A case-based reasoning approach to provide adaptive feedback in microworlds

M. Gutierrez-Santos; Mihaela Cocea; G. Magoulas

A case-based reasoning approach to provide adaptive feedback in microworlds

M. Gutierrez-Santos
, Mihaela Cocea
, G. Magoulas

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

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Abstract

This paper presents a case-based reasoning (CBR) approach to provide adaptive support in microworlds. Interaction in microworlds is complex and unstructured, making the analysis of student behaviour difficult and the provision of computer-based feedback challenging. Our approach starts with the ellicitation of expected solutions to microworld tasks (both valid and common mistakes) to generate a case base. This is used to evaluate the actions of students and provide adapted feedback.

Original language	English
Title of host publication	Intelligent Tutoring Systems
Editors	V. Aleven, J. Kay, J. Mostow
Place of Publication	New York
Publisher	Springer
Pages	330 - 333
Number of pages	4
Edition	6095
ISBN (Print)	9783642134364.
Publication status	Published - 2010

Publication series

Name	Lecture Notes in Computer Science 2
Publisher	Springer
Number	6095

Keywords

case-based reasoning
exploratory learning environments
microworlds
adaptive feedback

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ITS.pdfAccepted author manuscript (Post-print), 113 KB

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

Cite this

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abstract = "This paper presents a case-based reasoning (CBR) approach to provide adaptive support in microworlds. Interaction in microworlds is complex and unstructured, making the analysis of student behaviour difficult and the provision of computer-based feedback challenging. Our approach starts with the ellicitation of expected solutions to microworld tasks (both valid and common mistakes) to generate a case base. This is used to evaluate the actions of students and provide adapted feedback.",

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A case-based reasoning approach to provide adaptive feedback in microworlds. / Gutierrez-Santos, M.; Cocea, Mihaela; Magoulas, G.
Intelligent Tutoring Systems. ed. / V. Aleven; J. Kay; J. Mostow. 6095. ed. New York: Springer, 2010. p. 330 - 333 (Lecture Notes in Computer Science 2; No. 6095).

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

TY - CHAP

T1 - A case-based reasoning approach to provide adaptive feedback in microworlds

AU - Gutierrez-Santos, M.

AU - Cocea, Mihaela

AU - Magoulas, G.

PY - 2010

Y1 - 2010

N2 - This paper presents a case-based reasoning (CBR) approach to provide adaptive support in microworlds. Interaction in microworlds is complex and unstructured, making the analysis of student behaviour difficult and the provision of computer-based feedback challenging. Our approach starts with the ellicitation of expected solutions to microworld tasks (both valid and common mistakes) to generate a case base. This is used to evaluate the actions of students and provide adapted feedback.

AB - This paper presents a case-based reasoning (CBR) approach to provide adaptive support in microworlds. Interaction in microworlds is complex and unstructured, making the analysis of student behaviour difficult and the provision of computer-based feedback challenging. Our approach starts with the ellicitation of expected solutions to microworld tasks (both valid and common mistakes) to generate a case base. This is used to evaluate the actions of students and provide adapted feedback.

KW - case-based reasoning

KW - exploratory learning environments

KW - microworlds

KW - adaptive feedback

M3 - Chapter (peer-reviewed)

SN - 9783642134364.

T3 - Lecture Notes in Computer Science 2

SP - 330

EP - 333

BT - Intelligent Tutoring Systems

A2 - Aleven, V.

A2 - Kay, J.

A2 - Mostow, J.

PB - Springer

CY - New York

ER -

A case-based reasoning approach to provide adaptive feedback in microworlds

Abstract

Publication series

Keywords

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User modelling in Exploratory Learning Environments

Cite this