DRE 7021 Research Ethics

DRE 7021 Research Ethics

Course code: 
DRE 7021
Department: 
Economics
Credits: 
0
Course coordinator: 
Plamen Toshkov Nenov
Samuli Knüpfer
Product category: 
PhD
Portfolio: 
PhD Economics courses
Semester: 
2019 Autumn
Active status: 
Active
Teaching language: 
English
Course type: 
One semester
Introduction

This course is a one-day workshop intended to educate students about the principles of research ethics in the social sciences and issues related to research ethics. The course aims at making doctoral students conscientious about ethics and ethical principles in the social sciences, and preventing fraudulent behavior in research.

Learning outcomes - Knowledge

To raise awareness about good ethical practices in connection with: 
1. Data collection, data management, sharing, and ownership.
2. Management of sensitive data. 
3. Proper referencing of others' research. 
4. Publication of research. 
5. Digitalization and (international) collaboration in research. 
6. Researchers in expert roles. 
7. Supervisor and mentor relationships.

Learning outcomes - Skills

After taking the course the students will be able to conduct empirical research following the best ethical practices related to data collection, management and sharing. They will also be able to properly reference other people's research in their own work.

General Competence

After taking the course students should be able to constructively reflect on the ethical issues associated with economic research and critically assess these issues in their own work. 

Course content

The course will focus on case studies of ethical problems and introducing the participants to tools that can reduce the problems. One important case study we will focus on, is Reinhart and Rogoffs controversial study of the effect of debt on economic growth. 
The tools will include an introduction to software and web based solutions that make it easier to create reproducible research. This includes a brief introduction to Jupyter notebooks which can be used with Python,R and many other data analysis frameworks.

Teaching and learning activities

-

Software tools
No specified computer-based tools are required.
Additional information

-

Qualifications

Enrollment in a PhD programme is a general requirement for participation in PhD courses at BI Norwegian Business School.
External candidates are kindly asked to attach confirmation of enrollment in a PhD programme when signing up for a course. Other candidates may be allowed to sit in on courses by approval of the course leader. Sitting in on a course does not permit registration for the course, handing in exams or gaining credits for the course. Course certificates or confirmation letters will not be issued for sitting in on courses.

Required prerequisite knowledge

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Exam categoryWeightInvigilationDurationGroupingComment exam
Exam category:
Activity
Form of assessment:
Class participation
Exam code:
DRE70211
Grading scale:
Point scale
Grading rules:
Internal examiner with external supervisor
Resit:
All components must, as a main rule, be retaken during next scheduled course
100No -Individual
Exams:
Exam category:Activity
Form of assessment:Class participation
Weight:100
Invigilation:No
Grouping (size):Individual
Duration: -
Comment:
Exam code:DRE70211
Grading scale:Point scale
Resit:All components must, as a main rule, be retaken during next scheduled course
Type of Assessment: 
Continuous assessment
Grading scale: 
Pass/fail
Total weight: 
100