From qualitative reasoning models to Bayesian-based learner modeling

U. Milošević; B. Bredeweg

From qualitative reasoning models to Bayesian-based learner modeling

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

Abstract

Assessing the knowledge of a student is a fundamental part of intelligent learning environments. We present a Bayesian network based approach to dealing with uncertainty when estimating a learner’s state of knowledge in the context of Qualitative Reasoning (QR). A proposal for a global architecture is given. The essentials of the belief network structure for individual scenarios are described, while paying special attention to knowledge aggregation and some design issues that are specific for the domain of QR.

Original language	English
Title of host publication	24th International Workshop on Qualitative Reasoning (QR’10), Portland, Oregon, USA
Editors	J. de Kleer, K.D. Forbus
Pages	132-137
Number of pages	6
Publication status	Published - 2010
Externally published	Yes

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@inproceedings{1714dc7323644c29874c4959d2cf79e2,

title = "From qualitative reasoning models to Bayesian-based learner modeling",

abstract = "Assessing the knowledge of a student is a fundamental part of intelligent learning environments. We present a Bayesian network based approach to dealing with uncertainty when estimating a learner{\textquoteright}s state of knowledge in the context of Qualitative Reasoning (QR). A proposal for a global architecture is given. The essentials of the belief network structure for individual scenarios are described, while paying special attention to knowledge aggregation and some design issues that are specific for the domain of QR.",

author = "U. Milo{\v s}evi{\'c} and B. Bredeweg",

note = "24th International Workshop on Qualitative Reasoning (QR{\textquoteright}10), Portland, OR, USA ; Conference date: 08-08-2010 Through 10-08-2010",

year = "2010",

language = "English",

pages = "132--137",

editor = "{de Kleer}, J. and K.D. Forbus",

booktitle = "24th International Workshop on Qualitative Reasoning (QR{\textquoteright}10), Portland, Oregon, USA",

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T1 - From qualitative reasoning models to Bayesian-based learner modeling

AU - Milošević, U.

AU - Bredeweg, B.

N1 - 24th International Workshop on Qualitative Reasoning (QR’10), Portland, OR, USA ; Conference date: 08-08-2010 Through 10-08-2010

PY - 2010

Y1 - 2010

N2 - Assessing the knowledge of a student is a fundamental part of intelligent learning environments. We present a Bayesian network based approach to dealing with uncertainty when estimating a learner’s state of knowledge in the context of Qualitative Reasoning (QR). A proposal for a global architecture is given. The essentials of the belief network structure for individual scenarios are described, while paying special attention to knowledge aggregation and some design issues that are specific for the domain of QR.

AB - Assessing the knowledge of a student is a fundamental part of intelligent learning environments. We present a Bayesian network based approach to dealing with uncertainty when estimating a learner’s state of knowledge in the context of Qualitative Reasoning (QR). A proposal for a global architecture is given. The essentials of the belief network structure for individual scenarios are described, while paying special attention to knowledge aggregation and some design issues that are specific for the domain of QR.

M3 - Conference contribution

SP - 132

EP - 137

BT - 24th International Workshop on Qualitative Reasoning (QR’10), Portland, Oregon, USA

A2 - de Kleer, J.

A2 - Forbus, K.D.

ER -

From qualitative reasoning models to Bayesian-based learner modeling

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