Mathematical Modelling for Sustainable Development, 6 credits
Matematisk modellering för hållbar utveckling , 6 hp
TAMS48
Main field of study
Mathematics Applied MathematicsCourse level
Second cycleCourse type
Programme courseExaminer
Martin SingullCourse coordinator
Andrew WintersDirector of studies or equivalent
Roghayeh HajizadehEducation components
Preliminary scheduled hours: 0 hRecommended self-study hours: 160 h
Available for exchange students
YesCourse offered for | Semester | Period | Timetable module | Language | Campus | ECV | |
---|---|---|---|---|---|---|---|
6CTMA | Engineering Mathematics, Master of Science in Engineering (Master Profile in Computational Mathematics and Analysis) | 9 (Autumn 2026) | 1 | 2 | Swedish/English | Linköping, Valla | C |
6CTMA | Engineering Mathematics, Master of Science in Engineering (Master Profile in Mathematical Statistics and Optimization) | 9 (Autumn 2026) | 1 | 2 | Swedish/English | Linköping, Valla | C |
6MMAT | Mathematics, Master's Programme | 3 (Autumn 2026) | 1 | 2 | Swedish/English | Linköping, Valla | C/E |
Main field of study
Mathematics, Applied MathematicsCourse level
Second cycleAdvancement level
A1NCourse offered for
- Master of Science in Engineering Mathematics
- Master's Programme in Mathematics
Prerequisites
The mandatory mathematics courses in the Engineering Mathematics programme.
Intended learning outcomes
Through various learning elements in the course, students gain a deeper insight into how mathematics is relevant to other subject areas and the important role mathematics plays in sustainable development. After completing the course, the student is expected to be able to:
- M1 (Modeling): Understand the need for different modeling methods in natural sciences and technology, with a focus on sustainable development. Account for different mathematical and statistical models and explain the different steps of the modeling process. Plan and select the appropriate method considering the purpose of the modeling. Define an appropriate mathematical or statistical model that takes into account the chosen modeling method. Master and explain some general tools for mathematical modeling and have an understanding of the role of mathematics and statistics for modeling in sustainable development.
- M2 (Analysis): Use the modeling process to solve problems in natural sciences and technology, both individually and in groups, with a particular focus on sustainable development.
- M3 (Implementation): Develop programs in Python or an equivalent programming language, both independently and in collaboration with others. Document and present the results, both orally and in writing, also to a non-specialist audience
Course content
The course Mathematical Modeling for Sustainable Development balances an exciting combination of advanced mathematical and statistical modeling and machine learning with a focus on sustainable development in the natural sciences, and especially climate modeling. The course aims to provide an understanding of the use, role and limitations of mathematics in modeling. The course places great emphasis on integrating research into the education, with the goal of deepening students' knowledge of both theoretical and practical aspects of mathematical modeling with applications.
The course covers examples of mathematical and statistical models with special emphasis on the different steps in the modeling process, including problem formulation, analysis, calculations, simulation and feedback.
With a focus on climate modeling, the fundamentals and rationale for transforming climate physics into a mathematical climate model are considered and discussed, where the language of computational physics and mathematics consists of ordinary and partial differential equations (ODEs and PDEs). The analysis is done at both continuous and discrete levels to provide a deeper understanding of how the solutions behave and how uncertainty in the data (through error terms) affects them. In modeling, the mathematical model needs to be discretized effectively to calculate an approximate solution for various uncertain parameters. The results then need to be interpreted, used in prediction and the conclusions should be presented in an appropriate way. The visualization of the results from a climate model requires mathematical knowledge of how to plot spherical data using post-processing tools.
The mathematical models involved are within several subject areas, such as computational mathematics, mathematical statistics, optimization theory and applied mathematics.
Teaching and working methods
The teaching consists of lectures, seminars and project work. Participation in project work and other integrated teaching is mandatory.
Examination
UPG1 | Home assignments | 2 credits | U, G |
PRA1 | Project work | 4 credits | U, G |
Grades
Two-grade scale, U, GDepartment
Matematiska institutionenCode | Name | Scope | Grading scale |
---|---|---|---|
UPG1 | Home assignments | 2 credits | U, G |
PRA1 | Project work | 4 credits | U, G |
Course syllabus
A syllabus must be established for each course. The syllabus specifies the aim and contents of the course, and the prior knowledge that a student must have in order to be able to benefit from the course.
Timetabling
Program courses are timetabled after a decision has been made for this course concerning its assignment to a timetable module. Single subject courses can be timetabled at other times.
