rienties, Bart; Mukkonnen, Hanni. (2025). Stakeholder Responsibility for Building Trustworthy Learning Analytics in the AI Era . Proceedings of CSEDU 2025.

The trustworthiness of learning analytics has multiple aspects. According to a literature analysis by Svetec and Divjak (2025), these aspects can be grouped into social (ethical and legal) and technological (data, algorithms, and infrastructure) dimensions. They are interconnected and often interdependent, and each of these aspects includes multiple dimensions. There are also horizontal dimensions that are important for both social and technological aspects. In learning analytics, machine learning and artificial intelligence algorithms play an increasingly important role — especially in predictive analytics, personalisation, and the processing of large volumes of data. Therefore, principles of trustworthiness from the field of artificial intelligence are also applicable to learning analytics.

Aspects of trustworthiness of learning analytics

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Questions for self-assessment and reflection

In what ways do transparency and stakeholder involvement contribute to greater trust in learning analytics?

How can data and algorithmic bias affect the fairness and accuracy of learning analytics?