Suggested Capstone Projects
Semester 2 – 2019
Each group needs to select one of the following projects:
Project 1: Match Making System
You are required to develop a web based matching system, such as matching of jobs required by employers to skills of potential employees. Here are some examples:
• Potential employers post the details of the kinds of employees they are looking for and job seekers post their skills and experience and the system matches employers to job seekers.
• Sellers post descriptions of items they have for sale and buyers post descriptions of items they want to buy and the system matches buyers and sellers.
• Trades people post their expertise and location and householders post details of problems they want fixed or jobs they want done.
• A matchmaking site.
• Any other producer-consumer situation of your choice.
The system must:
• Permit users to register
• Provide the necessary transactions for data entry
• Provide appropriate matching algorithms
• Operate from desktops and mobile devices
• Provide appropriate admin functionality
You can add any other enhancements that you think would be useful and appropriate.
Project 2: Budding Share Market Investor
You are required to write a stock market game to introduce budding investors to learn the risks and opportunities share market-trading presents. Users should be given $1,000,000 (bogus money) initially and be allowed to buy and sell the shares at current price from the ASX. Assume the brokerage cost is made up of two parts: a fixed charge ($50) and a charge that is a percentage of sale or purchase (0.25% for sale and 1.0% for purchase) that may be lowered when high volumes are traded.
Users should be provided with the following functionality:
• Register as a stock market player
• Login as a user
• Open a Trading Account
• List the average price of shares in possession and current number of shares held
• Support transactions for the buying and selling of shares
• Track the movement of share price (at regular intervals, say every 1 hour) and plot the graph
• List a summary of transactions within specified dates
• View current balance in dollars and current stock value
• Maintain a leader-board
• Provide appropriate admin functionality
You can add any functionality that you think would be useful, for example algorithms to determine when and what shares to buy or sell. Also, further functionality such as invite and add friends, transfer money to your friend(s), and implementing the notification functionality (displaying the notifications on being invited as a friend or being sent money from a friend). Another option could be implementing/delivering the product on both web/desktop and mobile versions.
Project 3: Car Share Scheme
You are required to develop a web/mobile application for a company running a car share scheme. The company owns a number of cars which can be parked at a number of locations in the city. Users of the scheme will book a car for some period of time, use it and then return it to an empty location (the return location could be different than the book location). The system needs to provide the necessary transactions and data management/storage capabilities to support this kind of business.
The system must:
• Register users
• Keep all car data and rental information
• Provide a way for a user to book (and return) a car for a particular time and location
• Have an option to find the nearest available car based on the user’s location
• Provide a report for users to see their past bookings with date, time and location information
• Be platform-independent and work through web, or any mobile platform.
• Have enough dummy data to test user scenarios in different locations and with different cars
Project 4: Learning Analytics Visualisation (LAV)
You are required to conduct an investigation on a data set of student interactions with a learning management system and write a report on your findings. The data is at https://www.nature.com/articles/sdata2017171. Here is a description of the data from the website:
Learning Analytics focuses on the collection and analysis of learners’ data to improve their learning experience by providing informed guidance and to optimise learning materials. To support the research in this area we have developed a dataset, containing data from courses presented at the Open University (OU). What makes the dataset unique is the fact that it contains demographic data together with aggregated clickstream data of students’ interactions in the Virtual Learning Environment (VLE). This enables the analysis of student behaviour, represented by their actions. The dataset contains the information about 22 courses, 32,593 students, their assessment results, and logs of their interactions with the VLE represented by daily summaries of student clicks (10,655,280 entries). The dataset is freely available at https://analyse.kmi.open.ac.uk/open_dataset under a CC-BY 4.0 license.
You need to think up interesting questions to ask about the data and work out a method for answering them. For example you might ask “Is it possible to predict a student’s grade based on their interactions with the learning management system”. To answer the question you will need to extract relevant data from the dataset and prepare it for a suitable predictive algorithm.
The report should explain the methodology and software tools that you used and any interesting things that you found. It should include suitable visualisations of the data. Any scripts or programs developed should be included in an appendix.