Interruption in and deregistration from a course
The LiU decision, Guidelines concerning confirmation of participation in education, Dnr LiU-2020-02256 (https://styrdokument.liu.se/Regelsamling/VisaBeslut/764582), states that interruptions in study are to be recorded in Ladok. Thus, all students who do not participate in a course for which they have registered are therefore obliged to report the interruption so that this can be noted in Ladok. Deregistration from or interrupting a course is carried out using a Web-based form.
Cancelled courses and changes to the course syllabus
Courses with few participants (fewer than 10) may be cancelled or organised in a manner that differs from that stated in the course syllabus. The Dean is to deliberate and decide whether a course is to be cancelled or changed from the course syllabus. For single subject courses, the cancellation must be done before students are admitted to the course (in accordance with LiUs regulation Dnr LiU-2022-01200, https://styrdokument.liu.se/Regelsamling/VisaBeslut/622645).
Guidelines relating to examinations and examiners
For details, see Guidelines for education and examination for first-cycle and second-cycle education at Linköping University, Dnr LiU-2023-00379 (http://styrdokument.liu.se/Regelsamling/VisaBeslut/917592).
An examiner must be employed as a teacher at LiU according to the LiU Regulations for Appointments, Dnr LiU-2022-04445 (https://styrdokument.liu.se/Regelsamling/VisaBeslut/622784). For courses in second-cycle, the following teachers can be appointed as examiner: Professor (including Adjunct and Visiting Professor), Associate Professor (including Adjunct), Senior Lecturer (including Adjunct and Visiting Senior Lecturer), Research Fellow, or Postdoc. For courses in first-cycle, Assistant Lecturer (including Adjunct and Visiting Assistant Lecturer) can also be appointed as examiner in addition to those listed for second-cycle courses. In exceptional cases, a Part-time Lecturer can also be appointed as an examiner at both first- and second cycle, see Delegation of authority for the Board of Faculty of Science and Engineering.
Forms of examination
Principles for examination
Written and oral examinations and digital and computer-based examinations are held at least three times a year: once immediately after the end of the course, once in August, and once (usually) in one of the re-examination periods. Examinations held at other times are to follow a decision of the faculty programme board.
Principles for examination scheduling for courses that follow the study periods:
- courses given in VT1 are examined for the first time in March, with re-examination in June and August
- courses given in VT2 are examined for the first time in May, with re-examination in August and January
- courses given in HT1 are examined for the first time in October, with re-examination in January and August
- courses given in HT2 are examined for the first time in January, with re-examination in March and in August.
The examination schedule is based on the structure of timetable modules, but there may be deviations from this, mainly in the case of courses that are studied and examined for several programmes and in lower grades (i.e. 1 and 2).
Examinations for courses that the faculty programme board has decided are to be held in alternate years are held three times during the school year in which the course is given according to the principles stated above.
Examinations for courses that are cancelled or rescheduled such that they are not given in one or several years are held three times during the year that immediately follows the course, with examination scheduling that corresponds to the scheduling that was in force before the course was cancelled or rescheduled.
When a course, or a written or oral examination (TEN, DIT, DAT, MUN), is given for the last time, the regular examination and two re-examinations will be offered. Thereafter, examinations are phased out by offering three examinations during the following academic year at the same times as the examinations in any substitute course. The exception is courses given in the period HT1, where the three examination occasions are January, March and August. If there is no substitute course, three examinations will be offered during re-examination periods during the following academic year. Other examination times are decided by the faculty programme board. In all cases above, the examination is also offered one more time during the academic year after the following, unless the faculty programme board decides otherwise. In total, 6 re-examinations are offered, of which 2 are regular re-examinations. In the examination registration system, the examinations given for the penultimate time and the last time are denoted.
If a course is given during several periods of the year (for programmes, or on different occasions for different programmes) the faculty programme board or boards determine together the scheduling and frequency of re-examination occasions.
For single subject courses, written and oral examinations can be held at other times.
Retakes of other forms of examination
Regulations concerning retakes of other forms of examination than written examinations and digital and computer-based examinations are given in the LiU guidelines for examinations and examiners, Dnr LiU-2023-00379 (http://styrdokument.liu.se/Regelsamling/VisaBeslut/917592).
Course closure
For Decision on Routines for Administration of the Discontinuation of Educational Programs, Freestanding Courses and Courses in Programs, see Dnr LiU-2021-04782 (https://styrdokument.liu.se/Regelsamling/VisaBeslut/1156410). After a decision on closure and after the end of the discontinuation period, the students are referred to a replacement course (or similar) according to information in the course syllabus or programme syllabus. If a student has passed some part/parts of a closed program course but not all, and there is an at least partially replacing course, an assessment of crediting can be made. For questions about the crediting of course components, contact the Study councellors.
