RESEARCH METHODS FOR APPLIED PSYCHOLOGY - 2022/3
Module code: MANM383
In light of the Covid-19 pandemic the University has revised its courses to incorporate the ‘Hybrid Learning Experience’ in a departure from previous academic years and previously published information. The University has changed the delivery (and in some cases the content) of its programmes. Further information on the general principles of hybrid learning can be found at: Hybrid learning experience | University of Surrey.
We have updated key module information regarding the pattern of assessment and overall student workload to inform student module choices. We are currently working on bringing remaining published information up to date to reflect current practice in time for the start of the academic year 2021/22.
This means that some information within the programme and module catalogue will be subject to change. Current students are invited to contact their Programme Leader or Academic Hive with any questions relating to the information available.
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.
Surrey Business School
ZHOU Ying (SBS)
Number of Credits: 15
ECTS Credits: 7.5
Framework: FHEQ Level 7
JACs code: C810
Module cap (Maximum number of students): N/A
Overall student workload
Independent Learning Hours: 117
Lecture Hours: 22
Tutorial Hours: 11
Prerequisites / Co-requisites
Indicative content includes:
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?
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
Univariate descriptive statistics (Nominal, Ordinal and Scale variables)
Bivariate (Correlation, chi square)
Questionnaire design and measurement
Hypothesis testing and sampling
Univariate and bivariate hypothesis tests
Multivariate linear regression analysis
|Assessment type||Unit of assessment||Weighting|
|Examination||CLOSED EXAM (2 HOURS)||50|
|Coursework||INDIVIDUAL ASSIGNMENT (APPR. 4000 WORDS)||50|
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 and its application to research problems. The assessment strategy has 2 elements:
The formative and summative assessments (50% of the final module mark) consist of an individual assignment (approximately 4000 words) and a final exam. The indivdiual assignment focuses on the transfer of knowledge to practice and ensures that students actively apply their theoretical knowledge to analysing research questions.
The second assessment takes the form of a closed book examination conducted under exam conditions at the end of the semester (50% of the final module mark). Some of the exam questions will test understanding of the stages of research and the ability to distinguish between different research approaches, methods and procedures. Additionally, the exam will test the students’ ability to apply their knowledge and anticipate issues associated with a particular research scenario, as well as their understanding of quantitative/qualitative data analysis.
By combining the different types of questions, these assessments will test all the learning outcomes of the module.
- • 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
|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|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
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 combination of weekly lectures and PC lab sessions 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.
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.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. 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. 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.
Upon accessing the reading list, please search for the module using the module code: MANM383
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 2022/3 academic year.