Course syllabus

Course-PM

DAT026 / DIT993 / LGMA65 Mathematical modelling and problem solving lp1 HT22 (7.5 hp)

This course is offered by the department of Computer Science and Engineering.

Useful Links

Instructions for the Course:

• General Instructions
• Lecture Slides and Problem Modules
• Supervision sessions
• Submission Instructions
• Reflection and self-assessment
• A note on the purpose and pedagogy of the course
• Writing Hints
• Complementary literature

External Links

• Slack (to join: see Our Slack Workspace)
• FIRE
• Zoom (Password: ProbSolve)
• Schedule on TimeEdit

Contact details:

• Examiner and Course Responsible: Robin Adams
  
• Guest lecturer: Dag Wedelin
• Supervisors:
  • Santiago Arellano
  • Sólrún Halla Einarsdóttir
  • Oskar Eriksson
  • Alexander Gower
  • Prabhat Kumar Jha
  • Tobias Karlsson
  • Anton Matsson
  • David Wärn
• Student representatives:
  • Martin Engström (TKDAT)
  • Elvina Fahlgren (TKITE)
  • Marianne Garabetian (TKDAT)
  • Reshad Qurishi (TKITE)
  • Omar Sulaiman (TKITE)
  • Josefin Kokkinakis (DIT993)
  • Jonathan Engstad (LGMA65)

Course purpose

Mathematical models are used in science and engineering to describe and represent different objects and systems, to analyze, understand and predict, and for finding the best design or strategy. Mathematical modelling is therefore a basic skill in data science. It is also central to software engineering, since forming a mathematical model of the domain is a critical step in software design. It is also important for pure mathematics and mathematics education, since most ideas in mathematics were created for the purpose of modelling some application.

With carefully selected exercises this course teaches mathematical modelling as a tool for solving real problems. Problems are taken from many different areas of knowledge: including computing, engineering, economics, medicine and games.

The course is primarily intended as an introduction to mathematical modelling for students with relatively limited experience in the use of mathematics, but who may come to work in different areas where mathematics is useful. With application-oriented exercises, and by teaching modelling and problem solving, the course then bridges the gap between the theoretical courses in mathematics and relevant applications.

Schedule

The weekly schedule for this course will be:

Monday 10.00-11.45 (Week One only: 15.15-17.00) Introductory lecture to this week's module

Tuesday 15.15-17.00 Supervision session

Wednesday 10.00-11.45 Supervision session

Wednesday 15.15-17.00 Follow-up lecture to last week's module

Friday 10.00-11.45 Supervision session

Friday 13.15-15.00 Supervision session

The only session with compulsory attendance (in person or by Zoom) is the Wednesday follow-up lecture (not compulsory in week 1).

All lectures will be streamed by Zoom and recorded.

For the introductory lectures, the recordings will be made available here. The recordings for the follow-up lectures will be made available only to individual students who cannot attend on Wednesdays for any reason.

See also the schedule on TimeEdit.

Course design

The core of the course is a number of problems in seven weekly modules. The normal schedule of a module is the following:

• Introductory lecture (Monday). A general introduction to the the type of models considered in the module and preparation for the problems.
• Problem solving work during the week. The students work together on the problems in groups of three. There are several supervision sessions when the students can discuss their ideas with the supervisors. We give advice interactively and incrementally, so you are encouraged to come back and discuss the same exercise several times. You will then get more help every time.
• The problems are completed and handed in on Sunday.
• Follow-up lecture the following week (Wednesday). This is a compulsory follow up lecture providing feedback on the problems and additional comments.
• After the follow-up lecture, you are finally asked to reflect on your problem solving and your learning in a second submission.

Course literature

There is no textbook or compulsory literature for the course. A number of suggestions for students who want further reading about mathematical modelling or problem solving are on the page Complementary literature

Learning objectives and syllabus

Learning objectives:

• Describe different model types and their properties, as well as the processes of modelling and problem solving. Describe main aspects of mathematical thinking.
• Explain the role of mathematics in different areas of application.
• Mathematical modelling: investigate real problems, suitably translate into a mathematical model and draw conclusions with the help of the model. This includes to create a precise formulation, simplify, make suitable assumptions and selecting how the problem can be described e.g. with the help of equations or in other mathematical ways.
• Mathematical problem solving: solving complex and unknown problems with an investigative and structured approach. This includes analyzing and understanding, working in smaller steps and trying things out.
• Communicate with and about mathematics.
• Use different computational tools as a natural part of working mathematically.
• Show an ability to balance own thinking and using knowledge from others.
• Show a reflective attitude to the contents of the course and to the student's own thinking.
• Show accuracy and quality in all work. 

Link to the syllabus on Studieportalen:

DAT026 (Chalmers)

DIT993 (GU)

LGMA65 (GU)

Examination form

The course is examined through written assignments and a final report, where the students are encouraged to summarize the course in their own way. Additionally, the course includes compulsory follow-up lectures for each modules, and during the examination week there is also compulsory final meeting where the report is discussed. Both the weekly assignments and the final report are normally done in groups of three.