See One, Do One, Teach One…Value One: Integration of Artificial Intelligence in Encounter-Based Evaluation Application to Help Teaching Be More Valued

The goal of this project is to incorporate AI to complement and upgrade existing functions in myTE. We plan to invest in 3 features: thematic analysis, data interaction and web analytics. In our current version, myTE compiles all comments in learners’ feedback and presents them in their original form to the users. Using AI, the feedback can be summarized by theme, spellchecked, and paraphrased – which enhances our protection to learners’ anonymity and facilitates ease for user’s CV curation. In terms of data interaction, AI would make use of data available, such as ratings in each type of encounters, as well as teacher recordings, to make meaningful inferences on teaching quality and teaching recommendations. Finally, web analytics support continuous user interface improvement in the backend and analysis on user demographics (e.g., gender, ranking) and how they affect evaluations. We will apply machine learning to look at which functions users are capitalizing on and enhance on those, while removing or switching up some of the less capitalized features.

Faculty Supervisor:

Esther Bui

Student:

Partner:

Entrepreneuro

Discipline:

Computer science

Sector:

Information and cultural industries

University:

University of Toronto

Program: