The Application of Learning Analytics

Learning Analytics (LA) is a field of research that aims to predict and advise on learning, further to support faculty in identifying students’ learning needs and improve pedagogical strategies (Siemens, 2012; Verbert, Manouselis, Drachsler & Duval, 2012; Greller&Drachsler, 2012).

Verbert and his associates identified six highly interrelated objectives which are relevant in existing learning and knowledge analytics research (Verbert, Manouselis, Drachsler & Duval, 2012):

  • Predicting learner performance and modeling learners
  • Suggesting relevant learning resources
  • Increasing reflection and awareness
  • Enhancing social learning environments
  • Detecting undesirable learner behaviors
  • Detecting affects of learners

The results derived from LA research suggest that the learning data of students enrolled in programs with competence-based model can inform program core curriculum design. Under that assumption, I came up with a framework that illustrates how Learning Analytics can contribute to positive outcomes at the level of individual students, courses and departments.

  • Analyzing students’ data in learning diligence and outcome can hopefully target learners’ meta-cognition, foster awareness and reflection about one’s learning processes.
  • Data analysis from the student level can inform instructors to implemented targeted interventions and enhance their teaching practices (Greller & Drachsler, 2012).
  • Departments/programs can monitor the performance of students regarding retention and achievement in a discipline. Furthermore, they can evaluate course offerings within the discipline and improve outcomes of the programs.



Ali L., Hatala M., Gasevis D & Jovanovic J. (2012). Computers & Education, 58 (1), 470-489, Available at

Greller, W., & Drachsler, H. (2012). Translating Learning into Numbers: A Generic Framework for Learning Analytics. Educational Technology & Society, 15 (3), 42-57.

Siemens, G. (2012). Learning Analytics: Envisioning a Research Discipline and a Domain of Practice. LAK ’12 Proceedings of the 2nd International Conference on Learning Analytics and Knowledge , 4-8. Available at

Verbert, K., Manouselis, N., Drachsler, H., & Duval, E.(2012). Dataset-Driven Research to Support Learning and Knowledge Analytics. Educational Technology & Society, 15 (3), 133-148.

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