Learning Analytics Explainability
Learning Analytics Explainability is a scholarly construct within educational data science that denotes the capacity of learning analytics systems to provide transparent, interpretable, and human-understandable representations of analytical processes and outcomes, thereby enabling stakeholders to comprehend how data-driven insights about learner behavior and performance are generated and validated.
22
Publications
1K
Citations
80
Authors
28
Institutions
Publications per year
2017–2026
19
22
1–5 of 22
80
2
h-index
2
h-index
2
h-index
1
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1
h-index
1–5 of 80
28
Williams College
Williamstown, United States
1 h-index
3 publications
54 citations

University of Cagliari
Cagliari, Italy
1 h-index
1 publications
26 citations
Himachal Pradesh University
Shimla, India
1 h-index
2 publications
312 citations
University of Southampton
Southampton, United Kingdom
1 h-index
1 publications
54 citations

University of Edinburgh
Edinburgh, United Kingdom
1 h-index
1 publications
20 citations
Iowa State University
Ames, United States
1 h-index
1 publications
14 citations

The University of Queensland
Brisbane, Australia
1 h-index
5 publications
70 citations

Massey University
Palmerston North, New Zealand
1 h-index
1 publications
92 citations
1–8 of 28
3 publications · 64 citations
3
h-index
1 publications · 35 citations
1
h-index
1 publications · 15 citations
1
h-index
1 publications · 96 citations
1
h-index
1 publications · 156 citations
1
h-index
1–5