What your learning data helps us understand.

EduAlly began as independent student research with faculty guidance and became a Fall 2024 classroom pilot. The goal was practical: explore whether course-grounded AI could give students timely, actionable feedback while helping instructors meet varied learning needs.

The work has since expanded through SUNY Brockport's ACM SIGAI Student Chapter and a multi-campus collaboration supported by the 2024–2025 and 2025–2026 SUNY Innovative Instruction Technology Grants. Research helps the team understand what works, what confuses users, and how educational AI can be made more useful, accessible, and responsible.

The data available for educational and research purposes may include:

• account and profile details;
• course enrollment, assigned material, submissions, answers, grades, and feedback;
• AI prompts, responses, conversation threads, and the course context used to generate feedback;
• feature usage, model, token, timing, and performance information;
• messages, support requests, files, and feedback you choose to provide; and
• technical, session, device, error, and security records.

Not every study uses every category. Study-specific materials should explain the data relevant to that study.

Platform data can be used to deliver feedback and course features, evaluate whether EduAlly helps learners, compare patterns of use, identify interface problems, assess reliability and safety, improve AI workflows, develop accessibility features, and support scholarly reports or presentations.

The team may combine activity across participants and remove or reduce direct identifiers before analysis or reporting. Public research outputs should focus on grouped results or de-identified examples rather than naming individual students, unless a person has separately agreed to be identified.

Access may be available to authorized instructors and course staff, EduAlly administrators who operate the service, and approved faculty or student researchers whose work requires it. Service providers may process information for hosting, storage, AI, communications, email, or error monitoring.

Access should be based on role and purpose. Researchers and staff should use only the data needed for their approved work and follow applicable institutional, study, and confidentiality requirements.

Using a classroom tool and participating in a specific research study are not always the same thing. Your course or study materials should explain whether research participation is optional, what data is involved, and how to ask questions or withdraw. Those materials control for the specific study.

Withdrawing from a study may not remove academic records that the institution must keep, data already used in completed analysis, or data that has already been de-identified so it can no longer reasonably be linked back to you. Ask the named study contact what withdrawal means in your situation.

Research and educational records may be retained for different periods based on study protocols, course requirements, security needs, grants, institutional policy, and law. EduAlly does not promise one universal deletion date for every record.

AI output is probabilistic and research findings have limits. A pattern observed in one course or group may not apply everywhere. EduAlly's research should be understood as an ongoing effort to learn, test, and improve—not proof that automated feedback is always correct.

SUNY Brockport has documented EduAlly's development and recognition:

• Creating an AI Study Buddy
• SUNY Online Summit recognition
• SUNY AI Symposium showcase

For the rules that cover personal information generally, read the Privacy Policy. For practical protections, read How We Keep Data Safe.