Learning Design and Learning Analytics to Improve Higher Education: A Systematic Literature Review

Rangana Jayashanka et al.

Electronic Journal of e-Learning2026https://doi.org/10.34190/ejel.24.2.3645article
AJG 1
Weight
0.50

What the paper says

In recent years, higher education has increasingly emphasized the integration of Learning Design and Learning Analytics to foster more engaging, personalized, and effective learning environments. This systematic literature review investigates how these two domains interact to enhance teaching learning processes and improve educational outcomes. The review identifies key benefits and opportunities associated with this integration across three stakeholder groups: students, lecturers, and educational institutions by analyzing 55 peer-reviewed publications. The results show that learning effectiveness can be significantly enhanced through the visualization of students’ learning interactions using straightforward and user-friendly analytical approaches. Furthermore, successful implementation requires the development of lecturers’ data literacy and programming competencies, as well as the incorporation of sociocultural, psychological, and physical data to achieve a more holistic understanding of learners. The review also identifies four major research directions to guide future efforts in bridging Learning Analytics and Learning Design. Finally, the paper underscores the importance of establishing clear ethical and privacy frameworks to ensure the responsible application of Learning Analytics in higher education.

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https://doi.org/https://doi.org/10.34190/ejel.24.2.3645

Or copy a formatted citation

@article{rangana2026,
  title        = {{Learning Design and Learning Analytics to Improve Higher Education: A Systematic Literature Review}},
  author       = {Rangana Jayashanka et al.},
  journal      = {Electronic Journal of e-Learning},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.34190/ejel.24.2.3645},
}

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.