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Advances in Multimedia
Volume 2008, Article ID 825671, 10 pages
Research Article

An Effective Multimedia Item Shell Design for Individualized Education: The Crome Project

1Department of Computing Science, University of Alberta, Canada T6B 2E8
2Department of Computer and Information Science, University of Pennsylvania, PA 16802, USA

Received 10 August 2007; Revised 15 January 2008; Accepted 12 February 2008

Academic Editor: S. Takamura

Copyright © 2008 Irene Cheng and Anup Basu. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


There are several advantages to creating multimedia item types and applying computer-based adaptive testing in education. First is the capability to motivate learning by making the learners feel more engaged and in an interactive environment. Second is a better concept representation, which is not possible in conventional multiple-choice tests. Third is the advantage of individualized curriculum design, rather than a curriculum designed for an average student. Fourth is a good choice of the next question, associated with the appropriate difficulty level based on a student's response to the current question. However, many issues need to be addressed when achieving these goals, including: (a) the large number of item types required to represent the current multiple-choice questions in multimedia formats, (b) the criterion used to determine the difficulty level of a multimedia question item, and (c) the methodology applied to the question selection process for individual students. In this paper, we propose a multimedia item shell design that not only reduces the number of item types required, but also computes difficulty level of an item automatically. The concept of question seed is introduced to make content creation more cost-effective. The proposed item shell framework facilitates efficient communication between user responses at the client, and the scoring agents integrated with a student ability assessor at the server. We also describe approaches for automatically estimating difficulty level of questions, and discuss preliminary evaluation of multimedia item types by students.