Students’ local vs. global views of data distributions: a cross-grade-level analysis using eye-tracking

Abstract The ability to interpret and compare data distributions is an important educational goal. Inherent in the statistical concept of distribution is the need to focus not only on individual data points or small groups of data points (so-called local view), but to perceive a distribution as a whole, allowing to recognize global features such as center, spread, and shape (so-called global view). However, the latter is challenging for students to acquire. This study, involving 68 students in grades 4, 6, and 8, had two main objectives. First, we aimed to examine the potential impact of grade level on how students perceive and compare distributions presented in dot plots. Despite variations in specific pre-knowledge, our findings showed no significant grade-related differences in students’ gaze behavior or their ability to process global features when comparing distributions. This finding suggests that there is no significant developmental trend across grade levels regarding students’ capacity to perceive distributions globally, a critical aim in statistics education. Our second objective was to extend the findings of our previous work regarding the identification of specific eye-tracking measures as indicators of students’ local vs. global views. In line with our hypotheses, differences in gaze behavior between students with a local and global view were determined regardless of their grade level. This robustness across different educational stages underscores the validity of specific eye-tracking measures as reliable indicators for students local vs. global view of data. Our research highlights the potential of eye-tracking for understanding students’ data interpretation approaches in statistics education.

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Publication Details

Journal
Educational Studies in Mathematics
Published
2024-10-05
DOI
https://doi.org/10.1007/s10649-024-10352-2
Citations
1
Primary Topic
Statistics Education and Methodologies
Type
article
Field-Weighted Citation Impact
0.71
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article

Students’ local vs. global views of data distributions: a cross-grade-level analysis using eye-tracking

Markus Vogel, Saskia Schreiter
1 citations
Educational Studies in Mathematics
Statistics Education and Methodologies
0.71
article

Students’ local vs. global views of data distributions: a cross-grade-level analysis using eye-tracking

Markus Vogel, Saskia Schreiter
article en
1 citations

Abstract

Abstract The ability to interpret and compare data distributions is an important educational goal. Inherent in the statistical concept of distribution is the need to focus not only on individual data points or small groups of data points (so-called local view), but to perceive a distribution as a whole, allowing to recognize global features such as center, spread, and shape (so-called global view). However, the latter is challenging for students to acquire. This study, involving 68 students in grades 4, 6, and 8, had two main objectives. First, we aimed to examine the potential impact of grade level on how students perceive and compare distributions presented in dot plots. Despite variations in specific pre-knowledge, our findings showed no significant grade-related differences in students’ gaze behavior or their ability to process global features when comparing distributions. This finding suggests that there is no significant developmental trend across grade levels regarding students’ capacity to perceive distributions globally, a critical aim in statistics education. Our second objective was to extend the findings of our previous work regarding the identification of specific eye-tracking measures as indicators of students’ local vs. global views. In line with our hypotheses, differences in gaze behavior between students with a local and global view were determined regardless of their grade level. This robustness across different educational stages underscores the validity of specific eye-tracking measures as reliable indicators for students local vs. global view of data. Our research highlights the potential of eye-tracking for understanding students’ data interpretation approaches in statistics education.

Educational Studies in MathematicsVol. 119(1)
Heidelberg University (DE), Heidelberg University of Education (DE), University of Design Schwäbisch Gmünd (DE)
Quality Education
Openalex Percentile: Top 26%
Statistics Education and Methodologies
0.71
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