CSC/ECE 517 Fall 2018/E1878 Integrate Suggestion Detection Algorithm: Difference between revisions
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CSC-517 Fall 2018 - E1878 Integrate suggestion detection algorithm in Expertiza Project. This Wiki page explains how we are planning to integrate the suggestion detection algorithm in Expertiza project. | |||
==Introduction== | ==Introduction== | ||
===Team=== | ===Team=== | ||
# Ameya Dhavalikar | # Ameya Dhavalikar | ||
| Line 7: | Line 10: | ||
===Background information=== | ===Background information=== | ||
====Expertiza==== | ====Expertiza==== | ||
[http://expertiza.ncsu.edu/ Expertiza] is an Open Source project based on the [http://rubyonrails.org/ Ruby on Rails] framework, supported by National Science Foundation. It is the software to create reusable learning objects through peer review. It is a project where students can submit and peer review learning objects(articles, code, websites, etc). The users of this software include students and professors. Expertiza is used by select professors and students in North Carolina State University, for example. It supports team projects, reviews of projects/teammates, submission URLs, Wiki pages and certain document types. Instructors can create projects and the students can bid for the projects. The students can be assigned teams for a particular project or they may form their own team with fellow classmates. | |||
====Suggestion detection algorithm==== | ====Suggestion detection algorithm==== | ||
Peer-review systems like Expertiza utilize a lot of students’ input to determine each other’s performance. In the same time, we hope students could also gain knowledge from the reviews received thus improve their own performance. In order to make this happen, we would like to have everyone give quality reviews instead of generic ones. Currently, we have a few classifiers that could catch useful components of review comments, such as if it contains suggestions, etc. These classifiers are already ported into web services that we’d like to be integrated into Expertiza. | |||
====Problem statement==== | ====Problem statement==== | ||
#When a student submits a review, we would like to call this web service with the student’s review as the input. We would then want to tell the student whether their reviews contain suggestions or not, so they can make improvements based on the results of the webservice. | |||
#We would also like to evaluate how much time this API is taking and if possible work a way out to improve it. We don’t want the system to be terribly slow. | |||
==Files modified== | ==Files modified== | ||
==Design document== | ==Design document== | ||
Revision as of 21:11, 12 November 2018
CSC-517 Fall 2018 - E1878 Integrate suggestion detection algorithm in Expertiza Project. This Wiki page explains how we are planning to integrate the suggestion detection algorithm in Expertiza project.
Introduction
Team
- Ameya Dhavalikar
- Komal Kangutkar
- Prashanthi Kanniappan Murthy
- Vibhav Nandavaram Abbai Srivaths
Background information
Expertiza
Expertiza is an Open Source project based on the Ruby on Rails framework, supported by National Science Foundation. It is the software to create reusable learning objects through peer review. It is a project where students can submit and peer review learning objects(articles, code, websites, etc). The users of this software include students and professors. Expertiza is used by select professors and students in North Carolina State University, for example. It supports team projects, reviews of projects/teammates, submission URLs, Wiki pages and certain document types. Instructors can create projects and the students can bid for the projects. The students can be assigned teams for a particular project or they may form their own team with fellow classmates.
Suggestion detection algorithm
Peer-review systems like Expertiza utilize a lot of students’ input to determine each other’s performance. In the same time, we hope students could also gain knowledge from the reviews received thus improve their own performance. In order to make this happen, we would like to have everyone give quality reviews instead of generic ones. Currently, we have a few classifiers that could catch useful components of review comments, such as if it contains suggestions, etc. These classifiers are already ported into web services that we’d like to be integrated into Expertiza.
Problem statement
- When a student submits a review, we would like to call this web service with the student’s review as the input. We would then want to tell the student whether their reviews contain suggestions or not, so they can make improvements based on the results of the webservice.
- We would also like to evaluate how much time this API is taking and if possible work a way out to improve it. We don’t want the system to be terribly slow.