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SBIR Phase II: Providing Tools for Richer eLearning Assessment

Award Information
Agency: National Science Foundation
Branch: N/A
Contract: 0620380
Agency Tracking Number: 0441519
Amount: $500,000.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: IT
Solicitation Number: NSF 04-551
Timeline
Solicitation Year: 2004
Award Year: 2006
Award Start Date (Proposal Award Date): N/A
Award End Date (Contract End Date): N/A
Small Business Information
1100 South Main Street
Grapevine, TX 76051
United States
DUNS: N/A
HUBZone Owned: Yes
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Adele Goldberg
 Dr
 (650) 856-8720
 adele@thinkfive.com
Business Contact
 Linda Chaput
Title: Dr
Phone: (415) 385-4632
Email: lchaput@thinkfive.com
Research Institution
N/A
Abstract

This Small Business Innovation Research (SBIR) Phase II project will study effective models for carrying out assessments employing challenging puzzle-like questions that incorporate distractor analyses in which meaning is assigned to complex responses. Such distractor analyses apply where there is the possibility that the test taker can give alternative correct, partially correct, and incorrect answers. Metadata and distractor analyses will be combined to provide in-depth reports on student test performance. This new rule-based solution to distractor analysis meets a significant challenge in being able to include engaging problems in assessments of student progress in quantitative courses, such as Algebra and Geometry. The research will further develop question authoring and test construction tools. As a consequence of this work, educators using these new technologies will be able to move beyond online testing based solely on multiple-choice, single-answer questions that are known to be unmotivating for many students. The goals are twofold: to provide varied, interesting, and even gamelike learning interactions that incorporate motivational and pedagogically valuable feedback; and to do so in a form in which empirical evidence can be used to improve the assessment corpus - both the metadata and the rules used for defining distractor analysis, especially where the items are novel question types.

* Information listed above is at the time of submission. *

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