PLMRDN-Research and Dissertation

Module Provider: Clinical Language Sciences
Number of credits: 60 [30 ECTS credits]
Terms in which taught: Autumn / Spring / Summer module
Non-modular pre-requisites: successful completion of 120 credits' worth of modules
Modules excluded:
Current from: 2018/9

Module Convenor: Dr Christos Pliatsikas


Type of module:

Summary module description:
The aims of this module are to provide the students with an understanding and working knowledge of research methods, design, and statistical analysis and to apply this knowledge to the administration and writing up of a research project (the dissertation).

The dissertation allows students to complete an independent research project in a chosen area of Language Sciences. Students design the project with support from an assigned dissertation supervisor, and complete data collection and analysis. The outcome of the research project is written up as the student’s dissertation.


The aim of this module is to develop high-level skills in critical evaluation and understanding of current research issues and methodologies within the field of Language Sciences. This is achieved through the design, planning and implementation of an independent research project, submitted as a written dissertation of 10-12,000 words.

Assessable learning outcomes:

By the end of the module it is expected that a student will have a detailed knowledge of the topic of the dissertation and will be able to:

• Demonstrate a clear understanding of the theoretical issues addressed in the dissertation

• Demonstrate knowledge and critical evaluation of the relevant research literature

• Outline a proposal for the dissertation, with a clear statement of research questions, methods and plan for data analysis

• Evaluate the ethical implications of their project in detail, through the preparation of an ethics application

• Demonstrate the ability to use a computerised statistical package to code, summarise, explore and interpret data

• Write a clearly structured and supported argument, and present data appropriately

• Discuss the strengths and limitations of their work in the contexts of existing research and within the constraints of their research project

Additional outcomes:
This is a major piece of work and the student is expected to work independently for much of the dissertation. This will develop time management, problem solving, analytical and critical evaluation skills.

Outline content:
The Autumn term includes teaching on research methods and statistics and the application of this knowledge to the analysis of data. Topics covered include data description and summary, probability & distributions, testing hypotheses, and inferential statistics (parametric and non-parametric). Instruction is provided in the use of SPSS/PASW and students are given the opportunity for practical hands-on experience. Data collection, organisation and analysis, both qualitative and quantitative, are explored. Ethical issues in planning and conducting a research project are discussed. The entire research process from the development of a topic to writing the report is explored. Emphasis is also placed on the critical reading and evaluation of research in the literature.
Students are required to submit 5 choices for a dissertation supervisor by Enhancement Week in Autumn term. Allocations are then made, and students are then given support from their assigned supervisor to develop the research proposal poster and ethics coursework. It is the student’s responsibility to do necessary background research and information gathering for their proposed project, with the supervisor playing a supporting role.
The students then undertake a supervised project of at least 6 months’ duration, culminating in the submission of a thesis (8,000-12,000 words). The project should make an original and empirical contribution to the field of language sciences.

Brief description of teaching and learning methods:
•Lectures and practical classes for research methods and statistics
•Individual supervision with the assigned project supervisor.

Contact hours:
  Autumn Spring Summer
Lectures 20
Project Supervision 1 2 4
Practicals classes and workshops 8
Guided independent study 50 100 415
Total hours by term 79.00 102.00 419.00
Total hours for module 600.00

Summative Assessment Methods:
Method Percentage
Written assignment including essay 10
Dissertation 80
Class test administered by School 10

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

Coursework: Students will be required to submit a an ethics application with outline research design (10% of module mark). A class test in Autumn term (1 hour, open book) covering SPSS labs and statistics contributes 10% of the module mark. Students are required to submit a 10,000-12,000 word dissertation by mid-September of their second year (please see the dissertation handbook for specific details on word count).

Formative assessment methods:

During teaching of research methods and statistics (Autumn term): • Online quizzes on Blackboard to back up SPSS lab classes and statistics lectures • Short report / short answer questions, reviewed at the beginning of the lecture on the following week.

Penalties for late submission:
Penalties for late submission on this module are in accordance with the University policy. Please refer to page 5 of the Postgraduate Guide to Assessment for further information:

Assessment requirements for a pass:
A mark of 50% overall.

Reassessment arrangements:

Resubmission of written coursework (research proposal poster and ethics application) and retaking of the classroom test by September. A candidate who has failed the dissertation may re-submit the following academic year, taking into account feedback from the course directors.

Additional Costs (specified where applicable):
1) Required text books:
2) Specialist equipment or materials:
3) Specialist clothing, footwear or headgear:
4) Printing and binding:
5) Computers and devices with a particular specification:
6) Travel, accommodation and subsistence:

Last updated: 20 April 2018


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