Readings

Predictive Analytics and Using Data

• What Data Can’t Do: When it comes to people—and policy—numbers are both powerful and perilous (Hannah Fry, The New Yorker): Review of two books on data and statistics, with commentary on both the power and peril of using data to drive decisions; March 22, 2021
• How universities deploy student data (Esther Shein, Communications of the ACM, Vol. 63, No. 4, pp. 18-20, http://dx.doi.org/10.1145/3381910): Overview of some functions of the use of data for supporting students, including discussion on data governance; April 2020
• Big data and the problem of bias in higher education (Forbes): Using big data in higher education is not neutral and can be prejudiced, but embracing data-driven decisions and predictive models can advance student success; May 30, 2019
• Turning more tassels: How colleges and universities are improving student and institutional performance with better advising, https://www.bcg.com/en-us/publications/2019/turning-more-tassels, In partnership with the Bill & Melinda Gates Foundation and NASPA, the Boston Consulting Group (BCG) studied the return on investment of broad-based advising reforms, at Florida State University, Georgia State University, Montgomery County Community College, and the University of Texas at Austin, January 30, 2019
• The promises and perils of student success predictive modeling (EAB): An interview with Lars Waldo, principal data scientist for the Student Success Collaborative; March 6, 2018
• The promise and peril of predictive analytics in higher education: A landscape analysis (Policy Paper from New America): Descriptions of cases where institutions are using predictive analytics to support students and steer them toward success, presented with ethical concerns related to the impact of using data on underrepresented students; October 24, 2016

Meta-Majors

• Guided Pathways to Success (GPS): Boosting college completion (Complete College America): motivations for and results of college-completion programs that use methods including meta-majors, academic program maps, and intrusive advising
• How meta-majors guide students toward on-time graduation (EAB): how several institutions have implemented meta-major initiatives, and their impact on student success

Degree Maps

• Degree mapping guidelines: A toolkit (CUNY): overview, curricular issues, campus processes, and technologies for implementing degree maps

Corequisite Courses

• Corequisite Support (Complete College America): corequisite courses increase gateway course completion within the first year, by providing extra help to students who need it
• Guidance for designing corequisite courses at CUNY (CUNY): Information for creating non-credit support in math, reading, or English.

From EAB

• Conference materials:
  • Connected 2019
  • Connected 2020
• Nudges and Interventions to keep students on track
• Diversity, Equity, Inclusion, and Justice resource center