Radwa El-Khatib
Trainer, Scholarly Publishing &
AI for Research
Tired of playing AI Detective?
Ensuring academic integrity in the AI era is one of the most pressing challenges for educators and institutions. While AI detection tools offer temporary fixes, sustainable impact comes from educational, transparent approaches that empower both students and faculty.
Join fellow educators and academic leaders who are transforming integrity challenges into learning opportunities—not just compliance issues.
Key Takeaways:
- Understand the limitations of detection-only tools and learn what works better for clarity
- Rethink prevention of integrity violations by shifting from policing to proactive guidance
- Promote student responsibility and reflective learning using DocuMark
- Relieve faculty stress and foster students' ownership of content
- Learn how DocuMark ensures responsible AI use and transparent disclosure
- Strengthen your institution's reputation for academic excellence
Who Should Attend This Session?
- Librarians
- Research integrity officers and ethics committee members
- Faculty members, mentors, and thesis supervisors
- Graduate school administrators and academic affairs staff
- University policymakers and leaders
Speaker's Profile
Radwa El-Khatib
Trainer, Scholarly Publishing & AI for Research
Radwa El-Khatib is a publishing and academic integrity specialist with over five years of experience in international scholarly publishing. She specializes in peer review processes, international STEM publishing, AI applications in academic publishing, and research integrity. Her work focuses on helping researchers successfully navigate journal submissions and publish in high-impact journals.
With previous experience at Hindawi, she has worked extensively with all stakeholders in the publishing process - authors, editors, reviewers, and journals. Currently, she is particularly focused on exploring how AI can enhance productivity while maintaining academic integrity, with a special emphasis on supporting educators through responsible AI adoption in academia.