Thesis subject
Innovations in Data Science Education: The Data Factory (BSc/MSc)
This project involves an investigation into how data science education can be improved by harnessing the advanced communication potential of eXtended Reality (XR) technologies (an umbrella term referring to Augmented, Virtual and Mixed Reality technologies).
Short description
Within data science education, students experience four layers of learning that together form the Data Science Pipeline: 1) Data Sourcing – covering big data, variety in data (i.e., structured/unstructured) and data collection methodologies; 2) Data Cleaning and Manipulation – involving governance, storage, removal of errors, fixing artefacts and feature extraction; 3) Data Analysis – encompassing the exploration processes, descriptive statistics, machine/deep learning and generation of results; and 4) Data Visualisation and Storytelling – presentation of the findings in a meaningful and communicative manner. These layers take the students on a journey from raw data collection to establishing new understanding and insight in their own specific field of study. The pipeline can be considered as comparable to a Data Factory production line.
The aim of this project is investigate the design of an eXtended Reality (XR) software application (XR is an umbrella term referring to Augmented, Virtual and Mixed Reality technologies) that is dynamic so that it can be used in different data-focused courses at WUR - whereby the inclusion of the third dimension would enable students to better visualise complex processes. XR is proven to have enormous potential for education and its inclusion in the existing pedagogic practice caters for the students to have the opportunity to learn differently than the norm. Further, as part of the investigation, there will be an opportunity to be involved in organising a co-creation workshop (often also referred to as a hackathon) for WUR-based students to come together and design concepts for an XR-game. The event will involve students forming teams and designing XR-based data science games over a period of 48-hours.
Objectives and Tasks
- Conduct a detailed literature review on existing XR-based solutions for higher education;
- Support the development and setup of a student-focuses co-creation workshop / hackathon;
- Design a solution for the use of XR in Data Science education and propose a case study for testing;
- Collect quantitative/qualitative feedback on the design and suitability for Data Science education;
Literature
- Virtual reality for biochemistry education: the cellular factory, J Barrow, W Hurst, J Edman, N Ariesen, C Krampe, Education and Information Technologies, 1-26, https://doi.org/10.1007/s10639-023-11826-1
Requirements
- Courses: Data Science Concepts (INF-34306);
- Required skills/knowledge: Willingness to learn new software tools (such as Unity game engine), general interest in XR and Data Science;
Key words: eXtended Realities, Augmented Reality, Virtual Reality, Education, Information technology, Data Science.
- Will Hurst (will.hurst@wur.nl)
- Caspar Krampe (caspar.krampe@wur.nl)