7 EC
Semester 1, period 3
5244ITIR7Y
| Owner | Master Brain and Cognitive Sciences |
| Coordinator | Vincent Tijms |
| Part of | Master Brain and Cognitive Sciences, |
Interdisciplinarity can be a hard thing to pull off. While it is easy to see the value of recombining knowledge, insights or methods from different fields, researchers from disparate backgrounds can find it hard to work with each other. Experts from different fields speak different languages, laden with hidden assumptions and jargon that oh-so-subtly varies per discipline. Within science, it is already hard to balance open-mindedness with critical thinking and in a multidisciplinary context this problem becomes even harder.
Still, if we are ever to gain an understanding of mind, brain and the way in which they relate to each other, it will depend on the recombination of insights from cognitive science, philosophy, neurobiology, linguistics, artificial intelligence and more. This is why researchers in brain and cognitive sciences need to learn what interdisciplinarity is -- and how to get there.
This course offers tools to integrate knowledge from different fields. It is a project-based course: you will be doing ideation, literature research, interdisciplinary integration and science communication for a project for which your team can make its own design choices. The goal: too discover new ways in which you can bring distinct scientific fields together.
The lectures in this course serve to explain the rationale behind the course and particular assignments. The seminars exist to have you practice the tools we offer, to discuss your progress with your tutor and also to just keep a cadence while you work on your project. The presentations are there to probe your understanding of the project you've been doing. The self-study exists so that you can read up on the topic of your choosing, discuss literature with your team members and work on assignments.
|
Activity |
Hours |
|
|
Hoorcollege |
6 |
|
|
Presentatie |
3 |
|
|
Project |
24 |
|
|
Werkcollege |
17 |
|
|
Self study |
130 |
|
|
Interdisciplinary Study Trip |
16 |
|
|
Total |
196 |
(7 EC x 28 uur) |
| Item and weight | Details |
|
Final grade | |
|
Integration Plan | |
|
Participation and progress meetings | |
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Peer assessment | |
|
Popular science article | |
|
Portfolio | Must be ≥ 6 |
|
Symposium presentation | Must be ≥ 6 |
The final grade for the course is calculated as the total points obtained throughout the assignments (0 - 100), divided by 10. For the blog post (0 - 10 points) and the final report (0-40 points), a minimum score is required. Missing assignments or not meeting the minimal scores leads to a non-pass mark at the end of the course.
The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl
| Week | Topic | Description |
| 1 | What is interdisciplinarity? |
|
| 2 | How to do interdisciplinary research? |
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| 3 | Scientific communication as a vehicle for interdisciplinarity |
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| 4 | Bringing it together |
|
Use of GenAI in MBCS
Within the Research Master Brain and Cognitive Sciences, you are generally allowed to use Generative AI (GenAI) to support your learning process. For example, you can use large language models (LLMs) to help your self-study by generating flashcards, or generating explanations of concepts. You do so at your own risk: an LLM may generate inaccurate or incomplete information for your studies. You are never allowed to use GenAI to generate work that you will hand in as an assignment, unless the assignment description explicitly allows you to do so.
Note: GenAI should be a support tool to help you reach the course's learning objectives, not a system to which you delegate activities that are meant to promote your learning. The course examiner has final say on which use cases are permissible or not within their course.
Never share personal information, research data, or course materials with a GenAI system, except for UvA AI Chat (https://aichat.uva.nl/). This UvA-hosted system was built with GDPR compliance and data security in mind. If you are in doubt about sharing information, don't share. You can always check with your course coordinator whether any intended use case is responsible.
Teachers are never allowed to use GenAI to grade your work. They may, however, use it to formulate their feedback.
For more on the MBCS policy, see the programme Canvas page.
Course-specific rules on GenAI use
Within this specific course, permissible GenAI use is limited to:
Last year, the course was considered to be too rigid to allow for creative work. We recognised that (it was a response to earlier feedback that the course was too free-form). The current solution is to offer structure for those who need it and design the course so that freedom is there for those who want it.
Another criticism was that challenge-based education did not work well for fundamental research master students, and that the experiences of students with different clients varied too much. We stepped away from the challenge-based, client-driven setup and are returning to a more traditional, academic form with this year's iteration. We do acknowledge that in earlier years, there was a strong demand for working with clients to to transdisciplinary research, but we suspect that student feedback was understating the complexity of making such education work.
Finally, the course leaned heavily onto Design Thinking as a way to do interdisciplinary work in earlier years. While we still believe that framework is valuable, it did at time obscure the real learning objectives we had. With a new, more free-form design, Design Thinking is not as central anymore.