Undergraduate Programme and Module Handbook 2023-2024 (archived)
Module SOCI2252: RESEARCH METHODS IN ACTION
Department: Sociology
SOCI2252:
RESEARCH METHODS IN ACTION
Type |
Open |
Level |
2 |
Credits |
40 |
Availability |
Available in 2023/24 |
Module Cap |
|
Location |
Durham
|
Prerequisites
- SOCI1321 Social Research Methods or another equivalent research methods module in the Faculty of Social Sciences and Health or the Faculty of Business (at convenor's discretion).
Corequisites
Excluded Combination of Modules
Aims
- Develop students' conceptual understanding of social research methods and methodology as well as the ethics of social science research.
- Introduce students to a range of methods for analysing qualitative data and develop students ability to deploy these methods in practice.
- Introduce the key principles of basic methods of quantitative data analysis and develop students ability to deploy these methods in practice using SPSS.
- Develop students practical ability to design and implement a research project and therefore prepare students for their final-year Dissertation module.
Content
- Research Design and Process (lectures): This week lecture series outlines key issues which underpin the design and implementation of effective social research, as well as introducing major methods of qualitative data and analysis.
- Group Research Projects (workshops): Students will design and carry out a short research project in small groups. Students will carry out the study in their own time but will receive supervision, guidance and feedback in fortnightly workshops running across the year.
- Quantitative Data and Analysis (practicals): This ten-week lecture/practical series introduces students to the central methods of quantitative data analysis, including methods for describing the distribution of a variable (univariate analysis) and methods for examining relationships between variables (bivariate and multivariate analysis). Classes combine a practical overview of these various methods in the first half, with practical work using SPSS in the second half, to practice undertaking and interpreting statistical analyses.
Learning Outcomes
- Students will know the core principles of designing a social research project: formulation of a research question; operationalisation of core concepts; selection of an appropriate sample/set of cases; and selection of appropriate methods of data collection and analysis.
- Students will understand how research questions, research methods and theoretical issues interlink when designing and implementing a social research project.
- Students will know the main principles of several different methods of qualitative data analysis and be able to identify which method(s) are most appropriate for addressing particular kinds of research questions using particular kinds of qualitative data.
- Students will know the main principles of univariate, bivariate and multivariate analysis as well as statistical inference. Further, students will be able to identify which method(s) are most appropriate for addressing particular kinds of research questions using particular kinds of quantitative data.
- Students will understand the importance of research ethics and risk assessment when designing a social research project as well as how to carry out a project in a manner which is both ethical and safe.
- Students will be able to design a small research project which can effectively address a research problem or question. This will involve: effective operationalisation of core concepts; identification of an appropriate sampling strategy; and identification of methods which can collect and analyse data in a manner which effectively addresses the research question.
- Students will be able to collect primary data using one or more methods of data collection (e.g. interviews, focus groups, ethnography, archive/web searches, surveys/questionnaires, etc.).
- Students will be able to undertake a detailed analysis of qualitative (textual) data using one or more different methods of qualitative data analysis.
- Using SPSS, students will be able to analyse quantitative data by describing the distribution of individual variables (univariate analysis), describing the relationship between two variables (bivariate analysis) and inferring conclusions about a population based on sample data (statistical inference).
- Students will be able to clearly and succinctly communicate the central findings of a research project based on analysis of both quantitative and qualitative data.
- Students will be able to demonstrate a range of communication skills including the ability to: evaluate and synthesise information obtained from a variety of sources (e.g. written, oral, web); communicate relevant information in different ways (e.g. written, oral, tables and graphs, etc); select most appropriate method of communication for different tasks; respond effectively to others; monitor and reflect on use of communications skills.
- Students will be able to demonstrate a range of numeracy skills including the ability to read and interpret tables, graphs, charts; organise and classify data; make inferences from sets of data; adapt numerical strategies to overcome difficulties raised by self-reflection.
- Students will be able to demonstrate competence in the use of IT resources; use the statistical software SPSS; use a range of web-based resources to gather relevant information; adapt learning to overcome difficulties raised by self-reflection.
- Students will be able to demonstrate an ability to work effectively as part of a team including specific abilities to: plan work with others in order to achieve desired outcomes; establish good working relationships with peers; monitor and reflect on the quality of the group work, including group and external feedback on personal contributions; monitor and reflect on use of skills in working with others.
- Students will be able to demonstrate a capacity to improve own learning and performance, including the specific ability to manage time effectively; work to regular prescribed deadlines; engage in different ways of learning including both independent and directed forms of learning; gather necessary information from a range of bibliographic and electronic sources.
Modes of Teaching, Learning and Assessment and how these contribute to
the learning outcomes of the module
- Subject-specific knowledge outcomes are addressed by the Research Design and Practice lectures as well as the lecture components of the Quantitative Data and Analysis workshops. These are reinforced by the Research Proposal summative assignment which tests students on these issues as well as their ability to translate these issues into an effective research design.
- The practical elements of Quantitative Data Analysis workshops will allow students to develop practical aptitude in statistical analysis, thereby addressing subject-specific skills related to data analysis as well as key skills related to communication, ICT and numeracy. These are reinforced by the Data Analysis summative assignment which will assess students on these analytical skills.
- The group research project will both reinforce and test students learning across the module through its requirement to put knowledge and skill into practice.
Teaching Methods and Learning Hours
Activity |
Number |
Frequency |
Duration |
Total/Hours |
|
Research Design Lectures |
18 |
Once per week |
1 Hour |
18 |
|
Research Project Workshops |
10 |
One per fortnight |
2 Hours |
20 |
|
Statistics Practicals |
10 |
One per week for Michaelmas Term only (small groups) |
2 Hours |
20 |
|
Statistics Drop-in Session (Optional) |
10 |
One per week for Michaelmas Term only |
2 Hours: optional attendance |
|
|
Preparation and Reading |
|
|
|
342 |
|
Total |
|
|
|
400 |
|
|
|
|
|
|
|
Summative Assessment
Component: Data Analysis |
Component Weighting: 30% |
Element |
Length / duration |
Element Weighting |
Resit Opportunity |
Data Analysis Report |
2000 words |
100% |
|
Component: Group Research Project |
Component Weighting: 50% |
Element |
Length / duration |
Element Weighting |
Resit Opportunity |
Research Project Report |
4000 words plus 500 word reflection |
100% |
|
Component: Research Proposal |
Component Weighting: 20% |
Element |
Length / duration |
Element Weighting |
Resit Opportunity |
Research Proposal |
2000 words |
100% |
|
(Term 1): Self-assessed statistics practical exercises completed between classes. These exercises help students test their understanding of the key statistics required for their summative assessment.
(Term 2): A short outline of a provisional dissertation topic (max 50 words). Students will be referred to academic colleagues on the basis of their fit with the proposed topic for feedback and guidance on it.
(Term 2): A 10-15 minute group presentation outlining students' research projects undertaken in Epiphany Term. These will receive written feedback from the workshop leader as well as verbal feedback from other students in the same workshop group.
■ Attendance at all activities marked with this symbol will be monitored. Students who fail to attend these activities, or to complete the summative or formative assessment specified above, will be subject to the procedures defined in the University's General Regulation V, and may be required to leave the University