Vendor Documentation
General Best Practices for Using Data (Learning Analytics)
When working with or acting upon learning analytics, keep the following in mind:
Have a student-centered mindset when working with and acting upon learning analytics.
Tell your students how you will use this information, who else can see this information in your course (e.g. TA, support staff), and why it matters to you to view the information.
Use the information only as part of a larger understanding about a student. For example view trends or over time and use it in conjunction with other metrics. Students are multidimensional and small data points can be misinterpreted or not provide a complete picture.
Ensure you are following FERPA and data privacy regulations.
Ensure that "[t]he analysis, interpretation and use of learning analytics data does not reinforce discriminatory attitudes or increase social power differentials" (from Code of Practice on Learning Analytics).
Ensure that your thoughts about the data do not cloud your expectations of a student's performance, as this can be a self-fulfilling prophecy for the student. “When we expect certain behaviors of others, we are likely to act in ways that make the expected behavior more likely to occur.” (Rosenthal and Babad, 1985). For more information, review:
The Pygmalion Effect (from Duquesne University)
Pygmalion or Golem? Teacher Affect and Efficacy (by Susan H. McLeod)
Rosenthal, Robert, and Lenore Jacobson. 1968. Pygmalion in the classroom: teacher expectation and pupils' intellectual development. New York: Holt, Rinehart and Winston. Available in hard copy in the RIT Library.
Effective Ways to Act Upon Learning Analytics
Data is most useful when you can act upon it. The following are effective ways to act upon the learning analytics in the Insights Portal:
Use this information to reach out to individual students who are struggling. Have targeted conversations about the progress you are seeing in the data and tie that to actionable things the student can do to improve. Provide details on how you can support the student or ask the student how they would prefer to be supported.
Use this information to create "all class" coaching or advice based on the interaction patterns you see that best support student success. Open up a conversation with students about what you saw that worked from the data and have the students tell you about what they all felt worked for them.
Use this information for improving your course materials or your own engagement levels in the course (i.e. reflective professional development).
Flags and Kudos should still be raised in Starfish as usual for undergraduate students.
For More Information
Learning Analytics in Higher Education (from Educause Center for Analysis and Research)
Global Guidelines: Ethics in Learning Analytics (from the Association for the Advancement of Computing in Education)
Code of Practice on Learning Analytics (from University of Leeds)
Learning Analytics: Ethical Issues and Dilemmas (by Sharon Slade and Paul Prinsloo)
Learning Analytics in Higher Education: A review of UK and international practice (from Jisc)