CSMPRNU: MSc Project

Module code: CSMPRNU

Module provider: Computer Science; School of Mathematical, Physical and Computational Sciences

Credits: 60

Level: Postgraduate Masters

When you'll be taught: Semester 2 / Summer

Module convenor: Dr Carmen Lam, email: carmen.lam@reading.ac.uk

NUIST module lead: Xia Min, email: xiamin@nuist.edu.cn

Pre-requisite module(s):

Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2024/5

Available to visiting students: No

Talis reading list: No

Last updated: 21 May 2024

Overview

Module aims and purpose

Students enrolled in MSc Data Science have to do a dissertation project, which is a major component of the study programme. The student must pass this module in order to be awarded an MSc degree. This MSc project must be done individually and contain an element of original work.  

The aim of the dissertation is to allow MSc students to define and execute a piece of research on a specific topic of their choice, with direction from an academic supervisor, and to effectively communicate their findings in an appropriate form. The project will usually be allied to some current research done in the Department/School. 

There will be scheduled training sessions to cover key concepts, methods and techniques that are required in the process of a research project from the formulation of research problems to devise and validate outcomes. 

This module also encourages students to develop a set of professional skills, such as problem solving;  creativity and critical thinking; hypothesis generation and testing; literacy; action planning and decision making; self-reflection; negotiation and persuasion; and organisation and time management; professional communication (with supervisors and peers); initiative and self-motivation; software design and development; effective use of commercial software; end-user awareness; presentation skills and technical report writing for technical and non-technical audiences. 

Module learning outcomes

By the end of the module, it is expected that students will be able to:

1. Formulate research questions, select and justify suitable research methods, and conduct research projects;
2. Critically evaluate research materials from a wide range of literature sources;
3. Apply suitable approaches, techniques and tools to design and implement data science solutions for data collection, data analysis and validation of scientific results;
4. Consider and address ethical and professional issues; and
5. Present and report research results in a professional manner.

Module content

This module covers the following in-module training aspects: 

• Identify and formulate research problems/hypotheses;  
• Adopt mixed methods for design research (including methodology, experiment, result validation and verification) 
• Carry out literature review and conduct critiques on findings; 
• Propose research project and manage execution of the project; and 
• Address social, legal and ethical issues involved in research. 

Structure

Teaching and learning methods

The main part of this module is the research- based project. For each of dissertation projects, it will be guided by a supervisor. 

The in-module training sessions cover key concepts, methods and techniques that are required in the process of a research project from the formulation of research problems to devise and validate outcomes. 

Study hours

At least 5 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 50% to pass this module.

Summative assessment

Penalties for late submission of summative assessment

The Support Centres will apply the following penalties for work submitted late:

Assessments with numerical marks

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of three working days;
• the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
• where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

• where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf

You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

• Literature review 
• Project specification  

Reassessment

Additional costs