Fostering Creative Visualisation Skills Through Data-Art Exhibitions
August 29, 2024 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Jonathan C. Roberts
arXiv ID
2408.16479
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CY
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
Data-art exhibitions offer a unique and real-world setting to foster creative visualisation skills among students. They serve as real-world platform for students to display their work, bridging the gap between classroom learning and professional practice. Students must develop a technical solution, grasp the context, and produce work that is appropriate for public presentation. This scenario helps to encourage innovative thinking, engagement with the topic, and helps to enhance technical proficiency. We present our implementation of a data-art exhibition within a computing curriculum, for third-year degree-level students. Students create art-based visualisations from selected datasets and present their work in a public exhibition. We have used this initiative over the course of two academic years with different cohorts, and reflect on its impact on student learning and creativity.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted