Learning analytics

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Learning analytics (LA) means the collection and aggregation of large sets of student data and its analysis and reporting / visualization. The aims of LA can be to:

  1. understand the learners and help them to master the learning, e.g., by providing tailored feedback
  2. evaluate and improve learning activities
  3. detect students at risk of failing a course or program
  4. develop predictions about students’ performances. 

Using statistical and data mining methods makes it possible to detect meaningful patterns to improve learning. This is given in the case of electronic learning tools that have been used for a long time, in large scale events like Massive Open Online Courses or when sharing learning resources by many institutions. However, ethical and data-protection aspects are important to be considered. Virtual patient environments, similar to learning management systems, typically record and store learners’ interactions with the system and this data can be used for providing system-generated or tutor-guided feedback.

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