Аннотация
The field of learning analytics has the potential to enable higher education institutions
to increase their understanding of their students’ learning needs and to use that
understanding to positively influence student learning and progression. Analysis of
data relating to students and their engagement with their learning is the foundation
of this process. There is an inherent assumption linked to learning analytics that
knowledge of a learner’s behavior is advantageous for the individual, instructor, and
educational provider. It seems intuitively obvious that a greater understanding of
a student cohort and the learning designs and interventions they best respond to
would benefit students and, in turn, the institution’s retention and success rate.
Yet collection of data and their use face a number of ethical challenges, including
location and interpretation of data; informed consent, privacy, and deidentification
of data; and classification and management of data. Approaches taken to understand
the opportunities and ethical challenges of learning analytics necessarily depend on
many ideological assumptions and epistemologies. This article proposes a sociocritical
perspective on the use of learning analytics. Such an approach highlights the role of
power, the impact of surveillance, the need for transparency, and an acknowledgment
that student identity is a transient, temporal, and context-bound construct. Each of
these affects the scope and definition of learning analytics’ ethical use. We propose
six principles as a framework for considerations to guide higher education institutions
to address ethical issues in learning analytics and challenges in context-dependent and
appropriate ways.
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