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2021/22 Taught Postgraduate Module Catalogue

PSYC5901M Advanced Research Methods

20 creditsClass Size: 90

Module manager: Dr Carlo Campagnoli

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2021/22

Pre-requisite qualifications

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

Note: Additional support sessions for statistical methods training are offered as part of the module to all students, irrespective of their entry level skills in this area. However, there is a particular expectation that students with limited-to-no previous experience of using statistical software* will engage fully with these support sessions, in order to ensure they sufficiently support their learning.

*e.g. students whose undergraduate research-methods training may not have involved training in the use of software to undertake statistical analysis or who used used substantially different packages from the ones taught on this course.

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.It aims 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 using these techniques to design studies that investigate their own novel research questions3. Ensure they have the capacity to present their research and its findings in a professional, publishable standard format.The module is intended to build a student’s confidence in independently planning studies of various design (namely: observational and experimental quantitative, and 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 the ability to appropriately apply and interpret a range of advanced statistical and qualitative techniques used for psychological enquiry.


The module is intended to build a student’s confidence in independently planning studies of various design (namely: observational and experimental qualitative, and 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 analysis techniques used for psychological enquiry.

Learning outcomes
On completion of this module, students should be able to:

1. Critically evaluate quantitative designs for research, and apply this knowledge to their own experimental work.
2. Apply principles of scaling appropriately to their own work.
3. Recognise and evaluate issues in relation to validity and reliability in psychological measurement.
4. Demonstrate expertise in understanding the constraints of experimental, non-experimental and quasi-experimental approaches, and when these techniques should be applied.
5. Identify the value and importance of qualitative methods in psychological enquiry and when to apply such techniques.
6. Show critical evaluation of the strengths and weaknesses of various advanced statistical techniques in research.
7. Use appropriate statistical software to organise and analyse data and to interpret the output of these processes correctly.
8. Independently select, interpret and present a range of univariate and multivariate statistical analyses and provide appropriate interpretation thereof.
9. Using learning from the aforementioned outcomes to relate a research question to appropriate methodology and apply this knowledge appropriately.

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 examine 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 and psychometric instruments.


Module content can be subdivided into five main components.

Four of these are covered in interactive 'lecture + seminar' formats (listed below, delivered over 8 weeks). These involve 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 the measurement and analysis of psychological functioning (week 1-2)
- Principles of the scientific method and defining quantitative measurement
- Reliability and Validity in psychological measurement
- Statistical methodologies for analysing data and testing hypothesis

2. Quantitative Observational Methods for Research (weeks 3-4)
- Testing for associations in the naturally variation between outcomes
- Advanced Tests of natural variation and Multivariate Techniques

3. Qualitative Methods for Research (weeks 5-6)
- Qualitative methods and epistemology

4. Quantitative Experimental Methods for Research (weeks 7-8)
- Testing for the impact of experimental manipulation, within- and between-participants
- Advanced Tests of experimental manipulations and Multivariate Techniques

The fifth component focusses on applied statistical 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 others, with teaching for it delivered in a weekly “flipped classroom” style tutorial (see teaching and learning methods section later for more details).

Also, to prepare for the coursework assessment of the first four components students attend a workshop session in week 9, where they are supported by teaching staff to develop and then debate and discuss ideas for their own independent project proposals.

Teaching methods

Delivery typeNumberLength hoursStudent hours
Independent online learning hours29.00
Private study hours144.50
Total Contact hours26.50
Total hours (100hr per 10 credits)200.00

Private study

Independent online learning: Practical assignments will continue to be released on a weekly basis, with students expected to complete them remotely during the week and supported via a discussion board. On the last day of the week the 'solutions' guide will be released on Minerva, along with a 30 min pre-recorded 'how-to' guide for the main self-test question in the practical (previously this ‘how-to’ was demonstrated in-person in the practical). A further 60 min 'statistics' drop-in to answer student’s specific individual questions about the practical content will be provided via Blackboard Collaborate/Teams.

Private Study - Students will have 144.50 private study hours. It is envisaged that this time will be spent as follows:
Required Reading and/or video content supporting each lecture (8 x 2.5 hours) = 20 hours
Recommended reading supporting each statistics tutorial (10 x 1hours) = 10 hours*
Preparation for Week 9 project proposal = 3.5 hours
Completion of Week 7 Summative assessment (Qualitative: Methodology Rationale assignment) = 37 hours
Completion of Week 11 Summative assessment (Brief Project Proposal) = 37 hours
Complete of Week 12 Summative assessment (Quantitative: Statistics Assignment) = 37 hours

*There is an additional statistics tutorial in Week 11 (i.e. 2 that week) which specifically covers the statistics assignment, which has no recommended reading associated with it.

Opportunities for Formative Feedback

Students will receive group-based formative feedback in the following ways:

Through the first half of the semester, the weekly `Lecture + Seminar’ sessions will be foreshadowed by online pre-class exercises. These will ask students to post answers/opinions to online discussion boards. Feedback on student’s contributions will then be provided in the lecture/seminar by teaching staff. Within each of the lecture/seminar sessions students will also participate in several small group problem solving and critical discussion exercises per week. These will be overseen by the teaching team, who will provide summation and feedback at the conclusion of each activity.

Students will receive personalised formative feedback in the following ways:

In the weekly statistical practicals students are expected to complete, as part of their weekly exercises, a `self-test’ question prior to attending the session. This self-test question will be discussed, graded and peer reviewed in the class, with lecturer and postgraduate teaching assistants will also providing feedback directly to students in these sessions.

Students also complete three summatively assessed coursework assignments (submitted from mid Nov through to early January):
- Demonstration of understanding of rationale for a specific qualitative methodology (qualitative research methods, word limit 500 words, submitted week 7)
- Brief project proposal (in response to short answer questions, word limit 800 words, submitted week 11)
- Analysis and Interpretation of Datasets (statistical research methods, word limit 1500 words, submitted January)
For each of these pieces of coursework students will receive detailed written feedback on how they could further improve their work. They will also have the opportunity, after receiving this feedback, to meet and discuss further these written comments with teaching staff (e.g. to obtain additional clarification).

A learning module will be designed for release in week 9 explaining the assessment criteria and giving general advice (replacing a 30 min presentation at the start of the workshop). In small tutorial groups (4 students), students will undertake 2x 60 min tutorials in weeks 9 and 10, delivered via Blackboard Collaborate/Teams. In this session they will work through study design and development activities (this will give each student within the group 10-15 min within the tutorial to present, discuss and develop a specific project proposal over two successive weeks).

Methods of assessment

Assessment typeNotes% of formal assessment
AssignmentAnalysis and interpretation of data files (Short Answer Questions)33.33
AssignmentDemonstration of understanding of rationale for a specific qualitative methodology (500 words)33.33
AssignmentAssignment project proposal (800 words)33.33
Total percentage (Assessment Coursework)99.99

Students overall grade will then be determined by a weighted average of these three assignments. The equal weighting of each assessment in determining the overall grade reflect the fact each of these are a distinct and important component of the overall teaching (i.e. qualitative and quantitative methods and statistical analysis), necessary for meeting the overall learning objectives of the module. To pass the module the average grade of a student's across these three assignments must be >50.

Reading list

There is no reading list for this module

Last updated: 22/09/2021


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