Quantifying the personal creative experience: Evaluation of digital creativity support tools using self-report and physiological responses

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Carroll, E. (2013). Quantifying the personal creative experience: Evaluation of digital creativity support tools using self-report and physiological responses. Unc Charlotte Electronic Theses And Dissertations.
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Abstract

Creativity is understood intuitively, but it is not easily defined and therefore difficult to measure. This makes it challenging to evaluate the ability of a digital tool to support the creative process. When evaluating creativity support tools (CSTs), it is critical to look beyond traditional time, error, and other productivity measurements that are commonly used in Human-Computer Interaction (HCI) because these measures do not capture all the relevant dimensions of creativity support. Unfortunately, there are no clear measures of success to quantify in regards to creativity support tools, and this lack of 'convenient' metrics is a real challenge to their evaluation.In this dissertation, I introduce two computational methodologies for evaluating creativity support tools, including: (1) the Creativity Support Index (CSI), which is a psychometrically developed and validated survey, designed for evaluating the ability of a tool to support the creative process of users, and (2) a novel sensor data approach to measuring 'in-the-moment-creativity' (ITMC), to detect moments when users experience high creativity using electroencephalography (EEG), activity metrics (e.g., keyboard/mouse logger and accelerometer data), and machine learning.

Details
Author

Carroll, Erin

Title

Quantifying the personal creative experience: Evaluation of digital creativity support tools using self-report and physiological responses

Physical Description

1 online resource (142 pages) : PDF

Date

2013

Degree Granting Institution

University of North Carolina at Charlotte

Abstract

Creativity is understood intuitively, but it is not easily defined and therefore difficult to measure. This makes it challenging to evaluate the ability of a digital tool to support the creative process. When evaluating creativity support tools (CSTs), it is critical to look beyond traditional time, error, and other productivity measurements that are commonly used in Human-Computer Interaction (HCI) because these measures do not capture all the relevant dimensions of creativity support. Unfortunately, there are no clear measures of success to quantify in regards to creativity support tools, and this lack of 'convenient' metrics is a real challenge to their evaluation.In this dissertation, I introduce two computational methodologies for evaluating creativity support tools, including: (1) the Creativity Support Index (CSI), which is a psychometrically developed and validated survey, designed for evaluating the ability of a tool to support the creative process of users, and (2) a novel sensor data approach to measuring 'in-the-moment-creativity' (ITMC), to detect moments when users experience high creativity using electroencephalography (EEG), activity metrics (e.g., keyboard/mouse logger and accelerometer data), and machine learning.

Genre

doctoral dissertations

Subjects--Topics

Computer science
Psychology
Information science

Degree

Ph.D.

Keywords

Creativity Support Tools
Human Computer Interaction
Human Factors

Subject Area

Information Technology

Advisor(s)

Latulipe, Celine

Committee Members

Lipford, Heather
Maher, Mary Lou
Heggestad, Eric
Terry, Michael

Degree Note

Thesis (Ph.D.)--University of North Carolina at Charlotte, 2013.

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Rights Holder Information

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Identifier

Carroll_uncc_0694D_10435

Permalink

http://hdl.handle.net/20.500.13093/etd:1208