GE4-301 Fundamental Research Methods

Contents and structure

The overall aim is to provide all students with a fundamental grounding in three broad classes of data analysis techniques: Quantitative data analysis (statistics), Qualitative methods, and Geographic information systems (GIS). By considering how each method influences every stage of a research project, the course aims to improve student's abilities to understand and critically appraise published literature and to develop skills in project design and writing up.

The course will cover:

• Experiment design: theory of scientific methods, research questions, planning research, choosing methods, sampling, replication and randomisation, organisation
• Collecting data: collecting spatial data, climatic data, historical and secondary data sources, quantitative data collection (observations, measurements, experimentation), qualitative data collection (interviews, questionnaries, participatory research).
• Representing data: making maps, graphs and diagrams, data management, descriptive statistics
• Analysing data: Exploratory statistics, inferential statistics, spatial data analysis, computer assisted qualitative data analysis (CAQDAS)
• Interpretation and communication: writing up results, interpreting outputs.

Learning Outcome

Knowledge:

• Comprehend data collection and analytical methods used in the scientific literature in environmental sciences
• develop a broad and integrated understanding of data analysis methods, their principles and appropriate application
• Select and apply appropriate methods to plan research, and use some basic methods to analyse data

Skills:

• Evaluate the strengths, limitations and weaknesses of each method
• gain practical experience and awareness of some principal methods and specialised techniques of data collection and analysis
• Combine methods to formulate research, planning and management questions, both within and across disciplinary boundaries
• Select appropriate methods and use these on real data

General competence:

• Use a broad spectrum of basic analytical methods that enable them to perform practical tasks in other courses in this programme, and to follow the advanced course 9: Scientific Writing, Theory and Data Analysis
• Use the knowledge gained from this introductory course to develop their skills in specialized research methods during the work with their master thesis
• Be able to recognise well-conducted research and write a research report following principles of sound scientific writing

Entry requirements

Completed bachelor degree of 180 ECTS.

Recommended previous knowledge

It is an advantage with basic knowledge in statistics and Geographic information systems (GIS).

Teaching methods

• Lectures
• Group discussion of scientific studies that apply various research methods
• Practice in designing research projects, collecting data and in using analytical methods (R, GIS, and interviews/ questionnaires)

Compulsory learning activities

1. Individually, students should achieve at least 60% correct answers on lecture and practical questions and exercises
2. In groups of 2 or 3, students complete 1-3 short writing assignments.

Assessment

A written assignment in which students provide 1) a critical assessment of a published paper (chosen by the assessors), demonstrating critical reading skills and knowledge of topics covered on the course, and 2) a proposal for an alternative project that answers the same research question, outlining how the proposed project improves upon the issues identified in part 1.

 

Grading

A-F

Examination support material

All resources are allowed

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