Module code: MANM383

Module Overview

The Research Methods module aims to help students to develop an understanding of the research process and to undertake research leading to successful completion of their dissertation. It enables students to conduct research independently and also provides them with the knowledge, skills and understanding required to develop their proposal for their dissertation. The module covers ideas, techniques, and methods relevant to different stages of the research process, stressing the interdependence of each stage in conducting effective, coherent and rigorous research. By covering the fundamentals of research methods and research methodologies, this module will enable students to conduct research independently and provide them with the knowledge and understanding needed to do a dissertation.

This module also prepares for the “Advanced Research Methods for Applied Psychology” module in semester 2.

Module provider

Surrey Business School

Module Leader


Number of Credits: 15

ECTS Credits: 7.5

Framework: FHEQ Level 7

JACs code: C810

Module cap (Maximum number of students): N/A

Module Availability

Semester 1

Prerequisites / Co-requisites


Module content

Indicative content includes:


Week 1:

Introduction and overview

How to translate your research “problem” into scientific research? Formulating research aims and objectives

How to find relevant literature? How to critically review your literature?


Week 2:

Qualitative and quantitative research: what to use when?

How do I write a research plan/proposal?

Negotiating access and ethical issues in research

Citing, referencing and plagiarism


Week 3:

Univariate descriptive statistics (Nominal, Ordinal and Scale variables)

Bivariate (Correlation, chi square)


Week 4:

Questionnaire design and measurement

Cronbach’s alpha


Week 5:

Hypothesis testing and sampling

Univariate and bivariate hypothesis tests

Missing data


Week 6:

Factor analysis


Week 7:

Multivariate linear regression analysis


Week 8:

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Qualitative 1


Week 10:

Qualitative 2


Week 11:

Secondary data

Philosophy - Qualitative and quantitative methods revisited

Reporting results

Assessment pattern

Assessment type Unit of assessment Weighting
Examination CLOSED EXAM (2 HOURS) 40
Examination PC LAB (1 HOUR) 20

Alternative Assessment


Assessment Strategy

The assessment strategy is designed to give the students the opportunity to demonstrate their breadth and depth of understanding of both the theory of research methods (through the exam) and its application to research problems (through the exam and their project). The summative assessment strategy has 3 elements:

End of module summative closed question examination conducted under exam conditions (40%). Some of the exam questions will test understanding of the stages of research and ability to distinguish between different research approaches, methods, and procedures. Additionally, the exam will include questions using short cases to test the students’ ability to apply their knowledge and anticipate issues associated with a particular research scenario, as well as questions related to quantitative/qualitative data analysis (such as interpretation of SPSS output).

End of module PC lab examination (20%). Students are provided with a dataset and are asked to analyse and interpret the results.

Throughout the module students will be asked to submit parts of the project (40%). This assessment focuses on the application of the knowledge and ensures that students actively apply their knowledge (approximately 4000 words).

By combining the different types of questions, the examination will test all the learning outcomes of the module and it will equally cover different elements of the module.

Formative assessment: Mid semester (formative) examination in the same format as the end of module examination. Standard answers with be provided and the answers will be discussed in class. Through the strategy outlined above students will already be familiar with the assessment process and have had ample opportunity to practice prior to the summative exam.

In addition students will discuss questions related to a range of research scenarios within the lectures and tutorials.

Module aims

  • • Introduce the fundamentals of the research process
  • • Enable students to effectively define their research problem
  • • Introduce students to philosophy of science
  • • Provide students with an introduction to qualitative and quantitative research methods
  • • Explain the differences between quantitative and qualitative data collection techniques and analysis procedures
  • • Provide students with hands-on experience with data collection and data analysis
  • • Stress the ethical aspects of research and how to embed them into research practice

