Analysis on Cognitive Strategies of Scientific Predicting according to 6th Graders' Predicting Skills Based on Eye Movement
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This study aims to analyze the eye movement of elementary school students during a predicting process in a scientific problem solving situation. Forty students in 6th grade from South Korea participated and solved two problems designed to assess their predicting skill. The participants predicted results involving gradual change in shape and temperature. SMI’s Eye Tracker was used to collect and analyze eye movement data. Among 40 students, 15 students (group A) got all the answers right, 17 students (group B) got only half of the answers right, and 8 students (group C) got all the answers wrong. Group A spent little time on reading questions but focused on keywords in the question. They showed active eye movements between clues, discovered tendencies, and checked for accuracy. Group B concentrated on the keywords and clues but had difficulty finding tendencies. Group C spent a long time understanding the questions but missed the keywords and clues. They showed a lot of meaningless and busy saccades. Eye movements were analyzed with eye movement measures like fixation duration time, saccade, and scan path. To find different eye movement patterns between Groups A and C, every eye movement of the participants was categorized. Six eye movement patterns were found during the predicting process regardless of predicting skill. But these common patterns appeared in a different manner for each group. Cognitive strategies that participants used in the process of predicting were found during the process analysis. Every student followed certain steps to predict but used different strategies as well. Two cognitive strategies would help develop teaching methods in a problem solving process using scientific prediction.
Abstract
This study aims to analyze the eye movement of elementary school students during a predicting process in a scientific problem solving situation. Forty students in 6th grade from South Korea participated and solved two problems designed to assess their predicting skill. The participants predicted results involving gradual change in shape and temperature. SMI’s Eye Tracker was used to collect and analyze eye movement data. Among 40 students, 15 students (group A) got all the answers right, 17 students (group B) got only half of the answers right, and 8 students (group C) got all the answers wrong. Group A spent little time on reading questions but focused on keywords in the question. They showed active eye movements between clues, discovered tendencies, and checked for accuracy. Group B concentrated on the keywords and clues but had difficulty finding tendencies. Group C spent a long time understanding the questions but missed the keywords and clues. They showed a lot of meaningless and busy saccades. Eye movements were analyzed with eye movement measures like fixation duration time, saccade, and scan path. To find different eye movement patterns between Groups A and C, every eye movement of the participants was categorized. Six eye movement patterns were found during the predicting process regardless of predicting skill. But these common patterns appeared in a different manner for each group. Cognitive strategies that participants used in the process of predicting were found during the process analysis. Every student followed certain steps to predict but used different strategies as well. Two cognitive strategies would help develop teaching methods in a problem solving process using scientific prediction.
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