Learning analytics involves the measurement, collection, analysis and reporting of data about learners for the purpose of understanding and improving learning. It has many applications including:
- ??Developing models to predict learner outcomes and student performance;
- ??Identification of students who are struggling and understanding what can be done to assist them; and
- ??Assessing the usefulness of learning materials and resources, evaluating the effectiveness of the curriculum and assisting in evidence-based decision making relating to improving students??learning experience.
As such, learning analytics is an important tool in the quality assurance/quality enhancement process for any educational provider. Teachers can make use of learning analytics to inform their teaching practices such as using the assessment data and student profile to evaluate whether a particular teaching practice is effective for a certain group of students. Curriculum leaders can make use of learning analytics to drive curriculum development including the use of assessment results in different cohorts to identify the weakness of students in general. Administrators can make use of learning analytics to predict student achievements. This can be achieved by analyzing student admission scores and student assessment data to identify the best-fitted students for the programme.