Using data to support learning at the university
The focus of learning analytics is to provide actionable data that can improve the teaching and learning environment. Learning analytics has been contextually defined for campus as “the undertaking of activities that generate actionable data from the learning intended to improve student outcomes by informing structure, content, delivery or support of the learning environment” (defined in 2018 by the Learning Analytics Roadmap Committee).
Learning analytics is a process or instructional approach, and not a specific tool, although it uses tools and data to answer questions. There are numerous ways learning analytics can be used as explained in the Learning Analytics Functional Taxonomy, and there are a number of projects and resources on campus supporting the different opportunities.
Work with us
We collaborate on strategic teaching and learning data initiatives aimed at sustained data-driven practices that maintain and enhance student learning.
Major Efforts
Learning analytics continues to gain interest and demonstrate value in higher education. A variety of approaches have been piloted on campus over the past decade. Opportunities continue to arise with the university’s migration to Badger Analytics, our participation in the Unizin Consortium and a new institutional data policy. LACE collaborates with the Data Empowered Educational Practices (DEEP) Executive Committee, the Vice Provost for Teaching & Learning and others on the following learning analytics projects. Close collaboration with stakeholders is a central component of our project approach.
LACE works closely with campus governance groups and relevant authorities for institutional data to ensure all relevant policies, laws, and regulations, including cybersecurity measures and data protections are adhered to. Specific to our work as practitioners of learning analytics, we hold as a core value the alignment with the UW–Madison approved Guiding Principles for Appropriate Use of Data for Learning Analytics.
Data empowered educational practices (DEEP) microgrants
The University of Wisconsin—Madison started a microgrant program in 2021 to grow institutional capacity around data, specifically for teaching and learning. For the first two years, we focused on projects that used data to support diversity, equity, inclusion, and belonging (DEIB), which funded several important projects in this area. The current microgrants program builds on those goals, by expanding to consider making learning more accessible for all students, teachers, educational professionals, and the institution as a whole.
Get details on the DEEP microgrant program
For more information, please join the UW–Madison Learning Analytics MS Team.
Microgrant program announcement
The 2024-2025 Microgrant theme is Click, Learn, Thrive: Exploring Online Course Engagement.
Student engagement and student-facing tools
Students are interested in seeing data and leveraging learning analytics. Student engagement began in the spring of 2021 with focus groups, and then again in spring of 2022 when surveys and feedback sessions occurred. Students are already using available (minimal) data from campus-supported tools and are leveraging other external resources. They want to explore more tools, approaches and visualizations to support their learning. A student-facing tool will be piloted in the near future.
Learning Analytics Community of Practice (LA CoP)
The Learning Analytics Community of Practice (CoP) is designed to connect colleagues across campus in sharing learning analytics experiences.
Participatory design process
Learning analytics is a complex organizational change process and involves work across the domains of technology, culture, process/workflow, and policy. Various stakeholders have different needs and interests. We use a participatory design process to engage with stakeholders and keep circling back to get feedback while exploring possible approaches and tools. We explore consortium and vendor tools and also create custom solutions. Whether we’re working with instructors, advisors, or students, our process is similar.
- First infographic. Stakeholders Venn diagram intersections at instructors, advisors, students and institution.
- Second infographic. Step 1: Engage with stakeholders – what do they need?
- Step 2: Design prototype, get feedback.
- Step 3: Data governance discussions and process starts.
- Step 4: Develop minimum viable product, get feedback.
- Step 5: Accessibility and usability review.
- Step 6: Pilot, get feedback.
- Step 7: Iterate or enhance.
- Step 8: Support and communications resources.
- Step 9: Launch!
- Step 10: Evaluate, support and enhance.
Exploration
Learning Analytics guiding principles
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, optimize the teaching and learning data environment, and support the student experience.
View Guiding Principles for Appropriate Use of Data for Learning Analytics.
Learner Activity View for Advisors (LAVA)
Currently, in the pilot stage, the Learner Activity View for Advisors (LAVA) is a learning analytics resource that displays high-level trend data about student performance and engagement to academic advisors. A redesigned LAVA was piloted during the spring of 2022, following an engagement with advisors. A larger LAVA pilot is ongoing in fall 2023.
For additional reference, please see the KB article, “The Learner Activity View for Advisors (LAVA) Overview.”
Pedagogical guide to learning analytics
What are the pedagogical uses of learning analytics? The focus of learning analytics is to provide actionable information that can improve teaching and learning. By using data generated within online courses, we can make informed improvements to teaching and learning on our campus.
