![]() In other words, the perceptual feature view assumes that bar graphs have a unique graph schema and so do dot plots and tally charts. ![]() Each graph has its graphical pattern, which is the most distinguishable perceptual characteristic of a graph ( Kosslyn, 1989). The hypothesis of perceptual features suggests that each type of graph is determined by a different schema, leading to the graphs being interpreted differently ( Lohse, 1993). There are two main hypotheses regarding the structure of graph schemas. For instance, the difference between groups A and B in the bar graph is 4 ( Figure 1). Finally, the relevant information is located, and the answer is provided. For instance, the required information in this study is the difference between group A and group B. Fourth, the required information is determined. Integrating the perceived information with the graph schema is thus the most crucial step, as one activates the mental representation in the long-term memory and matches it to the early visual input. The graph schema describes relationships between ideas and fosters assumptions for the missing information ( Simkin and Hastie, 1987). A graph schema is a generic scaffold that directs readers to insert new information into a complex knowledge representation ( Simkin and Hastie, 1987 Pinker, 1990). During the interpretive processes, the graph schema stored in the long-term memory is activated. Third, the conceptual relations were retrieved from the long-term memory and the interpretive processes start. Second, parts of a visual mental model about the decoded information become represented in the capacity-limited working memory. For instance, a bar graph is decoded as several closed boxes, labels, and x-y coordinates. First, the visual information in the data graph is decoded via pattern recognition processes. These theories take the perceptual process, short-term memory, and long-term memory into account ( Shah and Carpenter, 1995 Shah and Hoeffner, 2002 Ratwani et al., 2008). ![]() Many theories of graph comprehension have been proposed to explain how we extract information from a graph ( Pinker, 1990 Lohse, 1993 Shah and Carpenter, 1995 Peebles and Cheng, 2002, 2003). tally) is the most suitable for group comparison. In addition, it examined which graphic type (bar vs. This study, therefore, tested whether the graph schema is based on perceptual features or common invariant structures. However, other types of data graphs can also be used for group comparisons, such as dot plots or tally charts ( Figure 1). Bar graphs have often been investigated, and it is suggested that bars are ideal for discrete comparisons ( Pinker, 1990 Tversky et al., 2000 Shah and Freedman, 2009). There are, however, different hypotheses on whether the graph schema is based on specific perceptual features (i.e., each graph has a unique graph schema, Lohse, 1993) or common invariant structures (i.e., shared by several graphs, Ratwani and Trafton, 2008). In theories of graph comprehension, activating the graph schema is the most important step ( Simkin and Hastie, 1987 Pinker, 1990). Therefore, a crucial question is, how we extract specific information from graphs and which type of graph is the most suitable for group comparison. They are widely used in everyday life, such as in politics, sports, stock market reports, and scientific articles. ![]() ![]() Moreover, processing time increased when the position difference of compared groups was increased.ĭata graphs are the ideal tools for comparing group differences. Tally charts were the more efficient format for group comparison compared to bar graphs. Yet, bar and dot graphs showed no mixing costs when paired together. Tally charts mixed either with bar graphs or with dot graphs showed mixing costs. The results suggested that graph schemas are based on a common invariant structure. Participants received graphs with quantities for three groups in randomized positions and were given the task of comparing two groups. Three experiments were conducted using the mixing-costs paradigm. tally) is the best to compare discrete groups. Thus, this study examined whether graph schemas are based on perceptual features (i.e., each graph has a specific schema) or common invariant structures (i.e., graphs share several common schemas), and which graphic type (bar vs. Different graph types might differ in group comparison due to differences in underlying graph schemas. ![]()
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