Intelligent support for inquiry learning from images: a learning scenario and tool

Mulholland, Paul; Zdrahal, Zdenek; Abrahamcik, Jan and Wolff, Annika (2009). Intelligent support for inquiry learning from images: a learning scenario and tool. In: The 14th International Conference on Artificial Intelligence in Education (AIED2009), 6 - 10 Jul 2009, Brighton, UK, pp. 417–424.

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URL:	http://www.iospress.nl/html/9781607500285.php
DOI (Digital Object Identifier) Link:	https://doi.org/10.3233/978-1-60750-028-5-417
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Abstract

Inquiry learning involves the learner acquiring new concepts and skills by means of carrying out an investigation. Some previous studies have looked into how these learning activities can be carried out on source materials, such as web documents, and the provision of appropriate scaffolding to guide the learning process. Here we consider how intelligent support can be provided to guide the learner in analysing source materials and building knowledge from their interpretation. An important feature of our case study is that the source materials are images, potentially having greater variation in how they are interpreted and therefore increasing the need for intelligent support. Intelligent support provided by our system can identify patterns and inconsistencies in the learner’s interpretation and knowledge building, and offer recommendations based on comparison with a reference model. The recommendations derived from a reference model aim to guide the learner in reviewing and revising their interpretation of the images and the implications of these for their inferences, rather than directly providing a “right” or “wrong” evaluation of their answer.

Item Type:	Conference or Workshop Item
Copyright Holders:	2009 The authors and IOS Press
Extra Information:	Frontiers in Artificial Intelligence and Applications v.200 ISSN 0922-6389 Artificial Intelligence in Education - Building Learning Systems that Care: From Knowledge Representation to Affective Modelling Edited by Vania Dimitrova, Riichiro Mizoguchi, Benedict du Boulay, Art Graesser ISBN 978-1-60750-028-5
Academic Unit/School:	Faculty of Science, Technology, Engineering and Mathematics (STEM) > Knowledge Media Institute (KMi) Faculty of Science, Technology, Engineering and Mathematics (STEM) Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Research Group:	Centre for Research in Computing (CRC)
Item ID:	24923
Depositing User:	Kay Dave
Date Deposited:	01 Dec 2010 10:53
Last Modified:	09 Feb 2018 06:08
URI:	http://oro.open.ac.uk/id/eprint/24923
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