Learning analytics functional taxonomy
Why are people using learning analytics? What are some practical examples?
Learning analytics is not a tool, rather it’s an approach that leverages data to improve teaching and learning. There are many different ways that data can be used to support students. This web content was created based on an article by Nguyen, Gardner and Sheridan (2017)*.
Explore the following tabs for more information and examples about how these approaches might be implemented. Examples are from UW–Madison and other institutions.
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Despite our best efforts to ensure accessibility of the LACE webpage and resources, there may be some limitations with some of the content that is linked on the LACE website. Below is a description of known limitations, and potential solutions. Please contact LearningAnalytics@office365.wisc.edu if you encounter an issue.
Known limitations for LACE’s content:
- Case study links and PDFs: Some of the research and case studies listed within the learning analytic functional taxonomy are provided through PDFs and external links. The PDFs and external links have images that may not have text alternatives. The PDFs may not be accessible to all screen readers. The PDFs may not have high color contrasting in some areas. Because we are unable to alter some of the PDFs or content from external links, fully accessible content cannot be guaranteed. However, we are committed to working with any users that need accommodations.
Resources and opportunities
There are several ways to learn about learning analytics at UW–Madison. LACE collaborates with the Learning Analytics Roadmap Committee (LARC), the Vice Provost for Teaching & Learning and others to provide the following opportunities and resources.
Community of interest for learning analytics
If you are interested in obtaining information about learning analytics opportunities, training, fellowships and events on campus, please join the UW–Madison Learning Analytics MS Team or email us and request to be added to the group.
Additional resources
Materials from past learning analytics events
- Explore Course-Level Data with Tableau Visualizations – presented by Clare Huhn & Jocelyn Milner, February 21, 2019
- Course-Level Dashboard (& Analytics Beta – Canvas) – presented by Kari Jordahl, James McKay, Garrett Smith & Xizhou “Canoe” Xie, November 13, 2018
- The Importance of Meaning: Turning Big Data into Real Understanding (video) – presented by David Williamson Shaffer, October 16, 2018
- 6 Ways to Use Learning Analytics: a Functional Taxonomy – presented by Sarah Hagen & Sarah Traynor, September 18, 2018
- Active Teaching Lab Recap: Canvas Analytics – September 7, 2018
- Canvas Analytics: Instructor Perspectives on Course Analytics – presented by Amanda Margolis, Mark Millard & Catherine Arnott Smith, April 26, 2018
- Data Visualizations & Infographics (It looks cool, but what is it telling you?) – presented by Cid Freitag, March 20, 2018
- Using Pattern to Log Course Activities – presented by Miguel Garcia-Gosalvez, Heather Kirkorian, James McKay, & Kim Arnold, February 21, 2018
Support documentation for tools used on campus
Instructors:
- How do I view Canvas Course Analytics?
- How do I view a context card for a student in a course?
- How do I view analytics for a student in a course?
- How do I view the course access report for an individual user?
- Canvas student course access and anonymous course reports (3rd party tool)
- How do I view Kaltura Media Analytics?
- Kaltura – Mediaspace Media Analytics
- Kaltura – Advanced Mediaspace Analytics
Students:
LACE updates
List of articles
Study the relationship between digital course content & student success
Interested in learning how to use course data to better understand how students engage with your online content? Apply for a microgrant. Deadline: May 22.
February 18, 2025Dr Kim Arnold earns distinguished director status
UW–Madison awards distinguished status to those who demonstrate an exceptional level of expertise in their field. Arnold is director of the Learning Analytics Center of Excellence (LACE), a Division of Information Technology unit within Academic Technology.
July 16, 2024Seven microgrant recipients awarded for data-driven education practices
The University of Wisconsin–Madison has announced the recipients of its annual microgrant program, aimed at advancing data-empowered education practices (DEEP). These grants, administered by the Learning Analytics Center of Excellence (LACE) in partnership with the …
May 16, 2024Microgrants in support of student success in online course content
Apply for a microgrant to explore how engagement with online course content impacts student performance. Deadline: Apr 21.
March 20, 2024Take a DEEP dive into teaching and learning data for student engagement and success
The 2024-2025 theme for the microgrant program focuses on enhancing student learning by drawing on data to empower key educational practices. Faculty and instructors from all disciplines are encouraged to apply.
December 5, 2023- More Learning Analytics Center of Excellence posts
Help & contact
Schedule a consultation
There are a wide range of tools available and our learning technology consultants are happy to help you choose the best tool to fit your needs. Instructors and instructional staff can request a consultation with a DoIT AT consultant through the DoIT Help Desk.