Undergraduate Programme and Module Handbook 2026-2027
Module GEOL2341: Research Skills for Geoscientists
Department: Earth Sciences
GEOL2341: Research Skills for Geoscientists
| Type | Tied | Level | 2 | Credits | 20 | Availability | Available in 2026/2027 | Module Cap | Location | Durham |
|---|
| Tied to | F600 |
|---|---|
| Tied to | F630 |
| Tied to | F643 |
| Tied to | F644 |
| Tied to | F645 |
| Tied to | F665 |
| Tied to | CFG0 |
| Tied to | FGC0 |
Prerequisites
- GEOL1151 Introductory Data Science for Geoscientists
Corequisites
- None
Excluded Combination of Modules
- None
Aims
- This module will equip students with the skills and hands-on experience needed to design and execute geoscientific analyses, and to interpret and communicate results.
- Students will be grounded in the fundamentals of scientific theory, and will learn through practice how these concepts apply to real-world geoscientific reasoning.
- Training in underpinning concepts of Earth observation and remote data acquisition will equip students to process, visualize and communicate geospatial data to solve research questions (including from their own datasets) and inform end-users.
Content
- Key concepts in scientific theory
- Designing an effective scientific experiment
- Hypothesis testing
- Statistical tools for data analysis and interpretation
- Assessment and evaluation of uncertainty
- Communicating evidence to different audiences, including through scientific writing and visual data presentation.
- Geoinformatics concepts, including the practice of geoinformatics and data analysis using GIS software.
- Digital cartography and data plotting techniques.
- Case studies to highlight the application of remote sensing and geoinformatic methods to a range of Earth Science topics, such as geohazards, resource estimation and environmental assessment.
Learning Outcomes
Subject-specific Knowledge:
- Fundamentals of the scientific method.
- What is a hypothesis?
- How to design an experiment to test a hypothesis.
- How to use statistics to analyse geoscience data.
- Fundamentals of remote sensing and data analysis methods.
- How to investigate Earth processes using geoinformatic methods.
- Capabilities and limitations of Earth observation methods.
- Enhanced understanding of selected Earth processes.
Subject-specific Skills:
- Deductive and inductive reasoning for geoscientists.
- Experimental design for geoscientists.
- Obtaining geoscientific datasets.
- Advanced GIS mapping and modelling.
- Visualization and statistical analysis of raw geoscience data.
- Interpretation of Earth observation datasets.
- Using hypothesis driven analysis to understand limitations of results.
- Evaluation of uncertainties.
- Preparation and presentation of geoinformatics outputs.
- Application of geospatial analysis to selected geoscience topics.
Key Skills:
- Critical analysis, practical competency.
- Independent study.
- Scientific writing.
- Communication and presentation for a range of audiences.
- Troubleshooting data and software issues and self-teaching via online tools.
- Personal effectiveness.
- Problem solving .
Modes of Teaching, Learning and Assessment and how these contribute to the learning outcomes of the module
- The module is delivered through two-hour workshops (two per week), supported by handouts, directed reading, and independent learning.
- A written report at the end of Term 1 will allow students to demonstrate their use of scientific and statistical methods to design, implement and evaluate an effective experiment, and to communicate their findings.
- In the final assessment students will produce a digital output that demonstrates their application of skills and knowledge to geoinformatic or geospatial datasets.
Teaching Methods and Learning Hours
| Activity | Number | Frequency | Duration | Total/Hours | Attendance Monitored |
|---|---|---|---|---|---|
| Workshops | 40 | 2 per week | 2 hours | 80 | Yes ■ |
| Preparation and Reading | 120 | ||||
| Total | 200 |
Summative Assessment
| Component: Summative Assessment | Component Weighting: 100% | ||
|---|---|---|---|
| Element | Length / duration | Element Weighting | Resit Opportunity |
| Report | Four pages | 30% | |
| Digital Output | 70% | ||
Formative Assessment:
Formative assessment will be provided through self-graded exercises, in workshops, and through peer feedback.
■ Students who do not attend monitored activities shown under Teaching Methods and Learning Hours, or who fail to complete the summative or formative assessment(s) specified above, may be subject to the Academic Progress procedures defined in the University's General Regulation V, and may be required to leave the University.