°ÄÃÅÁùºÏ²Ê¿ª½±¼Ç¼

Internal

MTMCW: Causality and Decision-Making

°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. 

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. 

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. 

Module learning outcomes

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

  1. Describe the main aspects of climate risk and decision-making in the context of climate adaptation
  2. Describe and apply the main modelling tools of causal inference
  3. Critically analyse reports of climate risk and draw correct inferences on potential impacts across a population with differentiated vulnerability
  4. 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  
  • Statistics refresher for causal inference – probability and multiple linear regression 
  • Causal Inference (CI) – overview and fundamental concepts 
  • Causal Networks – buildng a network and estimating causal effects; the role of expert knowledge 
  • Modelling risk and supporting decision-making with causal networks 
  • CI and machine learning – causal discovery  

These will be paired over the 12 weeks with invited lectures, seminars and discusssions on areas such as: 

  • Power dynamics and the political ecology of climate change 
  • Equity and inclusiveness in climate change negotiations 
  • Climate justice - contemporary and historical debates 
  • Climate chnage and AI: opportunities, challenges and dangers 
  • International environmental law, the UNFCCC, and mainstream institutional responses to climate change 
  • 'Greenwashing', business and climate change 

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. 

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

Please note that the hours listed above are for guidance purposes only.

 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. 

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.

Things to do now