PY2RM-Research Methods

Module Provider: Psychology
Number of credits: 20 [10 ECTS credits]
Level:5
Terms in which taught: Autumn / Spring term module
Pre-requisites: PY1PR Psychological Research
Non-modular pre-requisites: For Single Hons and Joint Hons Psychology students only
Co-requisites:
Modules excluded:
Current from: 2019/0

Module Convenor: Dr Eugene McSorley

Email: e.mcsorley@reading.ac.uk

Type of module:

Summary module description:
PY2RM Research Methods

Aims:
The aims of the module are that the student should extend his or her knowledge of psychological research methods, statistics, and computer packages for data analysis. They will gain practical experience of a variety of methods, analysis techniques, and report writing.

Assessable learning outcomes:
By the end of the module the student will be able to:

- Show the required standard of knowledge about the statistical concepts and techniques that have been taught, and know which techniques are appropriate for particular data
- Use computer packages to implement the statistical methods
- Show knowledge of questionnaire design and the principles underlying the use of questionnaires
- Be able to design, carry out and report experimental studies of psychological phenomena

Additional outcomes:
Students will gain practical experience of using a number of psychological research methods. They will have the opportunity to apply their knowledge of research methodology, data analysis and literature searching in essays and exam questions produced for other Part 2 modules.

Students will participate in research studies being conducted in the School, enhancing their knowledge of research methodology and enabling them to apply their knowledge of research design and procedure to real examples.

Outline content:

- Topics in statistics, including parametric and nonparametric analysis of variance, regression and principal components analysis, and their applications in psychological research.Ìý

- Introduction to questionnaire design, qualitative data analysis and interview techniques.Ìý

- How to choose from statistical methods.Ìý

- Use of a statistical package to analyse and present data.Ìý

- Overview of project planning including ethical issues.

- Designing, running and analysing the data from experimental mini-projects.Ìý

Brief description of teaching and learning methods:

(a) Lectures on research methods and statistics especially General Linear Model and non-parametric statistics; designing and administering questionnaires; psychometrics; qualitative methods such as content analysis; Principal Components Analysis.

(b) Laboratory practical’s on statistical computing and related topics.Ìý

(c) Completion of mini-projects, and associated reports.Ìý

(d) Statistics support workshops, where small groups of students can receive help with any topics relating to statistics they have found difficult in lectures or practical classes, and with the analyses they need to employ in their mini-projects.

(e) Participation in research studies, selected from those available, followed by debriefing, and answering questions on each. Students who have an approved reason for non-participation will be given an alternative assignment of equivalent value.

Contact hours:

Ìý	Autumn	Spring	Summer
Lectures	8	8
Project Supervision	4	4
Demonstration	9	9
Practicals classes and workshops	6	6
Guided independent study:	73	73
Ìý	Ìý	Ìý	Ìý
Total hours by term	100	100
Ìý	Ìý	Ìý	Ìý
Total hours for module	200

Summative Assessment Methods:

Method	Percentage
Report	60
Practical skills assessment	10
Set exercise	30

Summative assessment- Examinations:

This module is assessed by coursework.

Summative assessment- Coursework and in-class tests:

Students will complete two miniproject reports, one in Autumn, one in Spring, that describe an experimental study that they have designed, carried out, and analysed (contributing 60% of overall module mark). Students complete continuous assessment questions throughout the course (30% of overall module mark). Completion of the required hours of research participation (10% of the module mark).

Formative assessment methods:

Penalties for late submission:
The Module Convener will apply the following penalties for work submitted late:

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[1] (or part thereof) following the deadline up to a total of five working days;

where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

The University policy statement on penalties for late submission can be found at:
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.

Assessment requirements for a pass:
A mark of 40% overall

Reassessment arrangements:

Reassessment is byÌýresubmission of an experimental report in August/September

Additional Costs (specified where applicable):

1) Required text books: Field, A (2013). Discovering statistics using IBM SPSS statistics. Sage Publications. ISBN: 9781446249185. Later editions also suitable.

2) Specialist equipment or materials:Ìý

3) Specialist clothing, footwear or headgear:Ìý

4) Printing and binding:Ìý

5) Computers and devices with a particular specification:Ìý

6) Travel, accommodation and subsistence:Ìý

Last updated: 23 September 2019