Abstract
The concept of Active Conceptual Modeling of Learning (ACM-L) has been explored in order to capture content and context changes that permit a comprehensive learning from the past, understanding the present, and forecasting the future. Such capability has not been fully explored and it is not available with today’s static oriented database system. The potential of creating a “database of intention” that can have its own aim to understand the intentions of its users and the changes to their environment. This paper explores an architectural approach for the “database of intention” with predictability power. The proposed architecture is presented, illustrated, and discussed.
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Ting, T.C., Chen, P.P., Wong, L. (2007). Architecture for Active Conceptual Modeling of Learning. In: Chen, P.P., Wong, L.Y. (eds) Active Conceptual Modeling of Learning. ACM-L 2006. Lecture Notes in Computer Science, vol 4512. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-77503-4_2
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DOI: https://doi.org/10.1007/978-3-540-77503-4_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-77502-7
Online ISBN: 978-3-540-77503-4
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