Student research groups with a focus on data literacy

In the course of the constant digital transformation of society, science and the economy and the associated growing flood of data and increasing complexity in all areas, the competent and critical handling of data is a key skill for students in all disciplines. Data literacy, i.e. the basic skills required for a critical understanding and implementation of data collection, storage, processing, analysis and visualisation processes as well as for reflecting on contemporary data practices, is one of, if not the central prerequisite for individual participation in a world shaped by digitality.

With this in mind, we support students of all subjects in developing their digital and data skills within the framework of independent projects and in acquiring additional skills in scientific work and research-based learning.

As the overall DDLitLab project ends on 31 December 2025, there will unfortunately be no further funding round.

The projects of the individual funding rounds at a glance

In total, our funding comprises 77 students in 31 project groups, who are able to work intensively on their own chosen, data-driven topics and thus individually expand their expert knowledge and digital and data skills.

Photo: Google DeepMind / unsplash

In the 1st phase, 8 projects were selected for funding from 1 October 2022 to 30 September 2023.
In the 2nd funding round, the jury selected 6 projects to be supported from 1 April 2023 to 31 March 2024.
The 3rd round of calls resulted in 10 student projects, which were funded from 1 October 2023 to 31 March 2024.
The 4th and final round of calls resulted in 7 student projects, which will be funded in the period from 1 October 2024 to 30 September 2025.

Spotlight on exciting projects!

Take a look at selected projects of the student research groups focussing on data literacy and get to know the groups and their projects.

Photo: UHH / Rehder

NoLoCK

The aim of the NoLoCK project was to analyse and evaluate no- and low-code platforms and their limitations in comparison to native development. It was investigated whether these platforms are suitable as competence bridges in the context of employee-driven (digital) innovations.

More about the project

Photo: UHH / Rehder

FinWAIID

Our world is changing, and the tools we use to research it must change too. In cetacean (whale) research, photo identification is a crucial technique for tracking individuals and studying population size and dynamics. FinWAIID explores an automated approach to streamline this process by developing a deep learning pipeline for detection.

More about the project

Photo: UHH / Rehder

Beenough

Studies on food competition between wild bees and honey bees are inconsistent and often only meaningful at a local level. The aim of the project is therefore to carry out such an analysis for northern Germany. The aim is to identify possible regional differences and areas with particularly high competition potential.

More about the project

Information for mentors

What is the goal of the student reasearch groups?

In the Digital and Data Literacy in Teaching Lab (DDLitLab), we promote the holistic and university-wide teaching of data literacy to students in the context of knowledge-exchange-oriented, subject-specific, and interdisciplinary courses. Outside of the curriculum, we also want to support all students in increasing and applying their data literacy in independently designed innovative projects. This is where you come in, because for every project, student groups rely on your subject expertise.

Who can be a mentor?

All members of the academic staff at Universität Hamburg are eligible.

What needs to be done before submitting the project proposal?

You have an initial discussion with the student group and assign 3, 6, or 9 credit points to the project proposal, depending on its scope. Then, as a mentor, you sign the project proposal, which your student group submits with you in CC by mail at ddlitlab.isa"AT"uni-hamburg.de. The projects applied for will be reviewed in a competitive, 2-stage selection process based on set evaluation criteria. The funding decision will be announced in mid-July.

What are the tasks in case of a positive funding decision?

You will guide your student group during the period applied for (between 6 to 12 months), contribute your expertise, and support the students in achieving a qualitatively acceptable project result. Appointments to discuss content-related and other issues will be arranged flexibly between you and your student group. In addition, it would be desirable for you to participate in central events, such as project presentations by your students at the start and end of the project. At the end of the project, you will receive a written report and potentially created artifacts from your student group for ungraded evaluation. Special attention should be paid to the quality and scope of the project results defined at the beginning. If thecriteria in these 2 areas have been sufficiently met, the final credit will be awarded upon your signature.

What are the tasks in case of a positive funding decision?

You will guide your student group during the period applied for (between 6 to 12 months), contribute your expertise, and support the students in achieving a qualitatively acceptable project result. Appointments to discuss content-related and other issues will be arranged flexibly between you and your student group. In addition, it would be desirable for you to participate in central events, such as project presentations by your students at the start and end of the project. At the end of the project, you will receive a written report and potentially created artifacts from your student group for ungraded evaluation. Special attention should be paid to the quality and scope of the project results defined at the beginning. If thecriteria in these 2 areas have been sufficiently met, the final credit will be awarded upon your signature.

Information on funding

What is funded?

Data-driven, innovative student projects that address and apply aspects of data literacy in independent research projects
The implementation of data challenges in cooperation with practice partners
In addition, projects that expand on AI or generative AI in this call for proposals are particularly welcome

Who can be funded?

Students of all Bachelor's, Master's and state examination degree programs at Universität Hamburg in small groups of 2 to 5 people
Prerequisite: Mentor, i.e. a member of the academic staff at Universität Hamburg who is responsible for supervising the small group

What do mentors need to be prepared for?

All information on the role and tasks of mentors in the context of student projects can be found on the website "Information for Mentors"

What is the duration of a project?

6-12 months, beginning Oct. 1 2024

What does the funding cover?

Maximum of EUR 10,000 per student project
Option of crediting 3 to 9 credit points in "Freiem Wahlbereich"
Use of software and hardware provided by the DDLitLab

Is my project idea suitable?

If you are not sure whether your project idea is suitable in terms of content, gather inspiration and take a look at the funded student projects from the past
Arrange an individual appointment with us at ddlitlab.isa"AT"uni-hamburg.de

The application phase ended on 31.05.2024. It is no longer possible to submit project application

Supervision of Student research groups with a focus on data literacy

Contact

Stephan Leible

Research Associate

Jungiusstraße 11c

20355 Hamburg

Email: stephan.leible"AT"uni-hamburg.de