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Erschienen in:
2013 | OriginalPaper | Buchkapitel
Designing Computational Systems for Serendipity in Learning
verfasst von : Maria Taramigkou, Fotis Paraskevopoulos, Efthimios Bothos, Dimitris Apostolou, Gregoris Mentzas
Erschienen in: Scaling up Learning for Sustained Impact
Verlag: Springer Berlin Heidelberg
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Serendipity, the process of making fortunate discoveries for which someone was not looking for, can play a crucial role in leveraging creativity in learning [1]. Serendipity enables creative connections to develop while it can have a role in revealing hidden connections or “hidden analogies”, especially in a social context such as in most learning processes [2]. The results of a chance encounter can result in new ideas relevant to the learner’s previous knowledge [3]. In previous work, we have reviewed the related literature and identified five enabling factors for serendipity [4]:
diversity
,
unexpectedness
or
novelty
,
personalization
,
visualization
, and
social interaction
. The aim of this paper is to construct an architectural framework based on the aforementioned factors that can be used as a guide in the development of information seeking systems aiming to leverage serendipity in learning.