Teaching Responsibility
LJMU Schools involved in Delivery:
Biological and Environmental Sciences
Learning Methods
Lecture
Online
Workshop
Module Offerings
7107NATSCI-JAN-CTY
Aims
The aim of this module is to provide extensive training in generic research knowledge and statistical techniques for the Natural Sciences as part of the preparation for the MSc dissertation.
Learning Outcomes
1.
Design a research grant proposal around a research question: logistics, funding, timetabling, ethics, background.
2.
Identify and discuss the impact of their study – both academically and non-academically.
3.
Determine appropriate analytical methods for their project, including data collection.
4.
Present ideas in written format suitable for scientific communications by placing the research project into the broader context of the field, including logistics, dissemination and budget.
Module Content
Outline Syllabus:1) The scientific method: Inquiry, parsimony. Observation, problem, hypothesis, methods, results, conclusion, communication.
2) Project logistics. Sample, funding, remaining flexible, timeline, ethics,
3) Ethics, data protection and intellectual property. Managing research data.
4) Library Databases research, Endnote.
5) Presenting posters and presentations – the good and the bad. Publishing – where? Impact factor, quartiles, citation index, R index. Where should I present and why? Authorship order and acknowledgements. How to prepare a manuscript.
6) Communicating your work outside academia: Creating website, blog, podcast. Use of social media. Use of media.
7) Developing a research question. Developing ideas. Open and close ended questions. Bias. Read articles and narrow it down. Brainstorming. Feasibility.
8) Grant applications (assessment). Includes: measuring impact.
9) CV writing, applying for jobs. Making yourself employable.
10) Statistics. What is data. Statistical analyses and manipulating data in SPSS. Intro to other packages (R, etc.)
Module Overview:
This module provides extensive training in generic research knowledge and statistical techniques for the Natural Sciences. It aims to:
This module provides extensive training in generic research knowledge and statistical techniques for the Natural Sciences. It aims to:
- provide you with a broad appreciation of research methods and methodology including an understanding of the uses and limitations of different research methods
- teach you how to design and execute a research project keeping in mind feasibility, ethics, data protection, and project logistics and funding
Additional Information:The aim of this module is to provide extensive training in generic research knowledge and statistical techniques for the Natural Sciences. It will provide the student with a broad appreciation of research methods and methodology including an understanding of the uses and limitations of different research methods. It will teach the students how to design and execute a research project keeping in mind feasibility, ethics, data protection, and project logistics and funding. In addition, attention will be given to dissemination to both academic and non-academic audiences: from writing academic manuscripts to creating blogs and speaking to the media. Univariate and multivariate statistics will be taught by lectures and online exercises, and students will be introduced to statistical software packages such as SPSS and R.