2021-NormalAnalytics

Overview

Need to support student engagement through the data resources currently available. Whilst BB has a great amount of data which is currently broadly discarded in the background in unusable formats. The project proposes two elements:

• Develop a processed dashboard of information useful for gauging understanding and engagement of a unit at both a student by student level and also a cohort overview using log on data, attainment in formative and summative tests and the analytics from videos.
• If possible develop a tutor view where when given a list of students on a programme the software can compile this data across units to again give personal tutors the information required to spot difficulties for students and offer further support.”

User stories

• As a personal tutor, I would like to be able to see student formative assignment data, not just the summative assignment data
• As a personal tutor, I would like to be able to see the entirety of a student's academic data throughout all units, not just unit-by-unit
• As a personal tutor, I would like to be able to compare student assignment data to the general result of the cohort
• As a personal tutor, I would to be able to see a student's average overall grade taking into account the different weightings of each unit
• As a personal tutor, I would like to be able to select the student I want to see the data for from a list of just my tutees
• As a personal tutor, I would like to be able to see student attendance

Quick links and navigation of the project

Documentation

Kanban board

Pull requests

Commits

User guide

Follow this link : http://4c110c5a-eu-gb.lb.appdomain.cloud:8080/

Log in with your given credentials

Example :

• username: jross
• password: password123

Importing Blackboard data

• On initial login, a directory ./NormalAnalytics/target/blackboard will be created (or ./NormalAnalytics/blackboard if running through an IDE)
• In the directory, find the subdirectory for your tutor username
• Within this directory, create a subdirectory with the username of the student who's grades you wish to import
• Students can access their grades on Blackboard via the My Marks icon in the dropdown menu under their username
• From their they can select the assessment you wish to import
• Press Ctrl + S to download the page's HTML files
• Inside the newly downloaded folder, you should find a file named myGrades.html
• Copy this file into the corresponding student directory and rename it to the code of it's unit (For example, to import grades from SPE, you would rename myGrades.html to COMS20006.html
• The database should be updated upon next login

Developer guide:

Dependencies:

Java 11 or higher

Maven

MariaDB

Redis

Node JS

Local build

• Clone the repository

git clone https://github.com/spe-uob/2021-NormalAnalytics.git

• Open the database folder

cd 2021-NormalAnalytics/database

• Open MariaDB command prompt and authentisicate with the following command

mysql -u user -p 

Then will be asked for your password. Finally type the following command to initialise the database:

source [location of project on disk]/2021-NormalAnalytics/database/db-init.sql 

Note: This script populates the database with test data which can be safely removed if you wish

• Enter your database and Redis server credentials in ./NormalAnalytics/src/main/resources/application.properties
• Start Redis server by the following command:

sudo redis-server

Note - you will need sudo password

• Navigate to to ./NormalAnalytics and run the command 'mvn clean install'

• Navigate to ./NormalAnalytics/target and run the command 'java -jar NormalAnalytics-0.0.1-SNAPSHOT.jar'

• Open in browser on localhost:8080

• If you wish to run the frontend seperately navigate to 2021-NormalAnalytics/normal-analytics-frontend folder and run the following command in a terminal of your choice

npm install
npm start

Test

• To run frontend tests run command

npm test

• To run general tests run command

mvn test

Remote Deployment Guide on IBM Cloud

• From the IBM Cloud dashboard, navigate to DevOps > Toolchains in the sidebar
• Create a toolchain
• Select Develop a Kubernetes App
• Change the source provider to Github
• Set the repository type to Existing
• Enter the URL of the repository (Note: if you aren't the owner of the repository, you made need to make a fork and use its URL instead)
• Navigate to Delivery Pipeline
• Create a new API key or enter exisiting
• Set your organisation's Resource Group, Cluster Name and Cluster Namespace
• Click Create
• Click Delivery Pipeline
• Click on the settings gear of Build tile then Configure Stage
• Under Jobs tab, switch the Builder Type to Maven
• Replace the textbox under Build script with

#!/bin/bash
mvn -B -f NormalAnalytics/pom.xml package -DskipTests=True

• Click Save
• Click on the settings gear of Deploy tile then Configure Stage.
• Under the Jobs tab, inside Deploy script, replace what is in the textbox with

source ./check_and_deploy_kubectl.sh

• Click Save
• Begin the Pipeline

If your organisation does not have exisiting remote Redis and/or MariaDB servers, additional Dockerfiles for creating database containers in the redis and database directories respectively

Licence

The system use MIT License.

Ethics

No sensitive is collected in this system, general ethics form could be seen on Ethics form