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Table 2 Quality indicators for learning analytics. Source: summarized from Scheffel et al. (2014)

From: The use of data science for education: The case of social-emotional learning

Topic Criterion Representative statements
Objectives Teacher awareness Teachers change their behavior in some respects.
Teachers react in a more personalized way to how their students are dealing with learning material.
Student awareness Students become more self-regulated in their learning processes.
Students are more aware of their learning progress.
Learning Support Learning support An early detection of students at risk.
The ability to explain what could help them to improve further.
Students regularly utilize the tools provided.
Learning Measures and Output Learning outcome If teachers can gain new insights using the given methods.
Results are compared with other (traditional) measures.
Learning performance Change in workplace learning is measurable.
The extent to which the achievement of learning objectives can be demonstrated.
Data Aspects Open access Data are open access.
Portability of the collected data.
Privacy Privacy is ensured.
Learners can influence which data are provided.
Organizational Aspects Acceptance & uptake Administrators invest in scaling successful tools across their programming.