CUMULATE

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CUMULATE (Centralized User Modeling Architecture for TEaching) is a central user modeling server

designed to provide user modeling functionality to a student-adaptive educational system. It collects evidence (events) about student learning from multiple servers that interact with the student. It stores students' activities and infers their learning characteristics, which are the basis for an individual adaptation to them. ... External and internal inference agents process the flow of events and update the values in the inference model of the server. Each inference agent is responsible for maintaining a specific property in the inference model, such as the current motivation level of the student or the student's current level of knowledge for each course topic...

Kobsa, A. (2007) Generic User Modeling Systems In P. Brusilovsky, A. Kobsa and W. Nejdl (Eds.),
The Adaptive Web. Methods and Strategies of Web Personalization (pp. 136-154). Berlin / Heidelberg: Springer.

Overview

CUMULATE is a centralized user modeling server built for the [[ADAPT2|ADAPT² architecture. It is mainly targeted at providing user modeling support for adaptive educational hypermedia (AEH) systems. CUMULATE's data model consists of the following.

• users, groups of users, and group membership links (syndicated from Knowledge Tree)
• learning objects, learning object providers (client applications)
• knowledge components - concepts - grouped in learning domains
• metadata index - links between learning objects and corresponding concepts
• user activity log - historical log of all reported user interaction with learning objects
• assertions about user's knowledge of concepts ([concepts'] knowledge)
• summaries of user's interaction with learning objects ([learning objects'] progress)

CUMULATE implements several inference mechanisms to produce assertions about user's knowledge and progress, including the following.

• thresholded averaging
• asymptotic user knowledge assessment
• time-spent-reading

Modeling User's Knowledge

CUMULATE models user's knowledge of concepts with respect to the following levels of Bloom's taxonomy.

• knowledge - corresponds to reading tutorials or book chapters (Knowledge Sea II, AnnotatEd)
• understanding - reviewing examples, watching demos (WebEx, WADEIn demo mode)
• comprehension - solving problems (QuizPACK, SQLKnoT, [[QuizJET], WADEIn evaluation mode)

Utilizing CUMULATE

CUMULATE is has 3 major entry points:

1. interface for reporting user interaction with learning objects
2. interface for reporting changes to user knowledge of concepts in-the-raw (new)
3. interface for acquiring models of user knowledge/progress as a whole or in part

Interaction with CUMULATE is regulated by a set of protocols described here here.

Publications

• Zadorozhny, V., Yudelson, M., and Brusilovsky, P. (2008) A Framework for Performance Evaluation of User Modeling Servers for Web Applications. Web Intelligence and Agent Systems 6(2), 175-191. DOI
• Yudelson, M., Brusilovsky, P., and Zadorozhny, V. (2007) A user modeling server for contemporary adaptive hypermedia: An evaluation of the push approach to evidence propagation. In Conati, C., McCoy, K. F., and Paliouras, G. Eds., User Modeling, volume 4511 of Lecture Notes in Computer Science, pp 27-36. Springer, 2007. PDF DOI
• Brusilovsky, P., Sosnovsky, S. A., and Shcherbinina, O. (2005). User Modeling in a Distributed E-Learning Architecture. Paper presented at the 10th International Conference on User Modeling (UM 2005), Edinburgh, Scotland, UK, July 24-29, 2005. PDF DOI

See also

CUMULATE RDF Binding

Contacts

Michael V. Yudelson