CSC/ECE 517 Fall 2015 E1580 Text metrics

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Revision as of 00:43, 14 November 2015 by Msaikia (talk | contribs) (added test plan)
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Introduction

Expertiza is an open-source peer-review based web application which allows for incremental learning. Students can submit learning objects such as articles, wiki pages, repository links and with the help of peer reviews, improve them. The project has been developed using the Ruby on Rails framework and is supported by the National Science Foundation

Project

Purpose

The current version of The Expertiza Project has an automated meta-review system wherein the reviewer gets an e-mail containing various metrics of his review like relevance, plagiarism, number of words etc. , whenever a review is submitted. The purpose of this project is to give students some metrics on the content of the review when the automated meta reviews are disabled. This also includes the addition of new relevant metrics which can help the reviewers and instructors to gain insight into the reviews.

Scope

The scope of the project is limited creating a system where the reviewer and the instructors can view metrics for the submitted reviews.The user or the instructor need to manually visit the link to view the metrics.The instructor can view the metrics for every assignment available whereas the user can view only the metrics of the assignments relating to himself.The scope doesn't include any automated viewing of reports for the metrics.Since the project is mainly related to giving reports about the existing data, we will not be modifying the results saved by the actual peer-review mechanism.The scope also excludes any change of the actual peer review process i.e. submitting a review of an assignment or adding an assignment to a user profile.

Task Description

The project requires completion of the following tasks

  1. create database table to the metrics
  2. create code to calculate the values of the metrics and also ensure that the code runs fast enough (can give results within 5 seconds) as the current auto text metrics functionality is very slow and diminishes user experience.
  3. create partials for both students and instructors that show for each assignment:
    • Total no.of words
    • average no. of words for all the reviews for the particular assignment in a particular round
    • if there are suggestions in each reviewer's review
    • the percentage of peer reviews that offer any suggestions
    • if problems or errors are pointed out in the reviews
    • the percentage of the peer-reviews which point out problems in this assignment in this round
    • if any offensive language is used
    • the percentage of peer-reviews containing offensive language
    • No.of different words in a particular reviewer’s review
    • No. of questions responded to with complete sentences
  4. make the code work for an assignment with and without the "vary rubric by rounds" feature
  5. create tests to make sure the test coverage increases

Workflow

Use Cases

  1. View Reviews Text Metrics as Reviewer: As a reviewer, he/she can see the text metrics of individual reviews as well as aggregate metrics for all the reviews done for an assignment/project.
  2. View Reviews Text Metrics as Reviewee: As a reviewee, he/she can see the text metrics of individual reviews received from reviewers as well as aggregate metrics for all the reviews received for an assignment/project.
  3. View Reviews Text Metrics as Instructor: As an instructor, he/she can see the text metrics of reviews received by any team for a particular project/assignment. The instructor can also see the text metrics of the reviews done by any reviewer.


Test Plan

  1. For use case 1, test whether the text metrics Db has entries populated for each type of metrics (no. of words, no. of offensive words, etc), once the reviewer submits any reviews.
  2. For use case 2, test if the reviewer can see the text metrics of individual reviews received from all reviewers.
  3. For use case 3, test if the instructor can see the text metrics of reviews received by each team for a project/assignment. Also, test if the instructor can see the text metrics done by any reviewer.


Details of Requirements

Hardware requirements

  • Computing Power: Same as the current Expertiza system.
  • Memory: Same as the current Expertiza system.
  • Disk Storage: Same as the current Expertiza system.
  • Peripherals: Same as the current Expertiza system.
  • Network: Same as the current Expertiza system.

Software requirements

  • Operating system environment : Windows/UNIX/OS X based OS
  • Networking environment: Same as it is used in the current Expertiza system
  • Tools: Git, Interactive Ruby