Be the Data: Embodied Visual Analytics
| dc.contributor.author | Chen, Xin | en |
| dc.contributor.committeechair | North, Christopher L. | en |
| dc.contributor.committeechair | House, Leanna L. | en |
| dc.contributor.committeemember | Polys, Nicholas F. | en |
| dc.contributor.department | Computer Science | en |
| dc.date.accessioned | 2016-08-23T08:00:21Z | en |
| dc.date.available | 2016-08-23T08:00:21Z | en |
| dc.date.issued | 2016-08-22 | en |
| dc.description.abstract | With the rise of big data, it is becoming increasingly important to educate students about data analytics. In particular, students without a strong mathematical background usually have an unenthusiastic attitude towards high-dimensional data and find it challenging to understand relevant complex analytical methods, such as dimension reduction. In this thesis, we present an embodied approach for visual analytics designed to teach students exploring alternative 2D projections of high dimensional data points using weighted multidimensional scaling. We proposed a novel application, <i>Be the Data</i>, to explore the possibilities of using human's embodied resources to learn from high dimensional data. In our system, each student embodies a data point and the position of students in a physical space represents a 2D projection of the high-dimensional data. Students physically moves in a room with respect to others to interact with alternative projections and receive visual feedback. We conducted educational workshops with students inexperienced in relevant data analytical methods. Our findings indicate that the students were able to learn about high-dimensional data and data analysis process despite their low level of knowledge about the complex analytical methods. We also applied the same techniques into social meetings to explain social gatherings and facilitate interactions. | en |
| dc.description.degree | Master of Science | en |
| dc.format.medium | ETD | en |
| dc.identifier.other | vt_gsexam:8708 | en |
| dc.identifier.uri | http://hdl.handle.net/10919/72287 | en |
| dc.publisher | Virginia Tech | en |
| dc.rights | In Copyright | en |
| dc.rights.uri | http://rightsstatements.org/vocab/InC/1.0/ | en |
| dc.subject | Visual Analytics | en |
| dc.subject | Embodied Interaction | en |
| dc.subject | Collaborative Learning | en |
| dc.subject | Human-Computer Interaction | en |
| dc.subject | Immersive Environment | en |
| dc.title | Be the Data: Embodied Visual Analytics | en |
| dc.type | Thesis | en |
| thesis.degree.discipline | Computer Science and Applications | en |
| thesis.degree.grantor | Virginia Polytechnic Institute and State University | en |
| thesis.degree.level | masters | en |
| thesis.degree.name | Master of Science | en |