What is learning analytics?

Learning analytics is the data collected from a learner’s online and offline experiences. The data is analysed to better understand their context as learners, leading to adjustments of their learning environment to their specific needs.

What data is collected?

The data collected covers a broad spectrum of topics to obtain a deeper understanding of learners and their habits, such as student characteristics, educational background, log data and academic performance. All this emphasizes a learner-centred approach rather than a purely logical one - the algorithm has a better understanding of the human condition and is well able to adjust to this. This ‘adjustment’ process can be split into 3 stages: Hindsight, Insight and Foresight. Hindsight represents the collection of data; Insight provides reasons for the students results and Foresight predicts the students next moves and further helps in optimization. These three factors accompany the Descriptive, Diagnostic, Predictive and Prescriptive analytics stages discussed in class.

What is learning analytics used for?

This data, once processed, is useful for both the student and teacher alike. The teacher can better understand their students’ learning habits on a more personal level, which leads to learning support and teaching efficiency. The student can track their process, allowing self-assessment and a better understanding of their strengths and weaknesses.

https://www.youtube.com/watch?v=XscUZ8dIa-8https://www.solaresearch.org/about/what-is-learning-analytics/