2024/25 Taught Postgraduate Module Catalogue

GEOG5967M Dissertation - Consumer Analytics

45 creditsClass Size: 100

Module manager: Dr Like Jiang
Email: L.Jiang2@leeds.ac.uk

Taught: 1 Feb to 31 Aug View Timetable

Year running 2024/25

This module is mutually exclusive with

LUBS5401M

Marketing Dissertation/Project

Module replaces

Replaces GEOG5957M Dissertation – Consumer Analytics, whose final year run was 2022/2023.

This module is not approved as an Elective

Module summary

This module provides students with the opportunity to define and undertake a major piece of independent research on a topic relating to a spatial/geographical component of this programme. The dissertation will be a quantitative data analysis, presented as an academic report. Students wishing to undertake a project related to Marketing should take the equivalent LUBS module. Dissertations will be supervised by academic staff from the Centre for Spatial Analysis and Policy (CSAP).

Objectives

This module will enable students to:
* Develop and undertake a substantive piece of independent research.
* Demonstrate capacity to work independently on a series of research questions over a sustained time period.
* Apply skills, methodologies and techniques introduced within this programme in order to address a substantive research and data analysis problem.
* Personalise their learning experience by researching a topic of interest to them, and of relevance to their future career and professional development objectives.

Learning outcomes
On successful completion of the module students will have demonstrated the following subject learning outcomes:
1. The ability to design and execute a sustained data analysis project, presented as an academic research report.
2. The ability to work independently on a substantive research question, using initiative and reasoned thinking to problem solve.
3. Select, apply and critically evaluate appropriate spatial and statistical analysis techniques and theories in order to address stated research questions.
4. Communicate research findings in an academic style, situating findings within the broader academic literature and wider developments in the field or industry sector.

Skills learning outcomes
On successful completion of the module students will have demonstrated the following skills learning outcomes:
5. Academic. Students will report on their work in a concise and evidence-based way and with integrity.
6. Digital. Students will use digital technology to process and analyse data and to communicate data analysis findings.
7. Work-ready. Using often open and widely-used tools for quantitative data analysis, students will develop technical and IT skills valued in the workplace; students will demonstrate decision-making and critical thinking in making recommendations from their data analysis.
8. Technical. Through the use of open software and programming environments for quantitative data analysis.
9. Sustainability. Student-defined dissertation projects may involve systems-level thinking, and may demonstrate critical thinking and reasoning skills under uncertainty.
10. Enterprise. In defining a dissertation project of their own, students will develop and demonstrate creativity and innovation, a vision and purpose for their work and competency in planning time and resources.

Syllabus

Details of the syllabus will be provided on the Minerva organisation (or equivalent) for the module

Teaching methods

Delivery type	Number	Length hours	Student hours
Supervision	5	1.00	5.00
Lecture	4	1.00	4.00
Private study hours			441.00
Total Contact hours			9.00
Total hours (100hr per 10 credits)			450.00

Opportunities for Formative Feedback

Progress will be primarily monitored via individual supervision, comprising student-led scheduled or ad-hoc contact with their supervisor, to discuss their research and to identify any problems they are facing. Students will receive verbal/email advice/suggestions/comments as a result of these interactions, and supervisors will be able to identify students who may need further support to meet the LOs of this module. Additionally student progress is monitored their research proposal – a formative assignment that is e-mailed directly to supervisors -- enabling students to be matched to an appropriate supervisor and screening to ensure that chosen topics and approaches are feasible and in line with the module objectives.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Assignment	Dissertation project	100.00
Total percentage (Assessment Coursework)		100.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

There is no reading list for this module

Last updated: 30/10/2024

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