module specification

MA5051 - Project Management (2017/18)

Module specification Module approved to run in 2017/18
Module title Project Management
Module level Intermediate (05)
Credit rating for module 15
School School of Computing and Digital Media
Total study hours 150
45 hours Scheduled learning & teaching activities
105 hours Guided independent study
Assessment components
Type Weighting Qualifying mark Description
Coursework 20%   Interim Report 750 words max (Submission in Class)
Coursework 60%   Group Coursework 2100 words max
Coursework 20%   Individual viva (10 minutes)
Running in 2017/18
Period Campus Day Time Module Leader
Autumn semester North Tuesday Afternoon

Module summary

This module introduces a selected range of Operational Research techniques that are commonly used for solving a variety of small to medium size problems, through the medium of spreadsheet and other suitable software. It also enables the student to investigate real-life problems of business and industrial problems of varied complexity.

Module aims

To enable students to understand and apply some of the important business-modelling
techniques, through the use of group-based problem investigations and the study of real-life
cases taken from the literature.
- To appreciate the ways in which computer packages can assist in the solution of problems and
be able to interpret and report the results in a clear and concise manner.
- To present a properly structured written report on a technical subject.


Features of selected spreadsheets and suitable software.
Preliminary Topics in Probability Theory
Critical Path Analysis, Gantt charts, Cost analysis, Resource allocation
Project evaluation and review techniques
Decision Theory/Trees

Learning and teaching

Teaching methods will include a range of the following: tutor led seminar discussions, student led discussions, small group discussions and exercises, individual exercises, lectures given by tutor. The teaching methods will support the main aim of encouraging independent lifelong learning. Tutorials will be student centred using carefully graduated exercises to build up student's confidence and self-esteem and will also provide the opportunity for students to reinforce learning and demonstrate their skills and receive individual advice from their tutor.
Materials for learning are provided through an integrated learning environment (currently WebLearn).
Blended learning is incorporated by using on line resources as a medium for communication (both peer and tutor-led) and will also provide additional materials to stimulate the student interest and broaden their horizons.
Students are expected to spend a substantial proportion of their study time on the group The tutorial sessions and workshops will provide an ideal setting for students to meet up with their group members on regular basis and carry out their discussions and investigations.

Learning outcomes

On successful completion of this module, students should be able to:
LO1 Understand the detailed technical nature of Critical Path Analysis
LO2 Be able to prepare appropriate input data for software-based models, obtain numerical solutions, perform sensitivity analyses and interpret the outputs in the context of specific problems.
LO3 Structure and draw decision trees, assign probabilities, estimate payoffs and obtain expected monetary values.
LO4 Be able to work effectively within a small group on a problem solving activity and communicate the results in such a manner that a wider non-technical audience can understand.

Assessment strategy

The assessment consists of two elements interim report (LO1,LO4) and a group coursework
In the group coursework (LO1-LO4) students are expected to work in small group on a real-life-related problem taken from the literature. Students will have an opportunity to demonstrate their skills in the following activities.
- Preliminary investigation concerning the problem in hand.
- Selecting a suitable method for solving the problem.
- Appreciating the limitation of the techniques and the impact of any simplifying assumptions on
  the validity of the solution.
- Gathering input data and using software for analyses.
- Contributing, as a team member, towards successful completion of the project and offering a critical evaluation of the work of the other team members.
- Interpreting the results and writing a comprehensive report.


Winston WL and Albright SC (1997), Practical Management Science: Spreadsheet Modelling and Applications, Duxbury Press, New York.

Anderson DR, Sweeney DJ and Williams TA., (current annual edition),
Management Science – Quantitative Approach to Decision Making, International Thomson Publishing