  The widespread interest in learning analytics (LA) is associated with
increased availability of and access to student data where students' actions
are monitored, collected, stored and analysed. The availability and analysis of
such data is argued to be crucial for improved learning and teaching. Yet,
these data can be exposed to misuse, for example to be used for commercial
purposes, consequently, resulting in information privacy concerns (IPC) of
students who are the key stakeholders and data subjects in the LA context. The
main objective of this study is to propose a theoretical model to understand
the IPC of students in relation to LA. We explore the IPC as a central
construct between its two antecedents: perceived privacy vulnerability and
perceived privacy control, and its consequences, trusting beliefs and
self-disclosure behavior. Although these relationships have been investigated
in other contexts, this study aims to offer mainly theoretical insights on how
these relationships may be shaped in the context of LA in higher education.
Understanding students' IPC, the related root causes and consequences in LA is
the key step to a more comprehensive understanding of privacy issues and the
development of effective privacy practices that would protect students' privacy
in the evolving setting of data-driven higher education.
