MALKA220 Behavioral Economics Course description

This course provides an overview of behavioral economics for students and professionals interested in behavioral science. Whereas the focus is on a behavior analytic framework of choice behavior and decision-making, the course is highly interdisciplinary, as it includes concepts and cases drawn from economic, psychological, and social sciences.

Admission to the study program

On successful completion of the course, the student has the following learning outcomes classified as knowledge, skills and competence:

Knowledge

The student can

• describe and discuss the main distinctions between neoclassical economics, behavioral economics and behavior analysis, and define behavioral economics and describe the origins
• define the concepts of Homo economicus and bounded rationality
• define the core concepts of discounting
• define "beliefs, biases and heuristics" and describe typical heuristics
• define core principles in game theory

Skills

The student can

• discuss discounting in relation to the standard economic model and behavioral economics
• describe and discuss the concepts of rule-governed and contingency shaped behavior in the light of discounting
• discuss how nudging can affect choice, and analyze nudging in behavioral analytic terms
• discuss the concept of selection at the behavioral and cultural level in relation to micro- and macroeconomics
• discuss ethical concerns when influencing choice in the field of behavioral economics

Competence

The student can

• present core principles of behavioral economics to others in a way that meets the requirements of professional scientific communication
• present core principles of behavioral economics to the public
• discuss how behavior analysis can contribute to the field of behavioral economics
• present evidence based research from behavioral economics, and discuss different methods and applications
• discuss how the field of behavioral economics can contribute to further understanding of choice behavior

Campus-based lectures, exercises, oral presentations, discussions and individual papers are the main teaching methods. Students read selected texts in advance for each day of class, and everyone is expected to participate in class through questions and through joining in discussion. Feedback is used on written assignments.

The master’s program final exam is an independently written thesis in the form of a scientific article. Ideally, this work should be in preparation from the time when the student starts in the program. The candidates choose their own topics for the thesis. Theses may be written about topics from research projects run by faculty or initiated by the student. The thesis should be on a topic relevant for the field of behavioral science as the term is used in the context of the current degree. For theses concerned with theoretical perspective from fields other than behavior analysis, the thesis should include an account of a behavior analytic perspective on the topic of the thesis.

All courses included in the specialisation must be completed with pass grades and all coursework requirements must be approved before the candidate may submit the master’s thesis.

On successful completion of the course, the student has the following learning outcomes classified as knowledge, skills and competence:

Knowledge

The student can

• analyze and critically assess the scientific work of others

Skills

The student can

• demonstrate working knowledge of the ethical and technical principles that govern scientific research and publication, including international citation and reference standards
• demonstrate that they can conduct a supervised research project in accordance with research ethics guidelines and regulations, and guidelines from relevant governmental bodies (i. e. The Norwegian Data Protection Authority, relevant Norwegian Research Ethics Committees)
• choose and apply relevant methods of data collection for research or scientific inquiry
• write a thesis according to criteria determined by the university
• write a thesis according to the APA 7th standard and other reporting standards
• critically assess the results of his or her own work
• critically assess various sources of information
• employ artificial intelligence (AI) as a supportive tool in academic writing and research in an expedient and critical fashion, including being able to assess the quality of AI generated content, compare such content to academic sources, and reflect on ethical and professional implications of the use of AI

Competence

The student can

• participate in the development of the behavioral sciences
• justify their professional behavior with reference to ethical guidelines, general ethical considerations and their own assessment of the situation
• analyze and critically assess various sources of information with relevance for the thesis.

The following required coursework must be approved before the student can take the exam:

a. Research ethics seminar 1 and 2 must be fully attended

b. Introductory day for the course must be fully attended

c. Approved thesis outline

d. Approved ethical reflection note

e. A signed contract with the appointed supervisor

Thesis. Submission of master’s thesis according to program specifications, consisting of 1 scientific article. Technical standards according to the current APA manual. Submitting dates each year: June 15th and November 15th.

Thesis format

The 40 ECTS Master’s thesis consists of one article written in accordance with the author guidelines specified in the current APA Publication Manual. The length should be appropriate for the work that is reported, but should commonly not exceed 40 pages, including the title page, references, tables, and figures, but excluding appendices.

Ethics and data protection

An account of ethical considerations is regardless of thesis format. A risk -and vulnerability analysis (ROS-vurdering) should normally be conducted if the thesis includes empirical data on humans or nonhuman animals, and a case number should be provided when handing in the thesis. If data on humans are included in the thesis, an account of data protection issues is typically required. The description of ethical and data protection considerations can be included in the main body of the thesis. If the decision is made that such an account is unnecessary to include in the main body of the thesis, a reflection note on this topic should be attached to the thesis. A reflection note is a short description of ethical and data protection considerations, maximum 6000 characters, including spaces. For theses that do not include empirical data, research ethics relevant to the thesis should be discussed, either in the main body of the text or a reflection note.

Some Master projects may require consideration or approval from external bodies, such as Norwegian Centre for Research Data (NSD), the Regional Committee for Medicine and Health Sciences Research Ethics (REK), National Committee for Research Ethics in the Social Sciences and the Humanities (NESH), and/or internal or external data protection officials. It is ultimately the responsibility of the main supervisor or, if the main supervisor is external, the supervisor at OsloMet, to ensure that the relevant bodies are consulted. If external bodies are consulted, a case number should be provided when handing in the thesis. If a decision is made that there is no need to consult external bodies regarding ethics or data protection, a description of the deliberations preceding this decision is required, either in the main body of the thesis or in the reflection note. If the thesis is an empirical work, the main supervisor must state in writing that the research is conducted in accordance with current laws and regulations before the thesis can be submitted.