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Supervising doctoral students is one of the most rewarding things that anyone in university education can do. Guiding new scholars to become independent researchers, who conduct a project, write up the results, present them at the viva, is a satisfying experience. However – often supervisors state observations such as “my PhD students are diligent workers – only they haven’t got a clue as to what the data they came up with actually mean” – or “my PhD students are really bright, but they do not want to stay in science so they do not really put all possible effort into their projects”.
Many of the possible problems between supervisor and PhD student stem from diverging expectations or assumptions about each other that have never been raised.
In order to prevent possible problems we will be looking at the “ideal cycle” (selecting the doctoral student, getting him/her started, designing and planning a project, keeping up the students motivation, supervising the writing of the thesis and preparing him/her to present the data). We will also be looking at remedial measures when problems have occurred by discussing cases you bring along from your own experiences.
The aim of this blended learning workshop is to maximize the chances of your students being successful and foreshadow problems that might arise. The workshop will be conducted in a blended learning format. We will start with an online kick-off on 21.01.2025. This will be followed by a self-study/group work phase, before we conclude the workshop on 10.02.2025 with an on-site meeting.
Learning objectives:
After this course you will be able to …

• define your role as supervisor in regards to your leadership style and your responsibilities.
• define the core competencies (soft skills) needed in a doctoral student in order to successfully do a PhD with you.
• optimize your ideal supervision-cycle, starting with the recruitment interview.
• describe a framework of communication for regular performance evaluation with your students.
• apply some ideas about trouble shooting.

Teaching Learning Activities:

• online/blended/eLearning
• theoretical input
• group work / self-study phases

Prerequisite:

• Completion of module I would be nice, but is no „must“.
• You should have doctoral (or MA students) to supervise