1 / 27

Mathematics and Engineering Education - reflections from an electrical engineer

Mathematics and Engineering Education - reflections from an electrical engineer. Lars Lundheim Department of Eelectronic Systems NTNU. Engineering = Applied Physics?. Applied Chemsitry. Mathematician. Mathematician. Engineer. Engineer. Physicist. Physicist. Physical reality. Idea.

riverav
Download Presentation

Mathematics and Engineering Education - reflections from an electrical engineer

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Mathematics and Engineering Education- reflections from an electrical engineer Lars Lundheim Department of Eelectronic Systems NTNU

  2. Engineering = Applied Physics?

  3. Applied Chemsitry

  4. Mathematician Mathematician Engineer Engineer Physicist Physicist

  5. Physical reality Idea

  6. Models • Natural Sciences: Descripitve • Engineering: Prescriptive

  7. Steinauge

  8. Prescriptive model

  9. Silicon in nature

  10. As prescribed Si

  11. Transistor

  12. Prescribed (what we want) What we get

  13. Circuit design

  14. Circuit design

  15. Generalization Practical restrictions

  16. Digital electronics

  17. 1 000 000 000 transistors

  18. Computers as components

  19. Digital signal processing Virtually no restrictions

  20. Challenges and opportunities • The set of realizable prescriptive models has increased and is still increasing. ⇒ More math becomes relevant • The complexity of realized systems has increased and is still increasing. ⇒ More math becomes necessary. • Technology moving away from physics (nature) ⇒ Still Common math curriculum for physics and engineering?

  21. Shift of emphasis? • Basic calculus • Ordinary differential equations • Partial differential equations • Transforms • Linear algebra • Functional analysis • Numerical mathematics • Optimization theory • Statistics and probability theory

  22. Diversity of need • Differentiation of syllabus according to study program? • Differentiation of approach/learning style

  23. When to learn what • Four courses during three first semesters? • Coordination with user courses?

  24. Division of labour • How do we best collaborate to give relevant and motivating education?

More Related