2019/20 Undergraduate Module Catalogue
GEOG2117 Research project and skills in physical geography (geography dissertation route)
10 creditsClass Size: 40
Module manager: Prof Andy Baird
Taught: Semesters 1 & 2 View Timetable
Year running 2019/20
|GEOG1081||Data analysis and physical geography tutorials|
This module is mutually exclusive with
|GEOG2116||Research project and skills in physical geography (geologica|
This module is not approved as a discovery module
Module summaryExcellent critical writing skills, numeracy (statistics and modelling), and an ability to design small research projects are the hallmark of a good geography graduate from a world top 50 university. This module aims to ensure all our graduates have these skills and that they know how and where/when to apply them in a variety of real-world situations.
ObjectivesOn successful completion of this module, students will have gained:
i. A detailed knowledge and understanding of how to design research projects in physical geography.
ii. Competence in the critical analysis of published studies by physical geographers and environmental scientists.
iii. A good level of numeracy (statistics and modelling) for the solving of physical geography problems.
Students successfully completing the module will be able to design their own research project (e.g., dissertation). They will also be able to identify effective strategies for data collection and analysis using a range of statistical and numerical methods, that may include factorial analysis of variance (ANOVA), multiple regression, and time series analysis.
On completion of this module students will be able to:
i. Write confidently and knowledgably on research approaches within physical geography.
ii. Demonstrate understanding of how to design a small research project in physical geography.
iii. Display competence in the use of a range of multivariate statistical and numerical methods.
i. Tutorials based around (a) reading of research papers in physical geography, (b) the design of example research projects, and (c) the design of a dissertation project.
ii. Research design and data analysis. Data analysis methods may include factorial ANOVA, multiple regression, and time-series analysis. Students will be provided with suitable data sets for practicals but will also be taught the principles of data collection.
|Delivery type||Number||Length hours||Student hours|
|Private study hours||71.00|
|Total Contact hours||29.00|
|Total hours (100hr per 10 credits)||100.00|
Private studyThe statistics lectures will include follow-on reading material that students will be expected to complete in preparation for subsequent
lectures and practical classes. Students will also have to prepare for tutorials (they will be set work involving reading of research papers,
preparing reviews, and preparing presentations). Coursework preparation and completion will also be done in private study time as will
revision for the statistics exam.
Opportunities for Formative FeedbackStudent progress will be monitored via tutorial and practical class performance. Students will complete two practice essays for the tutorials and these will be 'informally' marked and returned with detailed comments.
Methods of assessment
|Assessment type||Notes||% of formal assessment|
|Research Proposal||1 x dissertation proposal (1500 words)||50.00|
|Practical||Statistics worksheet (~1500 words)||50.00|
|Total percentage (Assessment Coursework)||100.00|
Re-sit information: If students do not attend the practical exercises they will be set an essay by way of re-sit. If they do attend, but fail or do not submit the practical coursework, they will be allowed to re-sit.
Reading listThe reading list is available from the Library website
Last updated: 26/04/2017
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