TY - GEN
T1 - Analysing engineering expertise of high school students using eye tracking and multimodal learning analytics
AU - Gomes, July Silveira
AU - Yassine, Mohamed
AU - Worsley, Marcelo
AU - Blikstein, Paulo
N1 - Funding Information:
This material is based upon work supported by the National Science Foundation under the CAREER Award #1055130 and the Lemann Center at Stanford University.
Publisher Copyright:
© 2013 International Educational Data Mining Society. All rights reserved.
PY - 2013/1/1
Y1 - 2013/1/1
N2 - In this paper, we describe results of a multimodal learning analytics pilot study designed to understand the differences in eye tracking patterns found to exist between students with low and high performance in three engineering-related computer games, all of which require spatial ability, problem-solving skills, and a capacity to interpret visual imagery. In the first game, gears and chains had to be properly connected so that all gears depicted on the screen would spin simultaneously. In the second game, students needed to manipulate lines so as to ensure that no two intersected. In the final game, students were asked to position gears in specific screen locations in order to put in motion onscreen objects. The literature establishes that such abilities are related to math learning and math performance. In this regard, we believe that understanding these differences in student’s visual processing, problem-solving, and the attention they dedicate to spatial stimuli will be helpful in making positive interventions in STEM education for diverse populations.
AB - In this paper, we describe results of a multimodal learning analytics pilot study designed to understand the differences in eye tracking patterns found to exist between students with low and high performance in three engineering-related computer games, all of which require spatial ability, problem-solving skills, and a capacity to interpret visual imagery. In the first game, gears and chains had to be properly connected so that all gears depicted on the screen would spin simultaneously. In the second game, students needed to manipulate lines so as to ensure that no two intersected. In the final game, students were asked to position gears in specific screen locations in order to put in motion onscreen objects. The literature establishes that such abilities are related to math learning and math performance. In this regard, we believe that understanding these differences in student’s visual processing, problem-solving, and the attention they dedicate to spatial stimuli will be helpful in making positive interventions in STEM education for diverse populations.
KW - Constructionism
KW - Eye tracking
KW - Games
KW - Multimodal learning analytics
KW - Simulations
KW - Spatial ability
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M3 - Conference contribution
AN - SCOPUS:85084017840
T3 - Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013
BT - Proceedings of the 6th International Conference on Educational Data Mining, EDM 2013
A2 - D'Mello, Sidney K.
A2 - Calvo, Rafael A.
A2 - Olney, Andrew
PB - International Educational Data Mining Society
T2 - 6th International Conference on Educational Data Mining, EDM 2013
Y2 - 6 July 2013 through 9 July 2013
ER -