PARA2200 Prehospital Trauma Care Course description

Knowledge of injury mechanisms and the scope of injuries is vital for a paramedic to be able to make good professional assessments and choices relating to the prioritisation, treatment and transport needs of injured patients. The course is based on recommendations made by surgical and anaesthesiologist expert communities on emergency injury treatment.

This course covers qualitative and quantitative research methods that are essential to the UD of ICT Master's programme and ethical perspectives in UD research.

Admission requirements.

A student who has completed this course should have the following learning outcomes defined in terms of knowledge, skills and general competence:

Knowledge

On successful completion of this course the student:

• has thorough knowledge of qualitative methods
• has thorough knowledge of quantitative methods
• has thorough knowledge of the requirements and standards for registration, processing, and storage of information about participants in UD research

Skills

On successful completion of this course the student:

• can formulate research questions
• can design qualitative studies and set up qualitative experiments
• can use fieldwork strategies
• can use qualitative analysis and interpret data (with and without software tools)
• can evaluate strategies to enhance qualitative studies (e.g., using triangulation)
• can analyse the researcher's own role, influence and bias in a qualitative data collection
• can plan and carry out statistical tests

General competence

On successful completion of this course the student:

• can analyse ethical issues related to privacy and anonymity for participants in studies
• can handle personal data within the limits of privacy law and ethical standards
• can evaluate and select the research design, method, and analysis tools appropriate to the proposed research question/s
• can apply knowledge and skills learned on qualitative and quantitative methods on new problems and answer open questions

The course consists of lectures, workshops, and/or tutorials and potentially inclusion of online learning resources. Guidance and feedback are provided by the lecturer(s).

One project report (5000-6000 words) in pairs, with a project log book as attachment to the report.

Use of Examiners

Two internal examiners will assess the report with attached log book. External examiner is used periodically.

Assessment grades

A grading scale of A (highest) to F (lowest) where A to E is a pass grade and F is a fail grade.

Syllabus

Compulsory literature

(approx.. 800 pages in total)

Cairns, P., Cox, A. L., Research Methods for Human-Computer Interaction, Cambridge University Press, pp. 1-87, pp. 112-157, 2008.

Everitt, B. S., Torsten Hothorn, A Handbook of Statistical Analyses Using R, Chapman & Hall/CRC, pp. 55-72, pp. 215-226, pp. 243-258, 2006.

Lazar, J., Feng, J. H., Hochheiser, H., Research Methods in Human-Computer Interaction, Wiley, pp. 217-248, pp. 281-303, 2010.

Walpole, R. E., Myers, R. H., Myers, S. L., Ye, K., Probability & Statistics for Engineers & Scientists, 8th Edition, Prentice Hall, pp. 1-30, pp. 321-444, pp. 511-610, 2007.

Selected articles from relevant academic books, journals and conference proceedings will be informed about during the course.

None.

Grade scale A-F

All papers are assessed by two examiners. A minimum of twenty per cent of the exam papers will be assessed by an external examiner. The external examiner's assessment shall benefit all the students.