2017/18 Taught Postgraduate Module Catalogue

PSYC5901M Advanced Research Methods

20 creditsClass Size: 80

Module manager: Dr Liam Hill
Email: l.j.hill@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2017/18

Pre-requisite qualifications

At least and upper second class honours degree in Psychology or a discipline containing a substantial amount of psychology, research methods and statistics training.

Note: students without previous experience in using the statistical software package SPSS to undertake basic forms of analysis (forms typically taught at undergraduate level) will be required to undertake additional foundational training in using this software alongside studying on this module.

Module replaces

PSYC5310M Advanced Research Methods (15 credits)

This module is not approved as an Elective

Module summary

This module expands on the knowledge and skills that students bring with them from their undergraduate degree or other relevant experience, to:1) Advance their ability to understand, evaluate and apply advanced research methods and statistical techniques used in both qualitative and quantitative psychological enquiry.2) Build their confidence in independently applying these techniques to designing studies that investigate their own research questions, and then presenting the findings of such research to a professional, publishable standard.The module is intended to build a student’s confidence in independently planning studies of various design (namely: observational, experimental or qualitative methodologies), giving them the skills to justify the specific design choices they have deemed most appropriate to investigate a given research question. In addition to this the module develops in students an ability to appropriately apply and interpret a range of advanced statistical and qualitative techniques used for psychological enquiry.

Objectives

The module is intended to build a student’s confidence in independently planning studies of various design (namely: observational, experimental or qualitative methodologies), giving them the skills to justify the specific design choices they have deemed most appropriate to investigate a given research question.
In addition to this the module develops in students an ability to appropriately apply and interpret a range of advanced statistical and qualitative techniques used for psychological enquiry.

Learning outcomes
On completion of this module, students should be able to:
- Critically evaluate quantitative designs for research, and apply this knowledge to their own experimental work.
- Demonstrate expertise in the constraints of experimental, non-experimental and quasi-experimental approaches, and when these techniques should be applied.
- Identify the value and importance of qualitative methods in psychological enquiry and when to apply such techniques.
- Apply principles of scaling appropriately to their own work.
- Recognise and evaluate issues in relation to validity and reliability in psychological measurement.
- Using learning from the aforementioned outcomes to relate a research question to appropriate methodology and apply this knowledge appropriately.
- Show critical evaluation of the strengths and weaknesses of various advanced statistical techniques in research.
- Use IBM Statistical Product and Service Solutions (SPSS) to organise and analyse data and to interpret the output of these processes correctly.
- Independently select, interpret and present a range of univariate and multivariate statistical analyses and provide appropriate interpretation thereof.

Skills outcomes
Ability to apply multiple perspectives to psychological issues, recognising that psychology involves a range of research methods, theories, evidence and applications.
Ability to generate and explore hypotheses and research questions.
Ability to carry out empirical studies involving a variety of methods of data collection, including experiments, observation, psychometric tests, questionnaires, interviews and field studies.
Ability to analyse data using both quantitative and qualitative methods.
Ability to present and evaluate research findings.
Ability to employ evidence-based reasoning and examining practical, theoretical and ethical issues associated with the use of different methodologies, paradigms and methods of analysis in psychology.
Ability to use a variety of psychological tools, including specialist software, laboratory equipment and psychometric instruments.

Syllabus

Module content can be subdivided into seven main components.
Five of these are covered in interactive lecture formats (i.e. short presentations interspersed with small-group learning activities designed to develop students’ knowledge understanding and ability to independently apply the skills being taught in these sessions)
1) The fundamentals of research design and planning analysis (week 1)
2) Quantitative Observational Methods for Research (weeks 2-3)
- Testing for associations in the naturally variation between outcomes
- Advanced Tests of natural variation and Multivariate Techniques
3) Quantitative Experimental Methods for Research (weeks 4-5)
- Testing for the impact of experimental manipulation, within- and between-participants
- Advanced Tests of experimental manipulations and Multivariate Techniques
4) Qualitative Methods for Research (weeks 6-7)
- Qualitative methods and epistemology
- Interpretive Phenomenological analysis
5) Selecting appropriates measures for Research (weeks 8-9)
- Principles of quantitative research measurement
- Reliability and Validity in psychological measurement

6) The sixth component focusses on applied skills in (i) cleaning and validating newly collected data and (2) running and interpreting statistical analysis on such data. This component runs in parallel with the interactive lectures, with teaching delivered in a weekly “flipped-classroom” style tutorial (see teaching and learning methods section later for more details).

Having completed all six components previously discussed, students then attend a workshop session in the final week of term (week 11), where they are supported by teaching staff to develop and then debate and discuss ideas for their own independent project proposal. This session is designed to prepare students for working on the final formative assessment for this module (i.e. a project proposal submitted 4 weeks later, in January).

Teaching methods

Delivery type	Number	Length hours	Student hours
Lecture	10	2.00	20.00
Tutorial	11	1.00	11.00
Independent online learning hours			20.00
Private study hours			149.00
Total Contact hours			31.00
Total hours (100hr per 10 credits)			200.00

Private study

Independent online learning – For their statistics tutorials (excepting the 1st tutorial in week 1) students will be set an assignment 1 week in advance of a forthcoming tutorial, which is expected to take them approximately 2 hours to complete (excluding addition recommended reading, see below). Supported by an online discussion board (monitored by teaching staff) students are expected to attempt the assignment prior to attending the tutorial, where solutions and further discussion of the exercise will take place, led by the teaching staff.
Private Study - Students will have 149 private study hours. It is envisaged that this time will be spent as follows:
Required Reading and/or screencasted content supporting each lecture (10 x 3 hours) = 30 hours
Recommended reading supporting each statistics tutorial (11 x 1hours) = 11 hours
Preparation for week 11 project proposal workshop = 3 hours
Completion of Week 6 Formative assessment (Brief Project Proposal) = 22.5 hours
Completion of Week 8 Summative assessment (Qualitative: IPA assignment) = 22.5 hours
Complete of Week 10 Summative assessment (Quantitative: Statistics Assignment) = 22.5 hours
Complete of Final Summative assessment (Project Proposal) = 37.5 hours

Opportunities for Formative Feedback

The students will complete a total of 4 assignments to be submitted throughout the module. Consequently, any student who is struggling will be identified very early on in the module and can be supported accordingly. The assignments used include the following assessments methods:
Short questions (progress monitoring, formative-only, assessment submitted in week 6 of 11)
Application of quantitative methodology (IPA)
Statistical Data analysis and interpretation
Project Proposal (1,500 words)
To pass the module students are required to average a pass grade for the final project proposal and for the other two summative assessment combined (i.e. >50).
Student progress will be monitored throughout by participation in tutorials and the completion of the assignments above, which evidence understanding and knowledge of module learning outcomes. Students are expected to contribute and interact via tutorials and the online discussion board and these contributions will be monitored and supported by the module leader.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Assignment	Analysis and interpretation of data file	25.00
Assignment	Application of interpretative phenomenological analysis (500 words)	25.00
Assignment	Outline project proposal (1,500 words)	50.00
Assignment	Short answer question exercise (500 words)	0.00
Total percentage (Assessment Coursework)		100.00

To pass the module students are required to average a pass grade across all of the assessment tasks (i.e. >50). A compulsory formative assessment will also be set in Week 1 and submitted in Week 6 of term to monitor student progress through the first five weeks. This will take the form of a brief (500 word) short answer question exercise designed to get students to plan and report the essential information necessary to propose a viable research project. This will be submitted in the form of a VLE journal, with formative feedback provided on student responses.

Reading list

There is no reading list for this module

Last updated: 26/04/2017

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