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Academic Methodologies and Study Skills I

Module name (EN): Academic Methodologies and Study Skills I
Degree programme: Health care management, Bachelor, ASPO 01.10.2018
Module code: BAME18-05
Hours per semester week / Teaching method: 5S (5 hours per week, accumulated)
ECTS credits: 7
Semester: 1
Duration: 2 semester
Mandatory course: yes
Language of instruction:
German
Assessment:
Exam achievement: Written exam

[updated 01.10.2020]
Applicability / Curricular relevance:
BAME18-05 Health care management, Bachelor, ASPO 01.10.2018, semester 1, mandatory course
Workload:
75 class hours (= 56.25 clock hours) over a 15-week period.
The total student study time is 210 hours (equivalent to 7 ECTS credits).
There are therefore 153.75 hours available for class preparation and follow-up work and exam preparation.
Recommended prerequisites (modules):
None.
Recommended as prerequisite for:
BAME18-07 Methodologies I
BAME18-09 Public Health II
BAME18-10 Expertise II
BAME18-13 Methodologies II
BAME18-15 Study Project
BAME18-20 Compulsory Elective II: Research Expertise I
BAME18-22 Compulsory Elective IV: Research Expertise II
BAME18-23 Compulsory Elective V: Evaluation


[updated 23.03.2021]
Module coordinator:
Prof. Dr. Martha Meyer
Lecturer:
Prof. Dr. Iris Burkholder
Prof. Dr. Martha Meyer


[updated 17.07.2020]
Learning outcomes:
Introduction to the Theory of Science:
After successfully completing this module, students will have become acquainted with different scientific-theoretical currents and be able to explain the influence these currents have on their choice of methods. They will be familiar with exemplary methods for gaining scientific knowledge, as well as the basic epistemological assumptions of all sciences. They will be able to address questions pertaining to truth and value judgements in the sciences and discuss the need for research ethics.
 
Descriptive statistics:
Students will gain insight into the basics of descriptive statistics for collecting, evaluating and presenting data. They will be able to select and calculate suitable graphical and algebraic methods for describing one or more characteristics using the scale of measure. Students will be able to present observations in such a way that the essential structures are recognizable and carry out initial analyses, also using statistical software such as SPSS.
 


[updated 01.10.2020]
Module content:
Introduction to the Theory of Science:
1. Major questions in the theory of science and epistemology
_        Knowledge vs. scientific knowledge
2. Epistemological foundations and the assumptions of all sciences
_
        Common methodological characteristics
3. Academic disciplines
_        Empirical-analytical / phenomenological-hermeneutical theory of science
_        Care giving and therapy sciences as practical sciences in their dual logic of action
4. The research process and value neutrality
_        The research process
_        Scientific reasoning and argumentation
_        Value judgement dispute
5. Research ethics
_        The relevance of ethics for research on humans
 
Descriptive statistics:
1.        Basics and terms (objectives of descriptive statistics, population and sample, characteristic and characteristic value)
2.        Scale of measure
3.        Algebraic methods (location, scatter)
4.        Graphical methods
5.        Use of software


[updated 01.10.2020]
Teaching methods/Media:
Print and electronic media, slides, PC exercises

[updated 01.10.2020]
Recommended or required reading:
Introduction to the Theory of Science:
_        Chalmers AF (2007). Wege der Wissenschaft. Einführung in die Wissenschaftstheorie. Berlin: Springer
_        Diekmann A (2007). Empirische Sozialforschung. Grundlagen, Methoden, Anwendung. Reinbek: Rowohlt
_        Kromrey H (2009). Empirische Sozialforschung. Verlag für Sozialwissenschaften. Wiesbaden vormals Opladen: Leske & Budrich/UTB 1040
_        Schurz G (2008). Einführung in die Wissenschaftstheorie. Wissenschaftliche Buchgesellschaft, Darmstadt. 3. Aufl.
 
Descriptive statistics:
_        Bühner M, Ziegler M (2009). Statistik für Psychologen und Sozialwissenschaftler. München u.a.: Pearson
_        Held L, Rufibach K, Seifert B (2013). Medizinische Statistik. Konzepte, Methoden, Anwendungen. München u.a.: Pearson
_        Hornsteiner G (2012). Daten und Statistik. Eine praktische Einführung für den Bachelor in Psychologie und Sozialwissenschaften. Berlin, Heidelberg: Springer VS
_        Kukartz U, Rädiker S, Ebert T, Schehl J (2013). Statistik. Eine verständliche Einführung. Wiesbaden: Springer VS
_        Müller M (2011). Statistik für die Pflege. Handbuch für Pflegeforschung und -wissenschaft. Bern: Huber
_        Rasch B, Friese M, Hofmann W, Naumann E (2014). Quantitative Methoden 1. Einführung in die Statistik für Psychologen und Sozialwissenschaftler. Heidelberg: Springer
Additional literature will be announced in the course.


[updated 01.10.2020]
[Thu Dec  2 02:28:26 CET 2021, CKEY=mwaib, BKEY=me3, CID=BAME18-05, LANGUAGE=en, DATE=02.12.2021]