The campus community is encouraged to join higher education leaders from around the world as the University of Michigan hosts the Learning Analytics Summer Institute 2017, June 12-15, at the Michigan Union.
Through seven workshops and 11 tutorials, participants will hear about the latest technology and methodology for gathering and using data on how people learn, says institute organizer Stephanie Teasley, research professor in the School of Information and co-chair of the institute.
Michigan is a leader in using data to personalize education, Teasley said, which is why for a second year in a row through the Office of Academic Innovation U-M will host the international Society for Learning Analytics Research event.
Learning analytics is the process of gathering and using data about how people learn. The society defines it as: “The measurement, collection, analysis and reporting of data about learning and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs.”
Teasley said the institute will help faculty and graduate student who hope to learn new techniques to analyze data, in order to meet the needs of today’s learners.
“Analytics is ultimately aimed at action, and is done in service of doing something with the numbers so that we can better serve students,” she said. “There are people all across our campus using learning analytics. Our goal is to encourage others to get involved as well.”
- Building predictive models of student success with the weka toolkit
- SNA (Social Network Analysis) for learning analytics in formal and informal learning environments
- Automated personalization in education
- Writing analytics
- From data to student support actions
- Multi-modal analytics
- Analyzing temporal data: Theory & tools
- Learning analytics community of practice, human power driving data discovery at the university scale
- Black box learning analytics? Beyond algorithmic transparency
- Developing and implementing an institutional data governance policy
- Statistical analysis of interdependent observations in learning environments: Exponential Random Graph Modelling (ERGM)
Registration for the event is open for faculty and graduate students at the university until the end of this week.
The form on the website http://lasi.solaresearch.org/ asks participants to join the Society for Learning Analytics Research, which Teasley said some may wish to do, but U-M has an institutional membership so it is not required. Contact her or the Office of Academic Innovation (734-764-2010) for a code to use to fill in the membership information.
Written by Laurel Thomas Gnagey