Learning Analytics &
assurance of learning

Digitization is becoming part of almost everyone’s life, ranging from smartphones and tablets, smart devices automatically collecting information, to tools and scripting languages that are widely available and easy to use. This has recently been reflected in various university curricula, where courses such as computational thinking, and basic programming classes are now included in a broader range of (non-computer-science) programs. 

Additionally, In higher education, particularly at the university level, assessment of students' performance, systematically analyzing learning outcomes, and quality assurance of teaching and learning material has become a widely adopted practice.

Such activities even become mandatory when study programs apply for accreditation, which typically requires a set of well-established learning objectives on program-level, and a course syllabus with an assurance of learning system in place.  These objectives describe the competencies, in terms of skills and knowledge, learners, (i.e., students) should have acquired after successfully completing the course.

Besides accreditation requirements, assurance of learning is meant to further provide an effective quality assurance process to assess the effectiveness of individual courses, as well as entire programs. In order to make use of an established assurance of learning system and, moreover, facilitate accurate evaluation, proper and well-defined measurements and respective guidelines for improvements need to be established. This requires support for the structured capturing and definition of metrics and evaluation data at the program level, as well as at the individual course level. This further contributes to the principle of constructive alignment which emphasizes the alignment of learning objectives, and teaching methods, with the corresponding assessment.