Exploring Differences Among Student Populations During Climate Graph Reading Tasks: An Eye Tracking Study

Abstract

Communicating climate information is challenging due to the interdisciplinary nature of the topic along with compounding cognitive and affective learning challenges. Graphs are a common representation used by scientists to communicate evidence of climate change. However, it is important to identify how and why individuals on the continuum of expertise navigate graphical data differently as this has implications for effective communication of this information. We collected and analyzed eye-tracking metrics of geoscience graduate students and novice undergraduate students while viewing graphs displaying climate information. Our findings indicate that during fact-extraction tasks, novice undergraduates focus proportionally more attention on the question, title and axes graph elements, whereas geoscience graduate students spend proportionally more time viewing and interpreting data. This same finding was enhanced during extrapolation tasks. Undergraduate novices were also more likely to describe general trends, while graduate students identified more specific patterns. Undergraduates who performed high on the pre-test measuring graphing skill, viewed graphs more similar to graduate students than their peers who performed lower on the pre-test.

“Seeing” Data Like an Expert: An Eye-Tracking Study Using Graphical Data Representations

“…On the other hand, as experience level decreased, participants were more likely to focus their attention and rely on cues (provided answer options and question prompts) in an effort to complete the graph-based tasks than more expert participants. Our data are consistent with earlier expert–novice ET studies 4 focusing on discipline-specific or specialized graph data (Atkins, 2016; Topczewski et al. , 2016) as well as findings reported by Angra and Gardner (2017), who noted in their research on graph construction that experts are more likely to take the time to understand the data before using them.…”

“…Substantial differences were noted between the two groups: the introductory students had a more sporadic gaze pattern distributed across the graph, whereas the more experienced students focused on specific areas of interest in making sense of the data. Similarly, Atkins (2016) found notable variation in the search and fixation patterns of undergraduates and science experts (geoscience graduate students) when faced with five climate change graphs from the U.S. Environmental Protection Agency. In particular, undergraduates focused more attention on graph elements that helped them read the data (e.g., question text, title), but graduate students focused on information (e.g., data trends, legends, axis labels) that helped them better understand the data being presented.…”

“…Our goal is not to determine what skills experts possess and novices lack, but to see what differences may exist as a function of scientific training that can be used to inform the development of graph literacy. Based on prior data-visualization literature (e.g., Atkins, 2016; Angra and Gardner, 2016; Stofer, 2016; Topczewski et al. , 2016), it is anticipated that variation will exist between experts and novices in how they direct their attention during task completion when seeking meaningful information and that this knowledge might provide insight to help guide students in transitioning from novice to expert-like performance or “learning how to see” like experts (NRC, 2000, p. 36)…”

Students’ Ability to Work With Graphs in Physics Studies Related to Three Typical Student Groups

“…The results showed that each type of graph was suitable for different types of tasks. Atkins and McNeal (2018) conducted an eye-tracking study exploring graphs in the context of climate change. Van der Linden et al (2014) stated that graphs are the most effective way of communicating the climate consensus of researchers.…”

Users’ Cognitive Load: A Key Aspect to Successfully Communicate Visual Climate Information

“…Some examples are the use of cognitive psychology methods to help make information provided by IPCC graphs more accessible to expert and non-expert audiences (Harold et al 2016) and improve users' task performance (Hegarty et al 2010). Differences in the interpretation of climate graphs between experienced and non-experienced users have been explored elsewhere (Atkins and Mcneal 2018;Gerst et al 2020), both for climate change variables and for temperature and precipitation outlooks.…”