Worldwide Sites

You have been detected as being from . Where applicable, you can see country-specific product information, offers, and pricing.

Change country/language X

Keyboard ALT + g to toggle grid overlay

Investigating the Feasibility of Extracting Tool Demonstrations from In-Situ Video Content

ACM SIGCHI Conference on Human Factors in Computing Systems
2014

Investigating the Feasibility of Extracting Tool Demonstrations from In-Situ Video Content (4:43 min.)

Video title (x:xx min.)

Abstract

Short video demonstrations are effective resources for helping users to learn tools in feature-rich software. However manually creating demonstrations for the hundreds (or thousands) of individual features in these programs would be impractical. In this paper, we investigate the potential for identifying good tool demonstrations from within screen recordings of users performing real-world tasks. Using an instrumented image-editing application, we collected workflow video content and log data from actual end users. We then developed a heuristic for selecting demonstration clips, and had the quality of a sample set of clips evaluated by both domain experts and end users. This multi-step approach allowed us to characterize the quality of “naturally occurring” tool demonstrations, and to derive a list of good and bad features of these videos. Finally, we conducted an initial investigation into the potential of using machine learning techniques to identify good and bad video clips.

Related Publications

Related Projects

Software Learning

The Learning project aims to investigate advanced techniques for assisting users in learning complicated applications. We are interested in a range of investigations from the scientific study of the human learning process to prototyping novel interaction techniques for improving the general learning mechanisms that can be applied to all applications.

Heading

Descriptive text. Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt magna aliqua in reprehenderit.

Heading

Descriptive text. Lorem ipsum dolor sit amet, consectetur adipisicing elit, sed do eiusmod tempor incididunt magna aliqua in reprehenderit.