Courses in linear analysis will be brought under one thematic module
A new project launched at the university focuses on the teaching of matrix and linear algebra as a single entity and produces content that is suitable for the needs of different academic subjects as extensively as possible.
“Despite having a common goal, teaching of the basics of linear algebra is scattered into several courses, which is not optimal from the point of view of students or learning,” University Lecturer Janne Gröhn from the Department of Physics and Mathematics says.
In response, the linear analysis project will implement a reform in which the whole will be viewed from a broader perspective than a single subject.
This will clarify the study of linear algebra courses, enhance university teaching and create an interesting thematic module for the market of continuous learning. Parts of the thematic module can be flexibly tailored to students of mathematics, to people involved in applied mathematics, and to professionals working with mathematical computing.
“The aim is to create a thematic module that flexibly supports different student groups who have different desired learning outcomes,” Gröhn says.
“The creation of a multidisciplinary thematic module in linear analysis is a very important project. Linear algebra plays a key role in almost every aspect of mathematics from analysis to geometry, and even to number theory. In natural sciences and technology, a concrete example of where linear algebra is needed is the modelling of natural phenomena,” Professor Risto Korhonen adds.
“The new project focuses on the university’s teaching of matrix and linear algebra as a single entity and produces content that is as suitable for the needs of different academic subjects as extensively as possible,” say University Lecturer Anna Kaasinen and University Lecturer Päivi Ronkanen from the Department of Applied Physics.
For students of applied physics, mathematics is an important minor.
Anna Kaasinen and Päivi Ronkanen
University Lecturers, Department of Applied Physics
Linear algebra is the basis for many modern methods of data science, artificial intelligence and machine learning.
Professor of Data Science, School of Computing