Be the Data: Embodied Visual Analytics

Autor/inn/en	Chen, Xin; Self, Jessica Zeitz; House, Leanna; Wenskovitch, John; Sun, Maoyuan; Wycoff, Nathan; Evia, Jane Robertson; Leman, Scotland; North, Chris
Titel	Be the Data: Embodied Visual Analytics
Quelle	In: IEEE Transactions on Learning Technologies, 11 (2018) 1, S.81-95 (15 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Chen, Xin) ORCID (Self, Jessica Zeitz) ORCID (Wenskovitch, John) ORCID (Sun, Maoyuan) ORCID (Evia, Jane Robertson)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	1939-1382
DOI	10.1109/TLT.2017.2757481
Schlagwörter	Data; Visualization; Multidimensional Scaling; Mathematics Instruction; Mathematical Concepts; Interaction; Workshops; Grade 6; Grade 7; Grade 10; Grade 11; High School Graduates; Undergraduate Students; Grade 3; Student Surveys; Qualitative Research; Statistical Analysis; Video Technology + Suchen Sie Ihr Suchwort? Daten; Visualisation; Visualisierung; Mehrdimensionale Analysis; Mathematics lessons; Mathematikunterricht; Interaktion; Lernwerkstatt; Schulung; School year 06; 6. Schuljahr; Schuljahr 06; School year 07; 7. Schuljahr; Schuljahr 07; School year 11; 11. Schuljahr; Schuljahr 11; High school; High schools; Graduate; Graduates; Oberschule; Absolvent; Absolventin; School year 03; 3. Schuljahr; Schuljahr 03; Schülerbefragung; Qualitative Forschung; Statistische Analyse
Abstract	With the rise of big data, it is becoming increasingly important to educate groups of students at many educational levels about data analytics. In particular, students without a strong mathematical background may have an unenthusiastic attitude towards high-dimensional data and find it challenging to understand relevant complex analytical methods, such as dimension reduction. In this paper, we present an embodied approach for visual analytics designed to teach students about exploring alternative 2D projections of high-dimensional data points using weighted multidimensional scaling. We propose a novel concept, "Be the Data", to explore the possibilities of using human's embodied resources to learn from high-dimensional data. In our implemented 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 move within the room with respect to each other to collaboratively construct alternative projections and receive visual feedback about relevant data dimensions. In this way, students can pose hypotheses about the data to discover the statistical support as well as learn about complex concepts such as high-dimensional distance. We conducted educational workshops with students in various age groups inexperienced in complex data analytical methods. Our findings indicate that "Be the Data" provided the necessary engagement to enable students to quickly learn about high-dimensional data and analysis processes despite their minimal prior knowledge. (As Provided).
Anmerkungen	Institute of Electrical and Electronics Engineers, Inc. 445 Hoes Lane, Piscataway, NJ 08854. Tel: 732-981-0060; Web site: http://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=4620076
Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2020/1/01