Using the eye tracker, the present study was conducted to explore the cognitive process of problem finding of undergraduates in the contradictory and potential conditions, which focused on the four eye-movement areas of interest. Based on our hypothesis, we expected the quality and quantity of problem finding of two groups(high ability group and low ability group) would show significant difference in the contradictory and potential problem finding conditions, which would be reflected in the eye movement model. Furthermore, the eye movement characteristics would be correlated with the quantity and quality of problem finding. We think the analysis of eye track can show the eye movement rules which could not be reflected by the static indicators. The mixed design with 2(question situation: a contradictory situation, a potential situation) ×2(subject category : high ability group, low ability group) × 4(interest areas: the first to the fourth interest area) was conducted in the study. The question situation and interest area were within-group factors, while the subject category was a between-group factor. The dependent variable included the quantity and quality of problem finding and the eye movement indexes(e.g. the fixation duration, fixation frequency, regression frequency, pupil diameter and eye track in the overall and four areas of interest). In the experiment, subjects were required to find problems in the contradictory and potential situations. The eye tracker recorded eye movement parameters when subjects found problems. The results were as follows. First, the average fixation duration in the potential situation was significant longer than the time in the contradictory situation, which may reflect that the cognitive processing in the potential situation was much more difficult than it in the contradictory situation. The pupil diameter size in the contradictory situation was bigger than it in the potential situation. The regression frequency for high ability group was more than that for low ability group, which indicated the positive role of the relationship and integration of information in the problem finding. Second, the eye movement in problem finding was significant different in the four areas of interest. In the region with essential information, many eye movement indexesraised, such as fixation duration, fixation frequency, and pupil diameter, which indicated subjects would put more effort. Particularly, the total fixation duration and fixation frequency in the second, third and fourth areas were more than these in the first area. The average fixation duration and pupil diameter size of undergraduates in the rear area were more than these in the front area. The regression frequency in the second area was more than it in the first area. In the contradictory situation, the total fixation duration, fixation frequency and regression frequency were correlated significantly with the quantity of problems, while the regression frequency was correlated significantly with the quality of problems in the contradictory situation. The regression frequency was correlated significantly with the quantity of problems in the potential situation. The relationship between the eye movement indexes and the quantity or the quality of problems in the areas of interest was almost the same with in total. Third, the fixation area matched the problem finding area which indicated the eye movement followed the thinking in problem finding. Searching behavior across area was observed in the first and the last fixation area which means the search for clues and final inspection and evaluation. High ability group spent less time in a stable fixation phase, which reflected their superiority of the flexibility in information conversion. For problem finding, the factors of group category and situation were reflected in eye movement indexes. Because of the differences in material property and difficulty, there was a significant difference of eye movement in the situation between each area of interest. All kinds of static eye movement indexes could better reflect the quantity rather than the quality of problem finding. However, the regression frequency was a sensitive index of reflecting the problem-finding ability, and the analysis of the dynamic eye track revealed the rules that a single static index cannot. Overall, using the eye tracker to investigate the cognitive process of problem finding could not only improve the accuracy of the experimental research, but also conduce to deeply explore the internal information processing mechanism of problem finding.
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