• Posted Dec. 15, 2020

Study: Design principles for learning analytics information systems in higher education

• Digitalisation has influenced and changed how education functions and is administered. While a massive amount of educational data is generated every minute, most institutions have not gathered and utilised the data effectively.
• The development and implementation of an effective learning analytics system in institutions require extensive resources, skills, and in-depth knowledge.
• This study aims to construct a set of design principles that describe a class of systems that are a means to the purpose of supporting learning analytics in higher education.

The design principles were formulated based on our synthesis of the literature.  They were evaluated and revised throughout the design processes. We developed a learning analytics system prototype based on the design principles and evaluated the prototype in four courses with a total enrolment of 1,173 students.

Four design principles capture the key take-aways:

1. Principle of actionable information. Provide reports of actionable information about learners and their learning with flexible granularity in reporting.
2. Principle of information delivery. Generate responses and information that visualize learning and teaching behavior and performance.
3. Principle of information interoperability.  Enable interoperation with any LA and/or educational IS, including VLEs, and enable integration with different data sources without resulting in any discernible issues or complications.
4. Principle of information anonymity and protection. Provide anonymity for personal and protect data against accidental or unlawful destruction or accidental loss, alteration, unauthorized disclosure, or access.