In 2017, the Product Team that led the redesign of MediaShare filed multiple patents on our “Contextual Commenting” system (i.e. Various but related patents with this title "Systems and Methods for Automated Aggregated Content Comment Generation," patents available here: https://patents.justia.com/search?q=anne+hong+sadauskas). Among the commenting systems, we prototyped applications for commenting with rubric analysis in virtual reality and augmented reality. Some of these applications used Ai-learning models, such as Natural Language Processing (NLP) and sentiment analysis.

In 2019, after a Design Research Event, Dr. Samuel Downs and I collaborated on this concept of a commenting visualization. As the Learner scrolls through an essay, a floating visualization, similar to a Floating-Action-Button (FAB), would stick to the bottom of the window. This graphic would show the frequency of a type of comment (i.e. Misspelled word), or sentiment analysis based on NLP. I worked with a Learning Designer, Dr Samuel Downs, to make it useful to Instructors. Previously, I had designed it as a comment-filter for Learners. We also experimented with this feature as feedback from Instructors in other forms of assessments and/or assignments. As an a11y and coding exercise, I looked into both Canvas and D3 frameworks.