First meeting


Please prepare the following for your first meeting with your advisor.

  • (Re)share your thesis proposal

    • Please email/post your research proposal to your coach, even if you haven’t updated it after handing it in (PDF format). Do so at least three days before the meeting.
    • If you’re supervised in a team, send the research proposal to members of your thesis circle.
  • Review the agenda below to be prepared to address data availability

    • Will you get access to the data? can you prepare summary statistics of the data already?
    • Necessary investments in developing technical skills (have you learnt everything you need to successfully work on your thesis? (e.g., data preparation, Python for k-means clustering, R for fixed-effects models, etc.)
  • Make an evaluation of your individual strengths and weaknesses and share those with me! (this way, we can anticipate problems)

    • What’s your ambition with this thesis?
    • Where do you want to be in five years from now?
    • What are you really good at?
    • Which areas excite you, and wish to learn more about?
    • What is it that you really dislike?
  • Know the content on this website, and the various requirements that are already relevant at this stage of your thesis process

Preliminary meeting agenda

We will most likely discuss the contribution of your study and your data.

  1. Getting to know each other (e.g., brief topic pitch; talk about ambitions and strengths/weaknesses)
  2. Setting expectations
  3. Discuss meeting schedule
  • How to submit work and receive feedback
  • Allocate students to thesis circles
  • Determine date for handing in final thesis draft
  1. General feedback on research proposals
  2. Expectations for next meeting
  • Revised introduction
  • Literature review
  • Organize your project (directory structure, workflows)
  • Complete gathering data, start inspecting it
  1. Individual feedback on research proposals
  • Refine project ideas and contribution
  • Discuss data collection and data availability (i.e., clearly inform your advisor about data availability, or the steps that you still need to undertake to receive your data).
  • Discuss skill development (which skills are still required for successful completion? Which courses do you still need to follow?)