CSC/ECE 517 Fall 2019 - E1990. Integrate suggestion detection algorithm

Introduction

• On Expertiza, students receive review comments for their work from their peers. This review mechanism provides the students a chance to correct/modify their work, based on the reviews they receive. It is expected that the reviewers identify problems and suggest solutions, so that the students can improve their projects.
• The Instructor is facilitated with metrics such as average volume and total volume of the content of the reviews provided by a student.

Current Implementation

• Currently, reviewers cannot see insights on the how many problems and suggestions have been identified in their reviews. They can only submit reviews for their peers.
• Instructor can view insights regarding the text comments entered by the reviewers in terms of the volume of the text. Instructors do not have metrics with regards to the number of problems and suggestions identified by the reviewers.

Problem Statement

• The reviewers can fill in the review comments on others' work, however they do not receive feedback on how effective their reviews are. It would thus make sense to have a feedback mechanism in place, which can identify whether a reviewer has identified problems and provided suggestions for a student or team's project. In order to achieve this, we need to identify the suggestions in the review comments to determine how useful a review would be. This would motivate the reviewers to give better and constructive reviews.
• We would want the instructor of the course to be able to view how many constructive reviews were provided by a reviewer in comparison to the average number of constructive reviews provided by the other reviewers of the course.

Proposed Solutions

• On the student review page, once a student saves his/her review, a pop can show be shown with the feedback - suggestion scores, problem scores and tone analysis among others.
• As an instructor, one might be able to check each student's review scores and his performance as compared with the class. These scores along with the metrics will be shown in the review report page under the metrics column.

Team Information

Mentor: Ed Gehringer Team Name: Pizzamas Members:

• Maharshi Parekh (mgparekh)
• Pururaj Dave (pdave2)
• Roshani (rnarasi2)
• Yash Thakkar (yrthakka)