Spring 2017 - Learning Analytics Research Group (LARG)
- Wednesdays, 9-10am (w/ donuts and coffee), 4123 McKeldin Library
- Meeting schedule: Feb 1 (2nd week of classes) - May 3 (ends one week before last week of classes)
- Data Access policy and process
The goal of this group is to support each other as we work on using data to understand educational activity, interventions and programs. This approach towards evidence-based education uses data to inform decisions about how to structure classes, programs and university experiences.
This semester, we will offer two activities:
- The group will meet weekly to learn about tools, share our work for internal critical feedback, read papers, and listen to speakers. While we won't take attendance, we expect a general commitment to attend regularly so we can have a consistent cohort. While we will meet 1 hour per week, this group is designed for people that are doing some work with institutional data outside of the group. Conceptually, I see this group as a hybrid user's group of campus data and a scholarly community. You are free to use any tools that you feel comfortable with, but we will spend some time teaching and learning from each other how to use R, Tableau and sqlite.
- Graduate students can optionally sign up for 1-3 credits of TLTC 708 (syllabus) to work on a project based on institutional data. See project ideas below.
In partnership with IRPA, campus participants will be provided with access to anonymized historical student records (including grades, transfer credits, major declarations, and degrees granted) to be used for this course. Access will be provided for campus members only that sign an MOU (and graduate students must also sign an IRB).
All LARG participants will get free access to DataCamp! This is an website that teaches how to use R for data science through video lectures, and interactive training. Email me after you have RSVPd and I will give you access, or you can wait until the first day of class.
Note that all communications for the course (and LARG more generally) will be through this Google Group.
RSVP necessary - limit 40 people - please fill out this simple form.
Project Ideas: Grad students taking this course for credit will work on projects (ideally in small groups) with an institutional mentor. We will develop these ideas in the first few weeks of the course, but here are some sample project ideas to get you started:
- Subsequent course analysis. Analyze impact of course characteristics in a 2 course sequence - i.e., instructor, time of day, gap between courses, Fall/Spring v. Winter/Summer, 2x v. 3x mtgs per week.
- How do college benchmark checks to move students out of majors work? How does student success in new major vary depending on when they switch majors based on the benchmarks? Would need to codify benchmark rules.
- Program analysis - What are minimum, average completion times for different programs? Consider graph analysis to understand which programs are risky for students to complete in 4 years? Would need to codify program requirements.
- Course failure and major-change effects. Do students change majors after failing specific courses?
- Online/Blended course analysis - how much, which disciplines? which students? student performance?
- Measuring engagement: What are valid ways to assess engagement using existing UMD data? Assessment, psychometrics
- How useful are Early Warning Grades? How well do they predict final grades? Does giving them change behavior?