Learning outcomes

Attributes Developed
001 Understand the stages of the research process and demonstrate an ability to perform them CPT
002 Identify the attributes of a good research topic and turn research ideas into research problems CPT
003 Conduct a review of appropriate literature relevant to a stated research topic. CPT
004 Distinguish between main research approaches and understand philosophy of science KCPT
005 Understand a range of data collection tools in order to design an effective research method KCPT
006 Use quantitative and qualitative data analysis procedures to serve the purpose of a research project KCPT
007 Anticipate ethical issues at each stage of the research process, and be aware of a range of strategies to deal with them KCPT

Attributes Developed

C - Cognitive/analytical

K - Subject knowledge

T - Transferable skills

P - Professional/Practical skills

Overall student workload

Independent Study Hours: 104

Lecture Hours: 22

Tutorial Hours: 24

Methods of Teaching / Learning

The teaching and learning strategy for this module is designed to encourage students to think critically about the different stages of the research process and to engage in evaluating the different research methods and techniques.

 A. The principal teaching and learning method is a two-hour weekly session followed by a tutorial and/or a PC lab including several elements to achieve the module learning outcomes: 

Lectures delivered by the module tutors designed to develop an understanding of theory. 
Student-led class discussions of mini case studies and research scenarios during the lectures and tutorials to put theory into application and transform the acquired knowledge into practice.  
The tutorials allow the students to apply the theory (lecture classes) into practice. To maximise the students’ engagement and consolidate the knowledge, the focus of the tutorials will be on a specific project, as well as PC labs.
In the project, students will go through the whole research process in practice. They will start from a general research “problem” and develop a research plan and conceptual model. They will then develop a questionnaire, administer the questionnaire, analyse the data and write a short report on the results. They will also perform an in-depth interview to get more insight into the same topic and report on these qualitative findings. This is part of the evaluation.

B. Students are expected to support the work undertaken during each lecture by undertaking a number of independent learning activities: 

Preparatory reading with questions to guide their note taking. 
Follow up exercises to consolidate their learning, where appropriate applying this to new situations in particular through a project.
Guided further reading to enable them to extend their knowledge and understanding.

C. To support student learning of statistics, computer lab tutorials will run for 5 weeks, in which students will be trained on the basics of conducting quantitative data analysis using SPSS. Students are expected to support their learning by practising in their own time using the exercises and data sets provided by the lecturers. This will be enabled by their project.

D.The University’s virtual learning environment (SurreyLearn) will be used to support student learning by providing them with additional resources and links to useful websites. SurreyLearn will also be used for further discussion of the module topics between the students and the lecturers as well as the students and their colleagues. Additionally, PowerPoint presentations and case studies used by the lecturers will be placed on SurreyLearn before the lecture so that students may print off copies in time for the lecture.

The ethos of this module is that students will learn best when they become active participants in the learning process and this is reflected in all elements of the module design. For example: 

Students will be expected to participate in lectures through discussions and undertaking a range of other tasks.
Students will be expected to actively engage in all statistics practical classes held in the computer labs.
Not all elements of the curricula will be covered in detail in the lecture programme, students will be expected to find things out for themselves.
Students will be expected to prepare for all lectures by undertaking the pre-reading.
In order to gain high marks in the exam, students will have to participate fully and apply their knowledge in their project. In particular students should undertake the pre work and at least one follow up activity each week. They should also read beyond lecture notes and the recommended textbook. A list of specific reading is provided but the expectation is that this represents a starting point for reading and not an inclusive list. 

Indicated Lecture Hours (which may also include seminars, tutorials, workshops and other contact time) are approximate and may include in-class tests where one or more of these are an assessment on the module. In-class tests are scheduled/organised separately to taught content and will be published on to student personal timetables, where they apply to taken modules, as soon as they are finalised by central administration. This will usually be after the initial publication of the teaching timetable for the relevant semester.

Reading list


Programmes this module appears in

Programme Semester Classification Qualifying conditions
Occupational and Organizational Psychology MSc 1 Compulsory A weighted aggregate mark of 50% is required to pass the module

Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2018/9 academic year.