Registration for examination
In order to take an written, digital or computer-based examination, registration in advance is mandatory, see decision in the university’s rule book Dnr LiU-2020-04559 (https://styrdokument.liu.se/Regelsamling/VisaBeslut/622682). An unregistered student can thus not be offered a place. The registration is done at the Student Portal or in the LiU-app during the registration period. The registration period opens 30 days before the date of the examination and closes 10 days before the date of the examination. Candidates are informed of the location of the examination by email, four days in advance.
Code of conduct for students during examinations
Details are given in a decision in the university’s rule book, Dnr LiU-2020-04559 (http://styrdokument.liu.se/Regelsamling/VisaBeslut/622682).
Retakes for higher grade
Students at the Institute of Technology at LiU have the right to retake written examinations and digital and computer-based examinations in an attempt to achieve a higher grade. This is valid for all examination components with code “TEN”, “DIT” and "DAT". The same right may not be exercised for other examination components, unless otherwise specified in the course syllabus.
A retake is not possible on courses that are included in an issued degree diploma.
Grades
The grades that are preferably to be used are Fail (U), Pass (3), Pass not without distinction (4) and Pass with distinction (5).
- Grades U, 3, 4, 5 are to be awarded for courses that have written or digital examinations.
- Grades Fail (U) and Pass (G) may be awarded for courses with a large degree of practical components such as laboratory work, project work and group work.
- Grades Fail (U) and Pass (G) are to be used for degree projects and other independent work.
Examination components
The following examination components and associated module codes are used at the Faculty of Science and Engineering:
- Grades U, 3, 4, 5 are to be awarded for written examinations (TEN) and digital examinations (DIT).
- Examination components for which the grades Fail (U) and Pass (G) may be awarded are laboratory work (LAB), project work (PRA), preparatory written examination (KTR), digital preparatory written examination (DIK), oral examination (MUN), computer-based examination in a computer lab (DAT), digital preparatory written examination in a computer lab (DAK), home assignment (HEM), and assignment (UPG).
- Students receive grades either Fail (U) or Pass (G) for other examination components in which the examination criteria are satisfied principally through active attendance such as tutorial group (BAS) or examination item (MOM).
- Grades Fail (U) and Pass (G) are to be used for the examination components Opposition (OPPO) and Attendance at thesis presentation (AUSK) (i.e. part of the degree project).
In general, the following applies:
- Mandatory course components must be scored and given a module code.
- Examination components that are not scored, cannot be mandatory. Hence, it is voluntary to participate in these examinations, and the voluntariness must be clearly stated. Additionally, if there are any associated conditions to the examination component, these must be clearly stated as well.
- For courses with more than one examination component with grades U,3,4,5, it shall be clearly stated how the final grade is weighted.
For mandatory components, the following applies (in accordance with the LiU Guidelines for education and examination for first-cycle and second-cycle education at Linköping University, Dnr LiU-2023-00379 http://styrdokument.liu.se/Regelsamling/VisaBeslut/917592):
- If special circumstances prevail, and if it is possible with consideration of the nature of the compulsory component, the examiner may decide to replace the compulsory component with another equivalent component.
For possibilities to alternative forms of examinations, the following applies (in accordance with the LiU Guidelines for education and examination for first-cycle and second-cycle education at Linköping University, Dnr LiU-2023-00379 http://styrdokument.liu.se/Regelsamling/VisaBeslut/917592):
- If the LiU coordinator for students with disabilities has granted a student the right to an adapted examination for a written examination in an examination hall, the student has the right to it.
- If the coordinator has recommended for the student an adapted examination or alternative form of examination, the examiner may grant this if the examiner assesses that it is possible, based on consideration of the course objectives.
- An examiner may also decide that an adapted examination or alternative form of examination if the examiner assessed that special circumstances prevail, and the examiner assesses that it is possible while maintaing the objectives of the course.
Reporting of examination results
The examination results for a student are reported at the relevant department.
Plagiarism
For examinations that involve the writing of reports, in cases in which it can be assumed that the student has had access to other sources (such as during project work, writing essays, etc.), the material submitted must be prepared in accordance with principles for acceptable practice when referring to sources (references or quotations for which the source is specified) when the text, images, ideas, data, etc. of other people are used. It is also to be made clear whether the author has reused his or her own text, images, ideas, data, etc. from previous examinations, such as degree projects, project reports, etc. (this is sometimes known as “self-plagiarism”).
A failure to specify such sources may be regarded as attempted deception during examination.
Attempts to cheat
In the event of a suspected attempt by a student to cheat during an examination, or when study performance is to be assessed as specified in Chapter 10 of the Higher Education Ordinance, the examiner is to report this to the disciplinary board of the university. Possible consequences for the student are suspension from study and a formal warning. More information is available at Cheating, deception and plagiarism.
