MSc Project: Structure and Proposed Timeline
The Center for Cognitive and Decision Sciences (CDS) aims to understand human decision-making and contribute to improving decision-making through evidence-based practices and guidelines.
The goal of the master project is to help each MSc student maximize their learning potential and ensure solid knowledge in psychological theory, data science methods, project management, and communication skills that are crucial to any career in business or academia.
We offer below a diagram and detailed text concerning the structure and timeline of the MSc project in Cognitive and Decision Sciences. For the specific topics offered, search for Cognitive and Decision Science MSc projects in Mastermatch.
The figure above illustrates a prototypical timeline for students working towards an MSc thesis at the Center for Cognitive and Decision Sciences. This timeline encompasses 4 semesters, with the last (fourth) semester corresponding to the main period of thesis writing. The first 3 semesters consist of a combination of regular meetings between the student and the main advisor (Advisor meetings), self-directed learning and research (Project work), group sessions of coding and data analysis (Hackathon), and weekly group meetings between students and all CDS members (e.g., Brownbag). The Center for Cognitive and Decision Sciences offers a number of additional seminars that can complement many of the goals of the Master project and are offered in a way that can further strengthen student progress (but their attendance has fully optional character). See below for additional information concerning each of these components.
Please note that the working language of the center is English, consequently, joint activities (Hackathon, Brownbag) are typically held in English; however, advisor meetings, thesis writing, and student presentations can be conducted in either English or German.
The student meets the main advisor on a regular basis (e.g., weekly) to discuss progress and establish an individual learning program that will help the student work towards the MSc thesis. The meetings can take place individually or in small groups of students who are pursuing closely related topics.
Each student completes a self-progress checklist at the beginning and end of each semester. The checklist provides a list of learning goals to help each student construct a specific learning plan for the semester (and evaluate the respective learning experience at the end of the semester). Each student discusses the checklist at the start and end of each semester with the main advisor.
Project work is geared to working on developing expertise in theory and methods as well as project management that can be instrumental in writing a MSc thesis. The MSc involves any type of empirical work consisting of one (or more) primary studies using any set of approaches (e.g., observational, experimental, simulation), or research synthesis of several studies (e.g., meta-analysis). The area of research and the specific research question of the MSc thesis is jointly agreed upon between the MSc student and the main advisor. The topic of the thesis can be modified at any point throughout the first 3 semesters, although it is a goal to identify a suitable topic as early as possible in the process.
Every semester all students and CDS members participate in a joint programming hackathon aimed at developing data-analysis skills (data visualization, programming, statistical modeling). Whenever necessary and desired, MSc students can receive prior training (e.g., during the CDS brown-bag colloquium or through additional workshops) to ensure a productive hackathon.
The CDS brownbag (colloquium) takes place in the form of weekly one-hour group meetings and is a forum for discussion and training for MSc students and CDS staff members. It consists of
Journal club: discussion of published scientific papers or working papers by CDS members
Workshops: Workshops can cover any aspect of data collection or analyses, including aspects of ethics (ethical application), technical skills (programming experiments, designing surveys), open science (making data publicly available), or programming and data analytics (R workshops).
Presentations: CDS members can present ongoing or completed research and each MSc student presents an overview of work conducted throughout the semester (typically, at the end of the semester, ca. 15 min presentation + discussion).
The CDS master project can function in a stand-alone fashion. Nevertheless, students can profit from additional coursework offered by CDS members that emphasize evidence-based decision making and data analytics training. Students can discuss the potential of supporting coursework for their individual learning plans with their main advisors at the beginning and end of each semester.