Student Success Analytics (SSA)
Welcome to the EDUCAUSE Student Success Analytics Community Group!
Goal: The goal of the community group is to promote, educate, and further a network of practitioners with a desire to improve student success through the use of analytics. The more we can collaborate and share on these efforts, the easier it is for these initiatives to grow and succeed. Join us on Slack!
Membership
Individuals from educational institutions, organizations, and providers serving them who are actively planning or implementing analytics initiative aimed at improving student success.
Please don’t worry if you aren’t a data analyst, this group is for everyone interested in using analytics for student success, not just advanced mathematicians.
Anyone who is interested in the topic matter can, and should, join. There is plenty of room for everyone and the resources of the group will be geared toward all technology comfort levels.
Join Today! - SSACG Membership
Steering Committee, Meetings and Listserv
Presentation: Webinars & Presentations
NEW! 2021 June Webinar Analytics: Let's Get Ready!
SSA 2019-Q1 Webinar: Path to Predictive Learning Analytics
SSA 2019-Q2 Webinar: Privacy & Ethics
SSA 2019-Q3 Webinar: Open Learning Analytics In Practice
SSA 2019-Q4 Webinar: Data-driven Decision Making in Higher Education
The Life-cycle of Sustainable Analytics: From Data Collection to Change Management
Empowering Ethical Use of Analytics in Higher Education: Data Governance
Artificial Intelligence in Education: Legal Considerations and Ethical Questions
Learning: Resources, Tools, Conferences
News
Resource Hub (last update: 06/11/21)
We welcome you to submit links to content here
Reading: Books, Journals, Publications, Reports & Articles
Augmented Intelligence and Ethics of Care in 21st Century Advising Practice
Special Issue on Early Prediction and Supporting of Learning Performance
Improving Predictive Modeling for At-Risk Student Identification: A Multistage Approach
Developing Early Detectors of Student Attrition and Wheel Spinning using Deep Learning
Predicting the Risk of Academic Dropout With Temporal Multi-Objective Optimization
Feature Extraction for Next-Term Prediction of Poor Student Performance
Updated by Linda Feng on June 11, 2021