Provide in-depth privacy training and transparent communication about learning analytics processes to build user understanding and student trust¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article's Notes for Practice state that because users have only surface-level privacy understanding, "more in-depth training and discussion of student privacy is essential when implementing learning analytics." It further recommends that "transparency in process and procedure leads to trust from students and users of the system," including clear communication plans and syllabi statements about analytics use.

Design Implications¶

Context¶

Requirements¶

• Training must go beyond generic FERPA mentions to cover specific privacy issues such as black box algorithms and biased analytics

Constraints¶

• The case institution's existing documentation focused on how to use the system rather than the results of using it

Target Learners¶

• faculty and staff users of student success information systems
• higher education students

Target Learning Goals¶

• understanding student privacy obligations and practices when using learning analytics systems

Related Strategies¶

• Institutions implementing learning analytics should spend focused time developing privacy policies and procedures, with stakeholder input including students, before expanding analytics use
• Involve key stakeholders directly in defining privacy and designing LA systems

Examples¶

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Key Sources¶

• Mary Francis, Mejai Bola Mike Avoseh, Karen Card, Lisa Newland and Kevin Streff. (2023). Student Privacy and Learning Analytics: Investigating the Application of Privacy Within a Student Success Information System in Higher Education. Journal of Learning Analytics 10(3). https://doi.org/10.18608/jla.2023.7975