°ÄÃÅÁùºÏ²Ê¿ª½±¼Ç¼
MTMCW: Causality and Decision-Making
Module code: MTMCW
Module provider: Meteorology; School of Mathematical, Physical and Computational Sciences
Credits: 20
Level: Postgraduate Masters
When you'll be taught: Semester 2
Module convenor: Professor Rosalind Cornforth, email: r.j.cornforth@reading.ac.uk
Module co-convenor: Dr Celia Petty, email: e.c.petty@reading.ac.uk
Pre-requisite module(s):
Co-requisite module(s): IN THE SAME YEAR AS TAKING THIS MODULE YOU MUST TAKE MTMDCS (Compulsory)
Pre-requisite or Co-requisite module(s):
Module(s) excluded:
Placement information: NA
Academic year: 2024/5
Available to visiting students: Yes
Talis reading list: Yes
Last updated: 29 August 2024
Overview
Module aims and purpose
In this module, students will be introduced to the design and application of decision-making methods and problem-structuring based on causal inference theory. Socio-economic and aspects of climate risk and impacts will be considered through a range of real-world case studies and scenarios.Â
The aim of this module is to help students to develop and apply critical reasoning skills to practical decision-making situations regarding climate change impacts and adaptation. This will be achieved by learning how to use causal inference methods as a modelling framework for decision-making; with exploration of ethics, values and competing ideologies in the context of national and international policies and institutions.Â
The knowledge gained will be of practical relevance for supporting government agencies, organizations and communities to adapt to climate change and design decision-relevant climate services.Â
Module learning outcomes
By the end of the module, it is expected that students will be able to:
- Describe the main aspects of climate risk and decision-making in the context of climate adaptation
- Describe and apply the main modelling tools of causal inference
- Critically analyse reports of climate risk and draw correct inferences on potential impacts across a population with differentiated vulnerability
- Recognise the role political economy and ecology plays in the context of national and international policies and institutions, including the IPCC negotiations
Module content
- Climate change risk assessments and adaptation – the need for causal, explanatory models Â
- Statistics refresher for causal inference – probability and multiple linear regressionÂ
- Causal Inference (CI) – overview and fundamental conceptsÂ
- Causal Networks – buildng a network and estimating causal effects; the role of expert knowledgeÂ
- Modelling risk and supporting decision-making with causal networksÂ
- CI and machine learning – causal discovery Â
These will be paired over the 12 weeks with invited lectures, seminars and discusssions on areas such as:Â
- Power dynamics and the political ecology of climate changeÂ
- Equity and inclusiveness in climate change negotiationsÂ
- Climate justice - contemporary and historical debatesÂ
- Climate chnage and AI: opportunities, challenges and dangersÂ
- International environmental law, the UNFCCC, and mainstream institutional responses to climate changeÂ
- 'Greenwashing', business and climate changeÂ
Structure
Teaching and learning methods
Lectures, seminars, computer-based practicals, case study-based practical's and guided independent study. Practical sessions are designed to illustrate the concepts presented in the lectures and give students hands-on experience with their implementation through real-world case studies and shared discussion.Â
Study hours
At least 60 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.
 Scheduled teaching and learning activities |  Semester 1 |  Semester 2 | Ìý³§³Ü³¾³¾±ð°ù |
---|---|---|---|
Lectures | 22 | ||
Seminars | 22 | ||
Tutorials | |||
Project Supervision | |||
Demonstrations | |||
Practical classes and workshops | 16 | ||
Supervised time in studio / workshop | |||
Scheduled revision sessions | |||
Feedback meetings with staff | |||
Fieldwork | |||
External visits | |||
Work-based learning | |||
 Self-scheduled teaching and learning activities |  Semester 1 |  Semester 2 | Ìý³§³Ü³¾³¾±ð°ù |
---|---|---|---|
Directed viewing of video materials/screencasts | |||
Participation in discussion boards/other discussions | |||
Feedback meetings with staff | |||
Other | |||
Other (details) | |||
 Placement and study abroad |  Semester 1 |  Semester 2 | Ìý³§³Ü³¾³¾±ð°ù |
---|---|---|---|
Placement | |||
Study abroad | |||
 Independent study hours |  Semester 1 |  Semester 2 | Ìý³§³Ü³¾³¾±ð°ù |
---|---|---|---|
Independent study hours | 140 |
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
Type of assessment | Detail of assessment | % contribution towards module mark | Size of assessment | Submission date | Additional information |
---|---|---|---|---|---|
Set exercise | Creating sphere of influence diagram to locate AI in a CC space | 20 | 2-3 pages | Semester 2, Teaching Week 5 | |
Set exercise | Using SD to create a causal loop diagram incorporating the effects of AI on CC and Justice | 20 | 2-3 pages | Semester 2, Teaching Week 9 | |
Set exercise | Causal Inference for Decision-making coursework | 60 | 4-6 pages | Semester 2, Teaching Week 12 | Submission date, for clarity, this is when the assessment would be due. |
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.
Short interactive exercises/quizzes in each lecture, plus informal feedback in each practical session.Â
Reassessment
Type of reassessment | Detail of reassessment | % contribution towards module mark | Size of reassessment | Submission date | Additional information |
---|---|---|---|---|---|
Written coursework assignment | Climate change, AI and justice assignment | 40 | 3,000 words | During the University resit period | |
Set exercise | Causal inference for decision-making coursework | 60 | 3-5 pages | During the University resit period |
Additional costs
Item | Additional information | Cost |
---|---|---|
Computers and devices with a particular specification | ||
Required textbooks | ||
Specialist equipment or materials | ||
Specialist clothing, footwear, or headgear | ||
Printing and binding | ||
Travel, accommodation, and subsistence |
THE INFORMATION CONTAINED IN THIS MODULE DESCRIPTION DOES NOT FORM ANY PART OF A STUDENT'S CONTRACT.