(SpringerBriefs in Business Process Management) Learning Analytics Cookbook_ How to Support Learning Processes Through Data Analytics and Visualizatio

2.2 Stakeholders: Contributors and Beneficiaries of Learning Analytics 9
Internal
Limitations
External
Constraints
Competences Acceptance Conventions Norms
Stakeholders
Institution
Teachers
Learners
Other
Learning Analytics
Technology
Algorithm
Theories
Other
Instruments
Reflection Prediction Open Protected
Objectives
Data
Fig. 2.3 Six dimensions of learning analytics (Greller and Drachsler 2012)
ethics applied to the handling of personal data have even reversed implementations
(Singer 2014; Tsai et al. 2018).
Greller and Drachsler (2012) provided a comprehensive introduction to the
domains affected by learning analytics (Fig. 2.3). They clustered learning analytics
into six dimensions: stakeholders, objectives, data, instruments, external constraints,
and internal limitations. These dimensions are based on the assumption that developers
of analytic processes will implement what is technically possible and legally
allowed but also consider the outcomes for the educational stakeholders and, even
more important, the consequences for the people whose data is being used.
2.2 Stakeholders: Contributors and Beneficiaries
of Learning Analytics
The stakeholder dimension includes data clients as well as data subjects. Data
clients are the beneficiaries of the learning analytics process who are meant to act
upon the outcome (e.g., students and teachers). The data subjects are those who
supply data, normally through their browsing and interaction behavior. These roles
can change depending on the objective of the analytics (e.g., whether it is on the
micro-, meso-, or macro-level). Moreover, educational technology requires a sound
analysis of stakeholders’ needs to be successful in the long run (Greller and
Drachsler 2012). This requirement applies especially to learning analytics solutions,