Identifying user strategies in exploratory learning with evolving task modelling

Mihaela Cocea; G. Magoulas

doi:10.1109/IS.2010.5548339

Identifying user strategies in exploratory learning with evolving task modelling

Mihaela Cocea, G. Magoulas

School of Computing

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

184 Downloads (Pure)

Abstract

In this paper we present work on adaptive identification of learners’ strategies, gradually developing a higher level of adaptation based on evolving models of mathematical generalisation tasks in an Exploratory Learning Environment. A similarity-based classification approach is defined for the identification of strategies, using an initially small number of classes (i.e. strategies). A strategy is composed of several patterns with relations between them. An evolution monitor component observes changes in the environment and triggers a mechanism that builds-up the task model. The task model evolves when new relevant information becomes available by adding a new strategy (class) or a new inefficient pattern, i.e. patterns that make it difficult for the learner to generalise.

Original language	English
Title of host publication	2010 5th IEEE International Conference on Intelligent Systems (IS 2010): Proceedings of a meeting held 7-9 July 2010, London, United Kingdom
Place of Publication	Piscataway
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	13 -18
Number of pages	6
ISBN (Print)	9781424451630
DOIs	https://doi.org/10.1109/IS.2010.5548339
Publication status	Published - Jul 2010
Event	Intelligent Systems (IS), 2010 5th IEEE International Conference - London Duration: 7 Jul 2010 → 9 Jul 2010

Conference

Conference	Intelligent Systems (IS), 2010 5th IEEE International Conference
Period	7/07/10 → 9/07/10

Keywords

evolution monitor component
evolving task modelling
exploratory learning environment
similarity-based classification approach
user strategy identification
computer aided instruction
pattern classification
user interfaces

Access to Document

10.1109/IS.2010.5548339

IEEE_IS.pdfAccepted author manuscript (Post-print), 655 KB

http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5548339&tag=1

User modelling in Exploratory Learning Environments
Haig, E. (PI)
1/10/07 → 31/10/11
Project: Research

Cite this

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title = "Identifying user strategies in exploratory learning with evolving task modelling",

abstract = "In this paper we present work on adaptive identification of learners{\textquoteright} strategies, gradually developing a higher level of adaptation based on evolving models of mathematical generalisation tasks in an Exploratory Learning Environment. A similarity-based classification approach is defined for the identification of strategies, using an initially small number of classes (i.e. strategies). A strategy is composed of several patterns with relations between them. An evolution monitor component observes changes in the environment and triggers a mechanism that builds-up the task model. The task model evolves when new relevant information becomes available by adding a new strategy (class) or a new inefficient pattern, i.e. patterns that make it difficult for the learner to generalise.",

keywords = "evolution monitor component, evolving task modelling, exploratory learning environment, similarity-based classification approach, user strategy identification, computer aided instruction, pattern classification, user interfaces",

author = "Mihaela Cocea and G. Magoulas",

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booktitle = "2010 5th IEEE International Conference on Intelligent Systems (IS 2010): Proceedings of a meeting held 7-9 July 2010, London, United Kingdom",

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address = "United States",

note = "Intelligent Systems (IS), 2010 5th IEEE International Conference ; Conference date: 07-07-2010 Through 09-07-2010",

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Cocea, M & Magoulas, G 2010, Identifying user strategies in exploratory learning with evolving task modelling. in 2010 5th IEEE International Conference on Intelligent Systems (IS 2010): Proceedings of a meeting held 7-9 July 2010, London, United Kingdom. Institute of Electrical and Electronics Engineers Inc., Piscataway, pp. 13 -18, Intelligent Systems (IS), 2010 5th IEEE International Conference, 7/07/10. https://doi.org/10.1109/IS.2010.5548339

Identifying user strategies in exploratory learning with evolving task modelling. / Cocea, Mihaela; Magoulas, G.
2010 5th IEEE International Conference on Intelligent Systems (IS 2010): Proceedings of a meeting held 7-9 July 2010, London, United Kingdom. Piscataway: Institute of Electrical and Electronics Engineers Inc., 2010. p. 13 -18.

Research output: Chapter in Book/Report/Conference proceeding › Chapter (peer-reviewed) › peer-review

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AB - In this paper we present work on adaptive identification of learners’ strategies, gradually developing a higher level of adaptation based on evolving models of mathematical generalisation tasks in an Exploratory Learning Environment. A similarity-based classification approach is defined for the identification of strategies, using an initially small number of classes (i.e. strategies). A strategy is composed of several patterns with relations between them. An evolution monitor component observes changes in the environment and triggers a mechanism that builds-up the task model. The task model evolves when new relevant information becomes available by adding a new strategy (class) or a new inefficient pattern, i.e. patterns that make it difficult for the learner to generalise.

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KW - evolving task modelling

KW - exploratory learning environment

KW - similarity-based classification approach

KW - user strategy identification

KW - computer aided instruction

KW - pattern classification

KW - user interfaces

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BT - 2010 5th IEEE International Conference on Intelligent Systems (IS 2010): Proceedings of a meeting held 7-9 July 2010, London, United Kingdom

PB - Institute of Electrical and Electronics Engineers Inc.

CY - Piscataway

T2 - Intelligent Systems (IS), 2010 5th IEEE International Conference

Y2 - 7 July 2010 through 9 July 2010

ER -

Identifying user strategies in exploratory learning with evolving task modelling

Abstract

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Keywords

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User modelling in Exploratory Learning Environments

Cite this