All workshops will start at noon, and be available via video conference (the virtual meeting URL be announced on each myUMBC event registration site the morning of the event). To register and view more information, check the links below:
"Learning Analytics By Students For Students?" (9/30, Noon). In this session, Dr. Karen Chen, assistant professor of Information Systems, will make the case for why and how students can and should play a more active role in the design and development of learning analytics to improve student success.
"Using Analytics to Predict & Improve Sophomore Retention" (10/14, Noon). In this session, student success colleagues Robert Carpenter, Delana Gregg and Len Mancini, will share how UMBC has worked with HelioCampus to build very accurate models that predict second year retention at the beginning of their third semester. In addition to explaining how the models work, key inputs into them, and where to find the results, they will share how we have begun to act on them.
"Tips & Tricks for Telling Your Story with Data" (11/10, Noon). In this session, Mike Sharkey, an analytics thought leader, teacher, consultant and long-time friend of UMBC, will share his lessons learned using data, narrative and visualizations (including Tableau) to raise awareness and inspire change.
"Mapping Student Pathways Through the Curriculum" (12/2, Noon). As institutions continue to identify barriers to student success one area to explore is how we engage faculty and departments in using learning analytics to take a fresh look, along with a greater understanding, of student pathways toward graduation. In this talk, Dr. Martha Oakley, Assoc. Vice Provost for Undergraduate Education and professor of chemistry at Indiana University Bloomington, will highlight recent developments by IU's Bloomington Assessment and Research (BAR) team to provide faculty and administrators with process maps that show how students actually navigate through curricula.
To view prior data science and learning analytics meetings (and recordings), please visit doit.umbc.edu/analytics/community.
~ By John Fritz