Learning analytics refers to the process of collecting, analyzing, and using data from various learning contexts to improve teaching and learning outcomes. When it comes to assessing or giving feedback to university students related to their innovation competence, learning analytics can be a powerful tool. By analyzing student performance data in innovation-related activities, such as design thinking exercises or innovation challenges, instructors can gain insight into how well students are developing their innovation skills.

For example, learning analytics can be used to track the progress of individual students over time, identifying areas where they may be struggling and where they may need additional support. This can be especially useful in identifying students who may be falling behind in their development of innovation skills, and targeting interventions to help them catch up. Additionally, learning analytics can be used to identify patterns of success among high-performing students, providing insights into what strategies and approaches are most effective for developing innovation competencies.

Feedback is another key component of learning analytics in assessing innovation competencies. Through the use of analytics tools, instructors can provide personalized feedback to students based on their individual performance, highlighting areas where they excel and areas where they can improve. This feedback can be delivered in real-time, providing students with timely guidance and support to help them develop their innovation competencies.