Conference Paper

Sensors Model Student Self Concept in the Classroom.

DOI: 10.1007/978-3-642-02247-0_6 Conference: User Modeling, Adaptation, and Personalization, 17th International Conference, UMAP 2009, formerly UM and AH, Trento, Italy, June 22-26, 2009. Proceedings
Source: DBLP

ABSTRACT In this paper we explore ndings from three experiments that use minimally invasive sensors with a web based geometry tutor to create a user model. Minimally invasive sensor technology is mature enough to equip classrooms of up to 25 students with four sensors at the same time while using a computer based intelligent tutoring system. The sensors, which are on each student's chair, mouse, monitor, and wrist, provide data about posture, movement, grip tension, arousal, and facially expressed mental states. This data may provide adaptive feedback to an intelligent tutoring system based on an individual student's aective states. The experiments show that when sensor data supplements a user model based on tutor logs, the model reects a larger percentage of the students' self-concept than a user model based on the tutor logs alone. The models are further expanded to classify four ranges of emotional self-concept including frustration, interest, condence, and excitement with over 78% accuracy. The emotional predictions are a rst step for intelligent tutor systems to create sensor based personalized feedback for each student in a classroom environment. Bringing sensors to our children's schools addresses real problems of students' relationship to mathematics as they are learning the subject.

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    ABSTRACT: We provide evidence of persistent gender effects for students using advanced adaptive technology while learning mathematics. This technology improves each gender’s learning and affective predispositions toward mathematics, but specific features in the software help either female or male students. Gender differences were seen in the students’ style of use of the system, motivational goals, affective needs, and cognitive/affective benefits, as well as the impact of affective interventions involving pedagogical agents. We describe 4 studies, with hundreds of students in public schools over several years, which suggest that technology responses should probably be customized to each gender. This article shows differential results before, during, and after the use of adaptive tutoring software, indicating that digital tutoring systems can be an important supplement to mathematics classrooms but that male and female students should be addressed differently. Female students were more receptive than male students to seeking and accepting help provided by the tutoring system and to spending time seeing the hints; thus, they had a consistent general trend to benefit more from it, especially when affective learning companions were present. In addition, female students expressed positively valenced emotions most often and exhibited more productive behaviors when exposed to female characters; these affective pedagogical agents encouraged effort and perseverance. This was not the case for male students, who had more positive outcomes when no learning companion was present and their worst affective and cognitive outcomes when the female character was present. (PsycINFO Database Record (c) 2013 APA, all rights reserved)
    Journal of Educational Psychology 01/2013; 105(4):957. · 3.08 Impact Factor

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Aug 12, 2014

David G. Cooper