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Best Practices in Behavioral Research - Open Science, Data Protection, Research Ethics and Research Data Management

 
WS 2021
  0010012

Dates
Fr 15.10.2021–04.02.2022 16:00–18:00  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::

Commment
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: ˆ Demonstrate knowledge of the main concepts and principles of open and responsible science. ˆ Understand the way in which empirical research processes have developed. ˆ Assess the strengths and weaknesses of dierent research practices . ˆ Demonstrate an ability to apply the main concepts to a variety of empirical research projects. ˆ 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

Mehr... Legende Termintypen

 = 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.  = 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).

Mehr… 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

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