ADMRES: Research Skills in Agriculture, Ecology and Environment

Module code: ADMRES

Module provider: School of Agriculture, Policy and Development

Credits: 20

Level: Postgraduate Masters

When you'll be taught: Semester 1

Module convenor: Dr Jake Bishop, email: j.bishop@reading.ac.uk

Pre-requisite module(s):

Co-requisite module(s): IN THE SAME YEAR AS TAKING THIS MODULE YOU MUST TAKE ADMREP (Compulsory)

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2024/5

Available to visiting students: No

Talis reading list: No

Last updated: 20 May 2024

Overview

Module aims and purpose

Develop essential knowledge and skills for research in agriculture, ecology and the environment. This module prepares you to design and conduct your independent Masters level extended research project. Acquire and apply knowledge in experimental design and statistics and develop skills in field study methods and use of R statistical software for data manipulation and analysis. Visit a variety of research organisations on a series of field visits, during which you will explore the different types of research methods and approaches used in the sector. 

Module learning outcomes

By the end of the module, it is expected that students will be able to:

1. Identify a question and form a testable hypothesis
2. Design an appropriate experiment incorporating relevant research methods and statistical analyses in R statistical software
3. Appraise and contrast different research methods and approaches in agriculture, ecology, the environment

Module content

The module will use a range of teaching approaches including lectures, seminars, practical sessions, and field visits to research organisations to equip students with the essential skills for an independent Masters-level extended research project.

You will learn about the fundamentals of experimental and observational study design and the key statistical concepts and analyses of relevance to agriculture, ecology and the environment. You will apply this knowledge and develop programming, data manipulation and statistical analysis skills through a series of computer-lab sessions using R statistical software.

Through practical sessions and visits to a diverse range of external research organisations, you will develop a broad understanding of the research methods and approaches in the sector. This includes controlled environment and field crops research methods, survey methods and species identification. The field visits also offer an opportunity to gain insights into possible future career paths.

Structure

Teaching and learning methods

The module includes a series of lectures, field based practical classes at the university’s Sonning Farm, field visits and computer lab classes.

Study hours

At least 40 hours of scheduled teaching and learning activities will be delivered in person, with the remaining hours for scheduled and self-scheduled teaching and learning activities delivered either in person or online. You will receive further details about how these hours will be delivered before the start of the module.

Please note the independent study hours above are notional numbers of hours; each student will approach studying in different ways. We would advise you to reflect on your learning and the number of hours you are allocating to these tasks.

Semester 1 The hours in this column may include hours during the Christmas holiday period.

Semester 2 The hours in this column may include hours during the Easter holiday period.

Summer The hours in this column will take place during the summer holidays and may be at the start and/or end of the module.

Assessment

Requirements for a pass

Students need to achieve an overall module mark of 50% to pass this module.

Summative assessment

Penalties for late submission of summative assessment

The Support Centres will apply the following penalties for work submitted late:

Assessments with numerical marks

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of three working days;
• the mark awarded due to the imposition of the penalty shall not fall below the threshold pass mark, namely 40% in the case of modules at Levels 4-6 (i.e. undergraduate modules for Parts 1-3) and 50% in the case of Level 7 modules offered as part of an Integrated Masters or taught postgraduate degree programme;
• where the piece of work is awarded a mark below the threshold pass mark prior to any penalty being imposed, and is submitted up to three working days after the original deadline (or any formally agreed extension to the deadline), no penalty shall be imposed;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

Assessments marked Pass/Fail

• where the piece of work is submitted within three working days of the deadline (or any formally agreed extension of the deadline): no penalty will be applied;
• where the piece of work is submitted more than three working days after the original deadline (or any formally agreed extension of the deadline): a grade of Fail will be awarded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/qap/penaltiesforlatesubmission.pdf

You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Formative assessment

Formative assessment is any task or activity which creates feedback (or feedforward) for you about your learning, but which does not contribute towards your overall module mark.

Formative tests during the R software course

Reassessment

Additional costs