Ph.D. candidate, Ammar Almutawa will defend his Ph.D. dissertation on Wednesday, April 12, 2023, at 1 pm. Ammar’s research has explored the potential of an automated feedback system to support instructor self-assessment.
The defence will take place via Zoom. Anyone interested in attending can contact me. The title and abstract for the defence are provided below.
Title: Exploring an Automated Feedback System Framework to Facilitate Instructor Self-Assessment
Instructors in higher education face challenges getting feedback about their instructional practices. This research investigates the creation of a framework to provide automated private feedback to instructors. It limited the investigation to use one instructional practice, the course outline preparation, as the proof-of-concept experiment to demonstrate the potential of automatically providing instructors with feedback about communication, organizational, and planning instructional skills.
This research makes three contributions: a) the identification of essential skills for instructors; b) the necessary components to design the proposed AFSI framework; and c) the exploration of data to demonstrate that feedback topics can be automatically determined. The objective of the AFSI feedback is not to judge the instructorsβ performance but to provide private and immediate feedback that can help instructors to adjust their practice as the semester progresses
Examination Committee:
Chair: Dr. Joe Sawada
Advisor: Dr. Judi McCuaig
Co-Advisor: Dr. Daniel Gillis
Non-Advisory: Dr. Shoshanah Jacobs (Department of Integrative Biology)
External Examiner: Dr. Maria Cutumisu (University of Alberta)