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Best Practices in Behavioral Research - Open Science, Data Protection, Research Ethics and Research Data Management
Teaching language
Englisch
other lecturers
Holger FUTTERLEIB
Dates
Wö |
Fr |
15.10.2021–04.02.2022 |
16:00–18:00 |
C03-LG 1 | 135
|
Pandemie/Pandemic: ONLINE
|
Registration
Registration takes place via the central distribution procedure: https://www.uni-erfurt.de/studium/studium-fundamentale/verteilungsverfahren
Modules
B Ang 2021 SFIS#02 // S 6LP ::196580::
B EWI 2021 SFIS#02 // S 6LP ::196574::
B FÖ 2021 SFIS#02 // S 6LP ::196564::
B Ger 2021 QSFIS#02 // S 6LP ::196579::
B Ges 2021 SFIS#02 // S 6LP ::196565::
B IntB 2021 SFIS#02 // S 6LP ::196566::
B KaR 2021 SFIS#02 // S 6LP ::196567::
B Kom 2021 SFIS#02 // S 6LP ::196568::
B Kun 2021 SFIS#02 // S 6LP ::196569::
B Lit 2021 SFIS#02 // S 6LP ::196570::
B MUS 2021 SFIS#02 // S 6LP ::196571::
B Phi 2021 SFIS#02 // S 6LP ::196572::
B PPäd 2021 SFIS#02 // S 6LP ::196578::
B PSY 2021 SFIS#02 // S 6LP ::196573::
B Rel 2021 SFIS#02 // S 6LP ::196563::
B Sta 2021 SFIS#02 // S 6LP ::196575::
B Stu 2011 MTG#02 // S 6LP ::196583::
B TEC 2021 SFIS#02 // S 6LP ::196576::
MTheol KaTh 2009 296SF#01 // S 6LP ::196581::
MTheol KaTh 2015 A696SF#01 // S 6LP ::196582::
MTheol KaTh 2021 SFIS#02 // S 6LP ::196577::
Comment
This syllabus may be subject to change without prior notice. The latest changes will be announced in class
and in the most current version posted on Moodle. this version: 25.09.2020
Course description: Across disciplines empirical research with human subjects has become increasingly
important. Over the last decades, psychologists, economists and researchers from other disciplines have joined
forces to study how people process information and actually make decisions, rather than how they should
make decisions to act in line with the predictions of classic behavioral models. The new eld has provided
an understanding of how people's decisions deviate from predicted choices as well as the consequences of
such deviations for many stakeholders in society, like consumers, managers, rms, and policy makers.
At the same time advances in computational infrastructure and web services paved the way for faster and
more comfortable data collection. Following the rightly call for open science and sustainable research practices, workows and research practice have gradually adapted to these changed ways of data collection. As a
consequence many empirical research processes are getting more complex and the data collection is accompanied by various additional tasks. From a critical review of potential ethical issues, the pre-registration of
the research design, to compliance with data protection regulations and sustainable data preparation and
storage.
The aim of this course is to provide a grounding and practical experience in the main areas of research
process management within behavioral research, including research ethics, privacy issues and informed consent, research data management and other means that foster the transparency and accessibility of scientic
research. For each area we will study three things:
1. Some deterrent examples of poor research practices.
2. Best practices in dierent disciplines.
3. Practical implications for empirical research processes.
Objectives and learning outcomes: By the end of the course students should be able to:
Demonstrate knowledge of the main concepts and principles of open and responsible science.
Understand the way in which empirical research processes have developed.
Assess the strengths and weaknesses of dierent research practices .
Demonstrate an ability to apply the main concepts to a variety of empirical research projects.
Construct and substantiate arguments on a variety of topics covered in the course.
Prerequisite(s): No pre-requisites. Open to students of all elds of study.
Course language: The course language is English, unless all participants are native German speakers.
Recommended prior knowledge: Basic knowledge in empirical methods, like surveys, experiments, interviews and others, is useful but not essential to understand the concepts discussed in the course. As part
1of the assignments you will work (in groups) on your own research idea(s). It is not necessary to have a
full-blown research idea at the beginning of the course. You will have time to work on your idea together
with other students during the course.
Grading and assignments: Your grade will be based on a 90 minutes closed book exam that will be
held at the end of the course. The course is complemented by a number of practical exercises in which
you will work through the main concepts and principles discussed in the course. There will be a homework
assignment for each of the main topics. You should work on the assignments in groups and be prepared to
present your results in class.
Course outline:
Part 1 Introduction to Open Science
Why Open Science?
Open Science Framework(s)
Pre-Registration
Open Data and Open Materials
Part 2 Data Protection and Privacy
Data Protection in Research
Personal and Sensitive Data
Informed Consent and Voluntary Participation
Anonymization and Payments
Part 3 Research Ethics and Ethics Approval
Negligible Risk Research
Autonomy of Participants and Adequate Information
Risks and Potential Harm to Participants, Researchers and Society
Ethics Approval and Institutional Review Boards
Part 4 FAIR Research Data Management
Findable, Accessible, Interoperable, and Re-usable
Meta Data and Persistent Identiers
How to go FAIR
Literature
Course materials: The course is based on academic papers and online resources which will be available
on Moodle. Below you nd some introductory papers for each of the main parts of the course.
Mirowski, P. (2018). The future(s) of open science. Social Studies of Science, 48(2), 171-203.
https://doi.org/10.1177/0306312718772086
RatSWD [Rat für Sozial- und Wirtschaftsdaten] (2020). Data Protection Handout. 2nd Edition. RatSWD
Output 8(6). Berlin, Rat für Sozial- und Wirtschaftsdaten (RatSWD).
https://doi.org/10.17620/02671.50
European Commission (2018). Ethics in Social Science and Humanities. Horizon 2020 Online Manual.
https://ec.europa.eu/research/participants/data/ref/h2020/other/hi/h2020_ethics-soc-scie
nce-humanities_en.pdf
Wilkinson, M., Dumontier, M., Aalbersberg, I. et al. The FAIR Guiding Principles for scientic data management and stewardship. Scientic Data 3, 160018 (2016).
https://doi.org/10.1038/sdata.2016.18
Legende Termintypen
Wö = wöchentlicher Termin
, ET = Einzeltermin
, AB = A- oder B-Woche
, Vo = Vorbesprechung
, Ex = Exkursion
, Kl = Klausur
, Tä, At, Wt = täglicher (Block-)Termin
, nV = nach Vereinbarung/nicht festgelegt.
Wö = wöchentlicher Termin (meets weekly)
, ET = Einzeltermin (meets one time only)
, AB = A- oder B-Woche (alternating: “A” or “B” weeks)
, Vo = Vorbesprechung (preliminary meeting)
, Ex = Exkursion (excursion/study trip)
, Kl = Klausur (exam)
, Tä, At, Wt = täglicher (Block-)Termin (meets daily/block seminar)
, nV = nach Vereinbarung/nicht festgelegt (by appointment, TBA).
Legende Raumbezeichnungen
AMG = AudiMaxGebäude
, APS = AlteParteiSchule
, FG = Forschungsgebäude
, GH = Gartenhaus
, GSH = Große Sporthalle
, HdProjekte = Haus der Projekte
, KSyn = Kleine Synagoge
, LG = Lehrgebäude
, MG = Mitarbeitergbäude
, MTV Halle = Männerturnverein Halle
, SH JP = Schwimmhalle Johannesplatz
, WBS = Willy Brandt School
, ZSG = Zentralschulgarten
Die genaue Lage der Lehrveranstaltungsgebäude können Sie
dem Campusplan entnehmen.
Please check the campus map for the location of the university buildings and
facilities.