PhD Funding Policy

DLSPH aims to ensure excellent doctoral students can pursue higher education in public health. For this purpose, PHS has identified a minimum funding threshold to support the studies of PhD students in the funded cohort. For complete details of the PhD funding policy, visit Doctoral Student Policies.

 

GDPHS Statement on Good Academic Standing and Satisfactory Progress

Students admitted into a degree program in the Graduate Department of Public Health Sciences (GDPHS) in the Dalla Lana School of Public Health (DLSPH) are expected to maintain Good Academic Standing in their graduate program, which includes making Satisfactory Progress toward the completion of their degree requirements. Consistent with the policies outlined by the School of Graduate Studies (SGS), failure to maintain good academic standing may result in the consideration of various sanctions which include, but are not limited to, restricting enrolment in courses, ineligibility for financial assistance/awards, lowest priority for bursaries and assistantships, and recommendation for termination from the program.

The GDPHS Statement on Good Academic Standing and Satisfactory Progress can be found here. Any student in who is not in Good Academic Standing will be required to meet with the Graduate Coordinator and the Program Director to discuss his/her performance and to determine actions. The full DLSPH Good Standing and Satisfactory Progress Guideline is also available at the link above.

Guidelines on the use of Generative AI at DLSPH

DLSPH is keeping up to date with the University of Toronto policies and guidelines regarding the use of Generative AI in teaching, learning, and research.

Artificial Intelligence technologies and their use in higher education will continue evolving at a rapid pace for the foreseeable future. DLSPH therefore encourages faculty, staff, and students to stay up to date with U of T guidance and supports regarding the use of AI solutions; and to subsequently use AI solutions thoughtfully in teaching and learning in accordance with these U of T guidance and supports.

  • FAQ’s – this resource is regularly updated by the Office of the Vice-Provost, Innovations in Undergraduate Education provides a comprehensive University-vetted set of responses to frequently asked questions across three categories: 1) about Generative AI, 2) Student use of Generative AI, and 3) Instructor use of Generative AI.
  • Generative Artificial Intelligence in the Classroom – this resource is regularly updated by the U of T Centre for Teaching Support and Innovation. It includes a growing set of supports including an explanation of the educational challenges and opportunities presented by AI technologies and supports for instructors for designing courses and assessments with AI in mind.
  • Guidance on the Appropriate Use of Generative Artificial Intelligence in Graduate Theses – this is provided by the School of Graduate Students. It describes how generative AI tools can be utilized by graduate students in writing graduate theses when the intent is to enhance learning and scholarship while not inhibiting opportunities to develop critical research and writing skills.

DLSPH Instructors and students should at minimum be aware of the following key points based on the above U of T guidance and supports.

  • If using AI, use U of T’s Protected version of Microsoft Co-Pilot – This protected version is now available to all U of T faculty, librarians, staff, and students. This is an enterprise version of an AI-powered chatbot and search engine which better protects the privacy and security of end users (when users are signed into their U of T account). For information and instructions on accessing the enterprise edition, please read and adhere to the U of T Microsoft Copilot guidelines for use.
  • Learn and experiment – AI presents exciting challenges and opportunities as well as risks for public health education and practice. Instructors and students are encouraged to learn about AI technologies and experiment with how they can be used appropriately to improve public health education and enhance health and well-being for populations.
  • Be clear and transparent – The use of any AI solutions in any aspect of academic work must comply with University of Toronto Code of Behaviour on Academic Matters and be informed by relevant School of Graduate Studies Guidelines; for example – Guidance on the Appropriate Use of Generative Artificial Intelligence in Graduate Theses and Guideline for Graduate Student Supervision & Mentorship.
    • For Courses – use of AI must comply with instructor expectations around the use (or non-use) of AI in their courses. Instructors should include a statement around the use of AI in their course syllabus. The PHS syllabus template and IHPME syllabus template include options for AI use in courses, sample  statements, and links to U of T guidance. Students must ensure they use AI in courses as instructed.
    • For Research – AI must only be used with the prior approval of the student’s supervisor(s) and supervisory committees for students in research-based programs.

For Practicums – AI must be used in accordance with practicum preceptor expectations and guidance. Student can ask their instructor or program director for assistance if they have concerns regarding their practicum preceptor’s expectations.