Reading: Advice for interpretation of learning analytics

General recommendations

Learning analytics does not provide instructors with universal rules or generalisable results; rather, it must be interpreted within a specific educational context.

At least basic learning analytics functionalities are available in various e-learning tools and learning management systems (LMSs). Check the analytics available there, but do not interpret them without first consulting the documentation and discussing potential advantages and limitations with colleagues.

Learning analytics is always biased to some extent; therefore, instructors should be aware of their own goals as well as the limitations of a particular data analysis.

Be aware that learning analytics can both motivate and demotivate students to learn; therefore, pay attention to the types of analyses and feedback that may be more beneficial for your students’ learning.

Questions instructors should ask:

Why do you need learning analytics?

Some possible answers:

• • monitoring or evaluating my teaching and my students’ learning
  • evaluating course and learning design
  • providing feedback to students to improve their learning
  • evaluating the usefulness of and improving educational materials
  • monitoring and evaluating the impact of a new pedagogical approach
  • identifying early indicators of success or failure
  • adapting teaching to students’ specific needs

Based on the answers, you select the approach, metrics, data sources, learning analytics method, and level of dissemination, as analysed below:

To summarize your thoughts when planning activities related to the application of learning analytics, you can use this table: