Why Learning Analytics?

Innovation Pilot

Learning Analytics, as defined for UBC’s Learning Analytics Project, involves the measurement, collection, analysis, and reporting of data about learners and their contexts, with the goal of understanding and optimizing learning and the environments in which learning occurs. This page outlines some of the ways that the analysis of learner data can empower students, instructors, advisors, and faculties.

Opportunities for Innovation

Types of questions we can answer with learning analytics - infographicLearning Analytics is a broad term that spans a wide range of activities. For example, instructors and researchers can use learning analytics to test the effectiveness of learning approaches and of particular learning interventions. Faculties and departments may be interested in how insights from learning analytics can help them refine their approaches to program planning and reporting.

Learning analytics can help support student success by supporting:

  • Continuous improvement in the learning environment.
  • Earlier identification of students at risk of failure, supporting targeted and timely interventions.
  • Effective measurement of the value of investments in teaching and learning transformations.
  • Evidence to inform the planning of programs, courses, and infrastructure.
  • Data that can inform the evaluation of instructional materials, courses, and programs.
  • Efficient and timely data-informed decision making.

While promising, Learning Analytics is a relatively new field, and universities are still determining what questions we can and should be answering using course and program data, as well as the best ways to convey that data. The Learning Analytics Project was launched in part to allow UBC explore these possibilities through ongoing, iterative research pilots.




Who can Learning Analytics benefit?

The analysis of learning data can positively impact stakeholder groups in diverse ways, depending on their roles and interests. This table outlines some of the possible stakeholders and how learning analytics can support them in their efforts to enhance learner success.


Purposes and stakeholders in university learning analytics – adapted from Kay (2013)
Learning Analytics tools or insights can facilitate… Example stakeholders
Learner empowerment: awareness and control of own learning strategies and performance to encourage self-regulated learning and support metacognition Learners
Monitoring and tracking for immediate decisions

  • Identifying problems early enough to intervene
  • Distinguishing students who are disengaged
  • Responsive interventions / enhancements
Individual educators
Reflection and research for recognizing long term issues

  • Insights into learning processes / performance by many learners
  • Education research
  • Attrition factors
  • Insights into individual performance
  • Socio-cultural aspects and underserved populations
Individual educators
Educational researchers

  • Course design/re-design
  • Curriculum and program planning
  • Faculty-level planning with regards to course, program offerings
  • Teaching assignments / enrolment patterns
  • Decision-making with regards to management, staffing, etc.
Individual educators
Reporting and communication among and between stakeholder groups, e.g.:

  • Educators to learners
  • Institution to parents / government
  • Peer to peer