Linköping University has also produced a guide for teachers and students' use of generative AI in education (Dnr LiU-2023-02660). As a student, you are always expected to gain knowledge of what applies to each course (including the degree project). In general, clarity to where and how generative AI has been used is important.
Regulations (apply to LiU in its entirety)
The university is a government agency whose operations are regulated by legislation and ordinances, which include the Higher Education Act and the Higher Education Ordinance. In addition to legislation and ordinances, operations are subject to several policy documents. The Linköping University rule book collects currently valid decisions of a regulatory nature taken by the university board, the vice-chancellor and faculty/department boards.
LiU’s rule book for education at first-cycle and second-cycle levels is available at https://styrdokument.liu.se/Regelsamling/Innehall.
Note: The course matrix might contain more information in Swedish.
I | U | A | Modules | Comment | ||
---|---|---|---|---|---|---|
1. DISCIPLINARY KNOWLEDGE AND REASONING | ||||||
1.1 Knowledge of underlying mathematics and science (courses on G1X-level) |
|
|
X
|
UPG1
PRA1
|
Basic knowledge in mathematics |
|
1.2 Fundamental engineering knowledge (courses on G1X-level) |
|
|
X
|
UPG1
PRA1
|
Basic skills in programming |
|
1.3 Further knowledge, methods and tools in any of : mathematics, natural sciences, engineering (courses at G2X level) |
|
|
X
|
UPG1
PRA1
|
Advanced knowledge in mathematics is needed in both projects and assignments, as well as advanced knowledge in programming and/or other technical or scientific subjects. |
|
1.4 Advanced knowledge, methods and tools in any of: mathematics, natural sciences, engineering (courses at A1X level) |
|
X
|
X
|
PRA1
|
Reading in line with the the project |
|
1.5 Insight into current research and development work |
|
X
|
X
|
PRA1
|
Projects in mathematical modeling for sustainable development |
|
2. PERSONAL AND PROFESSIONAL SKILLS AND ATTRIBUTES | ||||||
2.1 Analytical reasoning and problem solving |
|
X
|
X
|
UPG1
PRA1
|
Formulate problem statement, mathematical modeling, programming |
|
2.2 Experimentation, investigation, and knowledge discovery |
|
X
|
X
|
PRA1
|
Analysis and assessment of the plausibility of results |
|
2.3 System thinking |
|
X
|
X
|
PRA1
|
Project work |
|
2.4 Attitudes, thought, and learning |
|
X
|
X
|
Project work |
||
2.5 Ethics, equity, and other responsibilities |
|
X
|
X
|
Project work |
||
3. INTERPERSONAL SKILLS: TEAMWORK AND COMMUNICATION | ||||||
3.1 Teamwork |
|
X
|
X
|
Project work |
||
3.2 Communications |
|
X
|
X
|
PRA1
|
Results are presented orally and written. |
|
3.3 Communication in foreign languages |
|
|
X
|
PRA1
|
Final presentation of the project |
|
4. CONCEIVING, DESIGNING, IMPLEMENTING AND OPERATING SYSTEMS IN THE ENTERPRISE, SOCIETAL AND ENVIRONMENTAL CONTEXT | ||||||
4.1 Societal conditions, including economically, socially and ecologically sustainable development |
X
|
X
|
X
|
PRA1
|
The role and responsibility of the engineer |
|
4.2 Enterprise and business context |
|
|
|
|||
4.3 Conceiving, system engineering and management |
|
|
|
|||
4.4 Designing |
|
X
|
X
|
PRA1
|
Implementation of the project |
|
4.5 Implementing |
|
X
|
X
|
PRA1
|
Implementation and demonstration of the project |
|
4.6 Operating |
|
|
|
|||
5. PLANNING, EXECUTION AND PRESENTATION OF RESEARCH DEVELOPMENT PROJECTS WITH RESPECT TO SCIENTIFIC AND SOCIETAL NEEDS AND REQUIREMENTS | ||||||
5.1 Societal conditions, including economically, socially and ecologically sustainable development within research or development projects |
X
|
X
|
X
|
UPG1
PRA1
|
The role and responsibility of researcher and professional |
|
5.2 Economic conditions for research or development projects |
|
|
|
|||
5.3 Identification of needs, structuring and planning of research or development projects |
X
|
X
|
X
|
PRA1
|
Implementation of the project |
|
5.4 Execution of research or development projects |
X
|
X
|
X
|
PRA1
|
Implementation of the project |
|
5.5 Presentation and evaluation of research or development projects |
|
X
|
X
|
PRA1
|
Implementation and presentation of the project |
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