2017/18 Undergraduate Module Catalogue
LUBS2910 Management Research and Analysis
20 creditsClass Size: 150
Module manager: Nick Jackson
Email: n.jackson@leeds.ac.uk
Taught: Semesters 1 & 2 (Sep to Jun) View Timetable
Year running 2017/18
This module is not approved as a discovery module
Objectives
This module aims to equip students with a variety of practical skills in research design, methodology, and analysis, both quantitative and qualitative, which are applied to evaluate and undertake research across the management field. These practical skills will be of particular use for the students’ final year research dissertations. This core module on the BA Management programme will directly prepare students to undertake their own independent empirical research studies for their final year research dissertations.Learning outcomes
Upon completing this module, students will be able to:
- Recognise and describe the different approaches to management research and the different epistemologies they represent
- Recognise and contextualise the practical and ethical issues of conducting management research in organizations
Skills outcomes
Upon completing this module, students will be able to:
Transferable
- Design research studies, analyse data, and evaluate information
- Apply research approaches to solve problems
Subject specific
- Design, formulate, and carry out quantitative and qualitative research studies including collecting the appropriate data to test hypotheses and research questions
- Apply quantitative and qualitative research approaches to conduct management research in organizations
- Report management research in a clear and thorough manner suitable for the intended audience
Syllabus
Indicative content
Lectures:
1. Research processes and approaches
2. Literature reviews
3. Overview of quantitative research
4. Questionnaires
5. Quantitative research design
6. Correlation and regression
7. T-tests and ANOVA
8. Reporting management research
9. Qualitative research interviews
10. Specialist Qualitative methods
11. Qualitative data analysis
Seminars:
1. The research process
2. Quantitative research
3. Qualitative research
Practicals:
1. Qualitative data analysis
2. Introduction for quantitative analysis with SPSS
3. Correlation and regression with SPSS
4. T-tests and ANOVA with SPSS
Teaching methods
| Delivery type | Number | Length hours | Student hours |
| Lecture | 22 | 1.00 | 22.00 |
| Practical | 4 | 2.00 | 8.00 |
| Seminar | 3 | 1.00 | 3.00 |
| Private study hours | 167.00 | ||
| Total Contact hours | 33.00 | ||
| Total hours (100hr per 10 credits) | 200.00 | ||
Private study
Background reading for each lecture = 55 hours (2.5 hours for each of the 22 lectures)Independent practice with SPSS/NVivo software = 20 hours (5 hours for each of the 4 practicals)
Preparation and writing of the assignment = 55 hours
Revision for the examination = 37 hours
Total independent learning = 167 hours
Opportunities for Formative Feedback
Students will receive informal feedback on their learning during the three seminars and four practical sessions. Formally, they will receive feedback on their coursework (project report) and the examination. As well as being of use to this module the feedback they recieve is intended to improve their performance on their final year research dissertations.Methods of assessment
Coursework
| Assessment type | Notes | % of formal assessment |
| Project | 4,000 words. The coursework will comprise a mini research project based on datasets they will recieve. | 60.00 |
| Total percentage (Assessment Coursework) | 60.00 | |
Resit will be 100% by exam.
Exams
| Exam type | Exam duration | % of formal assessment |
| Standard exam (closed essays, MCQs etc) | 2 hr 00 mins | 40.00 |
| Total percentage (Assessment Exams) | 40.00 | |
Resit will be 100% by exam.
Reading list
The reading list is available from the Library websiteLast updated: 01/12/2017
Browse Other Catalogues
- Undergraduate module catalogue
- Taught Postgraduate module catalogue
- Undergraduate programme catalogue
- Taught Postgraduate programme catalogue
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