Not everyone is familiar with the term “learning analytics”. How would you explain it – and how does it differ from educational-data mining?

Prof. Dr. Albrecht Fortenbacher: Both educational-data mining (EDM) and learning analytics deal with the analysis of data about learners in the context of a learning environment or learning situation. EDM places greater focus on methods of data mining or machine learning to reach conclusions about students or learning environments. Learning analytics goes beyond this, seeking to understand learning processes and interventions that can support and enhance learning. In simple terms, one could say that learning analytics sets the learner more in the middle of its interests.

Who can draw particular benefit from learning analytics?

Prof. Dr. Albrecht Fortenbacher: The list of stakeholders for learning analytics ranges from education providers such as universities, which are interested in the success of their training; to lecturers, instructors, and tutors, who deliver the training program; and on to students, to whom learning analytics provides instructions or recommendations in regard to “improved” learning. The use of learning analytics has two benefits for companies and organizations: It helps enhance the efficiency - i.e. the efficient use of resources - as well as the effectiveness (learning results) of training programs.

What can business and industry possibly learn from the universities’ experience? Which points do you view as particularly interesting?

Prof. Dr. Albrecht Fortenbacher: It is particularly interesting - and particularly difficult in the German-speaking countries – to get learners to accept learning analytics and the various aspects of data protection (ethical, legal, and social implications - ELSI). The experience and privacy concepts that the use of learning analytics has made available to universities can also be important and helpful for corporate training.

What kinds of benchmarks, guidelines, or other practical experience can your university offer companies?

Prof. Dr. Albrecht Fortenbacher: Standards and guidelines -‹-‹are complicated because the use of learning analytics is often still in its infancy in the business world. Practical experience, though, is currently being gathered in our BMBF-funded project called Learning Analytics for Sensor-Based Adaptive Learning – "LISA" for short. It involves three academic partners and three companies, which are using solutions developed in the project in their learning environments and application scenarios, respectively.