ADTS3100 Universal Design Course description

This course, together with Mathematics 1000, will give students an understanding of mathematical concepts, issues and solution methods with the focus on applications. The course will also give students an understanding of concepts in statistics and probability theory, problems and solution methods with the focus on applications in their own field and in the engineering field in general. ;

Grade scale A-F.

No requirements over and above the admission requirements.

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

The student is capable of:

• planning the development of useful and user-friendly systems, including system descriptions, product development, testing/evaluation and user participation
• fresh and creative thinking relating to the development of universal ICT systems
• giving an account of the contents of national and international legislation and recommended guidelines for the universal design of ICT

Skills

The student is capable of:

• evaluating the usefulness of user interfaces, websites and web applications
• creating user-friendly, universally designed ICT solutions
• creating universally designed documents

General competence

The student:

• understands the difference between universal design and assistive technology, and is capable of disseminating knowledge about universal design
• understands that people are different, and that diversity must be taken into account in the planning and development of information and communication technology
• is capable of identifying barriers that different people can encounter in connection with ICT systems and of finding solutions to such challenges

After completing the course, the student is expected to have achieved the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge The student is capable of:

• using linear algebra to determine eigenvalues and solving systems of differential equations and solving second order linear differential equations with constant coefficients;
• discussing functions of multiple variables and apply partial derivatives to various problems
• explaining convergence and power series representations of functions
• explaining key concepts in set theory, probability theory, parameter estimation, hypothesis testing and choice of model
• explaining normal, binomial, Poisson and exponential probability distributions, as well as typical problems to which they can be applied

Skills

The student is capable of:

• calculating eigenvectors and diagonalising matrices
• applying diagonalisation of matrices to solve systems of differential equations
• determining the convergence of series using the ratio test, and finding the Taylor series of known functions
• describing and discussing functions of multiple variables using e.g. level curves and partial derivatives
• determining and classifying critical points of functions of two variables
• applying statistical principles and concepts from their own field
• basic calculus of probability with discrete and continuous probability distributions and parameter estimation
• calculating confidence intervals and testing hypotheses
• applying mathematical tools to matrices and functions of two variables

General competence

The student is capable of:

• identifying the connection between mathematics and their own field of engineering
• transferring a practical problem from their own field into mathematical form, so it can be solved analytically or numerically
• using mathematical methods and tools that are relevant to the field
• using statistical ways of thinking to solve problems in engineering and communicating them orally and in writing
• solving problems in engineering by use of probability calculations, statistical planning of trials, data collection and analysis

The course is taught through joint lectures and exercises. In the exercise sessions, the students work on assignments, both individually and in groups, under the supervision of a lecturer.

Portfolio assessment subject to the following requirements:

• one individual assignment.
• one project assignment in groups (usually 3-5 students)

Total folder size as described in the assignment.

The exam result can be appealed.

In the event of resit and rescheduled exams, another exam form may also be used or a new assignment given with a new deadline. If oral exams are used, the result cannot be appealed.

None.

Individual written exam, 3 hours.

The exam result can be appealed.

Aids enclosed with the exam question paper, and a handheld calculator that cannot be used for wireless communication or to perform symbolic calculations. If the calculator’s internal memory can store data, the memory must be deleted before the exam. Random checks may be carried out.