| Dozent/in |
Dr. rer. nat. Hanna Bettine Fechner; Dr. rer. soc. Brigitte Hofstetter Furrer |
| Veranstaltungsart |
Vorlesung |
| Code |
HS221074 |
| Semester |
Herbstsemester 2022 |
| Durchführender Fachbereich |
Gesundheitswissenschaften |
| Studienstufe |
Master |
| Termin/e |
Mi, 05.10.2022, 08:15 - 12:00 Uhr, 3.B58
Mi, 12.10.2022, 08:15 - 12:00 Uhr, 3.B58
Mi, 19.10.2022, 08:15 - 12:00 Uhr, 3.B58
Mi, 26.10.2022, 08:15 - 12:00 Uhr, 3.B58
Mi, 02.11.2022, 08:15 - 12:00 Uhr, HS 9
Mi, 09.11.2022, 08:15 - 12:00 Uhr, HS 9
Mi, 16.11.2022, 08:15 - 12:00 Uhr, HS 9
Mi, 23.11.2022, 08:15 - 12:00 Uhr, HS 9
Mi, 30.11.2022, 08:15 - 12:00 Uhr, HS 9
Mi, 07.12.2022, 08:15 - 12:00 Uhr, HS 9
Mi, 14.12.2022, 08:15 - 12:00 Uhr, HS 9
Mi, 21.12.2022, 08:15 - 12:00 Uhr, HS 9
Mo, 23.01.2023, 14:00 - 15:30 Uhr, HS 1 (Prüfung)
Di, 06.06.2023, 12:30 - 14:00 Uhr, HS 8 (Wiederholungsprüfung) |
| Weitere Daten |
Teaching methods:
Part Qualitative Methods: Theoretical knowledge is conveyed through input lectures and reading assignments and is deepened and applied in exercises and presentations.
Part Quantitative Methods: In the lectures, knowledge is imparted using theory and data examples. In the exercises, small groups of students present their solutions in R to the exercises on topics from the previous lecture. There is also the opportunity to ask questions about topics that have already been covered and to start working on new exercises. |
| Umfang |
4 Semesterwochenstunden |
| Inhalt |
The course part Qualitative Methods covers the following topics:
• Setting the scene: theoretical frameworks, ontological positions, main features and uses of qualitative research
• Designing qualitative research: initial steps, research approaches, building comparison into qualitative research design
• Generating data: sampling strategies, overview of basic methods (interview, focus groups, observation), secondary/digital sources
• Interviewing: types of interviews, doing in-depth interviews (process, questions, and probes), issues and challenges
• Analysis of qualitative data: analytic strategies, processing, and coding data
• Interpreting and reporting data: description, explanation, generalization in qualitative research, displaying qualitative evidence
• Quality criteria, ethical issues and note on mixed methods
The course part Quantitative Methods covers the following topics:
• Basic concepts: Measuring, estimating, testing, and forecasting
• Introduction to the statistical software R
• Basics of descriptive statistics: Scale levels, statistical parameters
• Basics of inferential statistics: Sample and population, probabilities, random variables, and distribution families, basic elements of hypothesis testing
• Investigation of differences: Procedures for one- and two-group comparisons
• Examination of relations: Correlations and their test
• Analysis of dependencies: Linear and generalized linear models
|
| E-Learning |
Course materials are provided or linked, and exercises handed in via the e-learning platform Moodle. |
| Lernziele |
The overarching goal of the course Basic Research Methods is for incoming students to obtain a foundation in qualitative and quantitative research methods for the start of their studies in the M. Sc. in health sciences.
In the Qualitative Methods part of the course students should gain an understanding of the underlying principles of different methodologies and their consequences for scientific practice. They should know the methods of data collection and analysis used in health science and become aware of their respective strengths and weaknesses and familiarize with the qualitative research process.
The goal in the Quantitative Methods part is for students to understand statistical foundations, basic and some advanced statistical methods used in the health sciences and to learn how to apply them with the statistical software R. |
| Voraussetzungen |
Basic knowledge in qualitative methods, in statistics, and in the software R are an advantage, but not a requirement. Please bring your own laptops with an installation of a recent version of R. |
| Sprache |
Englisch |
| Anmeldung |
https://elearning.hsm-unilu.ch/course/view.php?id=547 |
| Prüfung |
Part Qualitative Methods: Presentation of a qualitative design incl. justification (group work, 30% of the grade for this course part) and written exam during the exam session at the end of the semester (70% of the grade for this course part).
Part Quantitative Methods: Submission and presentation of the solutions to an exercise sheet during the semester by small groups of students (20% of the grade for the course part Quantitative Methods) and written exam during the exam session at the end of the semester (80% of the grade for the course part Quantitative Methods).
Overall grade of 4.0 or better for successful completion of the course. |
| Abschlussform / Credits |
Schriftliche Prüfung / 6 Credits
|
| Hinweise |
Part Quantitative Methods: For the exercises during the course, the students work on their own laptops, on which they have installed the statistical software R and topic-specific R packages. |
| Hörer-/innen |
Ja |
| Kontakt |
hanna.fechner@unilu.ch / brigitte.hofstetter@doz.unilu.ch |
| Material |
Lecture slides, mandatory readings, exercise materials and other documents for the course are provided or linked on Moodle. |
| Literatur |
Further readings/textbooks on qualitative research:
Green, J. & Thorogood, N. (2018). Qualitative Methods for Health Research. Sage.
Silverman, D. (2020). Doing Qualitative Research. Sage.
Supplementary textbook for analyses with the statistical software R:
Field., A., Miles, J., Field, Z. (2012). Discovering Statistics Using R. Sage.
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