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  1. International Journal of Artificial Intelligence in Education
  2. International Journal of Artificial Intelligence in Education : Volume 24
  3. International Journal of Artificial Intelligence in Education : Volume 24, Issue 2, June 2014
  4. Carelessness and Affect in an Intelligent Tutoring System for Mathematics
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International Journal of Artificial Intelligence in Education : Volume 27
International Journal of Artificial Intelligence in Education : Volume 26
International Journal of Artificial Intelligence in Education : Volume 25
International Journal of Artificial Intelligence in Education : Volume 24
International Journal of Artificial Intelligence in Education : Volume 24, Issue 4, December 2014
International Journal of Artificial Intelligence in Education : Volume 24, Issue 3, September 2014
International Journal of Artificial Intelligence in Education : Volume 24, Issue 2, June 2014
How Should Intelligent Tutoring Systems Sequence Multiple Graphical Representations of Fractions? A Multi-Methods Study
Analysing Student Programs in the PHP Intelligent Tutoring System
Carelessness and Affect in an Intelligent Tutoring System for Mathematics
International Journal of Artificial Intelligence in Education : Volume 24, Issue 1, January 2014
International Journal of Artificial Intelligence in Education : Volume 23

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Carelessness and Affect in an Intelligent Tutoring System for Mathematics

Content Provider Springer Nature Link
Author Baker, Ryan S. J. d. Rodrigo, Ma. Mercedes T. San Pedro, Maria Ofelia Z.
Copyright Year 2014
Abstract We investigate the relationship between students’ affect and their frequency of careless errors while using an Intelligent Tutoring System for middle school mathematics. A student is said to have committed a careless error when the student’s answer is wrong despite knowing the skill required to provide the correct answer. We operationalize the probability that an error is careless through the use of an automated detector, developed using educational data mining, which infers the probability that an error involves carelessness rather than not knowing the relevant skill. This detector is then applied to log data produced by high-school students in the Philippines using a Cognitive Tutor for scatterplots. We study the relationship between carelessness and affect, triangulating between the detector of carelessness and field observations of affect. Surprisingly, we find that carelessness is common among students who frequently experience engaged concentration. This finding implies that a highly engaged student may paradoxically become overconfident or impulsive, leading to more careless errors. In contrast, students displaying confusion or boredom make fewer careless errors. Further analysis over time suggests that confused and bored students have lower learning overall. Thus, their mistakes appear to stem from a genuine lack of knowledge rather than carelessness.
Starting Page 189
Ending Page 210
Page Count 22
File Format PDF
ISSN 15604292
Journal International Journal of Artificial Intelligence in Education
Volume Number 24
Issue Number 2
e-ISSN 15604306
Language English
Publisher Springer New York
Publisher Date 2014-02-26
Publisher Institution International AIED Society
Publisher Place New York
Access Restriction One Nation One Subscription (ONOS)
Subject Keyword Carelessness Educational data mining Educational Technology User Interfaces and Human Computer Interaction Artificial Intelligence (incl. Robotics) Computers and Education Affect Cognitive tutor
Content Type Text
Resource Type Article
Subject Education Computational Theory and Mathematics E-learning
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