The Six Principles
These principles have been endorsed by the following groups at Colorado State University:
- Center for the Analytics of Teaching and Learning
- The Committee on Teaching and Learning
- Associated Students of Colorado State University
Review the report created by Colorado State University’s Committee on Teaching and Learning Task Force on the Ethics of Learning Analytics.
Principle 1: Learning Analytics serve the teaching and learning mission of CSU
Learning Analytics, and all information technology in support of the institutional teaching mission will serve to enhance the teacher and student interaction, placing an emphasis on enhancing individual student learning opportunities and student success.
Principle 2: Learning Analytics serve the aim of inclusive excellence in the learning environment
Learning Analytics is designed for equity and inclusive excellence in our educational mission. As educational leaders, we’re responsible for being mindful of how Learning Analytics may reinforce the exclusion or marginalization of historically excluded groups and guard against such misuse.
Principle 3: Learning Analytics is accountable to academic and institutional integrity
As scholars, educators, and learners we’re accountable for understanding the implications of collecting, distributing, analyzing, and making decisions based on Learning Analytics data. This includes the implications of making decisions based on algorithms or statistics that are not disclosed to or understood by the user(s).
Principle 4: Learning Analytics data will be collected and maintained to understand specific pedagogical questions
Learning Analytics data is collected from learning and teaching systems, retained, and used for the purposes of enhancing learning and teaching. Holding true to this principle, LA data will be collected based on predetermined pedagogical reasons, used for those reasons alone, and deleted after that data has served that specific use.
Principle 5: Learning Analytics operates with transparency and accountability
As scholars and educators, we will be fully transparent with students about what types of data are collected, where and how it is stored, who has access to it, and how the threat of a data breach is mitigated. In addition, faculty and administrators are obligated to provide a method for dialog and discussion about any LA assessments. The use of LA algorithms that can’t be clearly understood will be avoided.
Principle 6: Learning Analytics data use arises from respect for the individual
All faculty, staff, and students at CSU are valuable members of the CSU community. The design and application of all Learning Analytics methods recognize the individual dignity, rights, and responsibilities of all students as learners, engaged with faculty in pursuit of educational excellence. Given this, the primary use of Learning Analytics should be formative, helping all students to understand and pursue excellence in learning and all faculty to pursue excellence in teaching.