Learning Analytics Event Focused on Ethically Leveraging Data to Help Students

Thu November 14, 2019

Beth co-chaired LADUS and is a professor (CHS) and assistant dean for assessment, teaching & learning; School of Pharmacy.

On Tuesday, October 22, 2019, Beth Martin and Brian Yandell presented on Learning Analytics Guiding Principles: Supporting Students While Ethically Leveraging Data as part of the learning analytics speaker series, co-sponsored by DoIT Academic Technology and the Educational Innovation (EI) Initiative.

Beth and Brian were members of the Learning Analytics Data Use Subcommittee (LADUS), which was an ad hoc committee convened last year by the Data Stewardship Council at the recommendation of the Learning Analytics Roadmap Committee (LARC). LADUS included representatives from across the university, with a goal to establish guidelines for the use of data for learning analytics as an educational practice. The guidelines are the first step in establishing policy and providing transparency about data use to students, instructors, administrators and other staff.

Brian is a professor of horticulture and statistics, director of biometry program, and interim director of the American Family Insurance Data Science Institute.

They shared the guiding principles and also provided some background around how and why they were created. The four principles are:

  • Beneficence
  • Minimize adverse impacts
  • Transparency
  • Privacy and Confidentiality

These principles are student-centric as the introduction to the Learning Analytics Guiding Principles notes: “Students are real and diverse individuals, and not just their data or information. These principles – beneficence, transparency, privacy and confidentiality, and minimization of adverse impacts – aim to uphold the dignity of students while ensuring learning analytics are used to improve educational outcomes.”

During the October presentation, participants engaged in small group discussions about four different course scenarios; each group discussed a different example of how an instructor might consider using learning analytics in a typical UW-Madison course. This activity provided a thoughtful way for participants to experience how the guiding principles can be used, to ensure that they are using learning analytics data in adherence to these principles.

Resources

  • Please check out the slides from the session for more information. The scenarios for the discussion activity are included in the slide deck and can also be accessed as a separate handout.
  • The Appropriate Use of Data for Learning Analytics Guiding Principles document is posted on the provost’s page and was approved by the Data Stewardship Council, and endorsed by the Learning Analytics Roadmap Committee in May of 2019. In addition to the four principles, this 7-page document includes the background and purpose, in-scope and out-of-scope descriptions for activities and data, as well as roles and responsibilities for the different stakeholders who are impacted by learning analytics.
  • If you have questions about applying the principles or would like to discuss further, please contact Kim Arnold or Beth Martin, LADUS co-chairs.

If you are interested in discovering more about learning analytics at UW-Madison, refer to these resources:

  • DoIT Academic Technology’s Evaluation Design & Analysis service provides information about current learning analytics projects, events, resources and opportunities on our website. In addition, there is the Learning Analytics Functional Taxonomy that provides examples for each category.
  • Learning Analytics at UW-Madison (on the Office of the Provost’s page) includes the university’s definition for learning analytics, information about governance and oversight, as well as the recently adopted Guiding Principles for Use of Data for Learning Analytics.
  • Office of Data Management & Analytics Services – Teaching and Learning has been established as a new data domain, under the Vice Provost for Teaching & Learning.