Metaphorical graphics aid learning and memory

Kendeou

2016

Discourse Processes

Self Cite

Refutation texts have been shown to be effective at promoting knowledge revision. It has been suggested that refutation texts are most effective when the misconception and the correct information are co-activated and integrated with causal networks that support the correct information. We explored two augmentations to a refutation text that might enhance the possibility of co-activation, integration, and thus revision: analogies and graphics. Participants (122 college students) were randomly assigned to read one of four experimental texts (refutation text, refutation text þ graphic, refutation text þ analogy, or refutation text þ graphic þ analogy). Results showed that refutation text þ analogy and refutation text þ graphic þ analogy were the most successful in promoting revision. Implications for theory and practice are discussed.

Section: Graphics and Textmentioning

confidence: 99%

Augmenting the Refutation Text Effect with Analogies and Graphics

Danielson

Kendeou

2016

Discourse Processes

Self Cite

“…Second, the relative coherence between the two referents should explain why some graphics fail to show the learning gains intended. Here, we echo the argument of Danielson et al (2015)-when researchers make these connections explicit a priori, we can move the field of text-graphic processing forward. We now turn to a more detailed explanation of the four types of relational reasoning as they relate to text-graphic processing.…”

Section: Processing Texts and Graphicsmentioning

confidence: 61%

“…Assuming that a reader is always attempting to draw a relation between the text and graphics as they construct a mental model (Danielson et al 2015), we expect that adopting a relational reasoning perspective may provide two unique advantages to text-graphic processing research. First, if learners are always processing the text-graphic pair in some fashion, then their ability to reconcile these two referents should influence their ability to create a strong mental model of the content.…”

Section: Processing Texts and Graphicsmentioning

confidence: 99%

“…Graphical metaphors have been used to highlight concepts in health (Houts et al 2006), math (Sab et al 2011), chemistry (Stroud and Schwartz 2010;Thomas and McRobbie 2001), and astronomy (Mason et al 2016). While many studies of this kind rely on either critical thinking measures (Danielson et al 2015) or spatial reasoning measures (Mason et al 2016) as proxies for analogical or graphical reasoning (respectively), we suggest that including formal measures of relational reasoning may provide a more nuanced understanding of how learners are interacting with text-graphic pairs, especially if the connections they are attempting to forge are analogical in nature.…”

Section: Analogiesmentioning

confidence: 99%

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A Relational Reasoning Approach to Text-Graphic Processing

Danielson

2016

Educ Psychol Rev

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We propose that research on text-graphic processing could be strengthened by the inclusion of relational reasoning perspectives. We briefly outline four aspects of relational reasoning: analogies, anomalies, antinomies, and antitheses. Next, we illustrate how textgraphic researchers have been conducting research aligned with aspects of relational reasoning, although not deliberately. We call for future research on intentionally designed textgraphic pairings that should be empirically tested for their ability to support relational reasoning. Finally, we argue that relational reasoning may help explain some of the mixed results and unintended outcomes that often appear in the text-graphic research literature.Researchers have developed rich models to account for both text processing (Kintsch 1992;McNamara et al. 1996) and graphic processing (Ainsworth 2006; Ainsworth and Burcham 2007; Hegarty 2011) in isolation. Yet, when text and graphics are combined, learners tend to infer very different meanings than when these representations are presented independently (Hagan 2007). Often, the combination of a text with a graphic is more than just the sum of the two parts. This is because when combined, text and graphics can communicate relationships among or between the informational representations (Hegarty 2011;McCabe and Castel 2008). In other words, text and graphics, when presented together, are inherently relational.In this article, we briefly review the extant text-graphic research as it relates to four aspects of relational reasoning: analogies, anomalies, antinomies, and antitheses. Next, we present a number of examples that draw upon these four aspects of relational reasoning as they relate to learning with texts and graphics. We go on to suggest that viewing text-graphic processing as an exercise in relational reasoning may help explain a number of inconsistent results that have historically hampered research in this area. Finally, we conclude with Educ Psychol Rev

“…The use of "refutation texts"-texts that describe common misconceptions and then refute those misconceptions with evidence-has met with some success in supporting students to overcome misconceptions about various scientific topics that are noncontroversial [22] and controversial [23][24][25]. Refutation texts support undergraduate students in overcoming misconceptions about climate change [25] and are even more successful when paired with graphics and analogies that bridge prior knowledge with information presented in text [25,26]. However, text descriptions do not solve the challenge of visualizing the greenhouse effect.…”

Section: Current Pedagogical Approaches To the Greenhouse Effectmentioning

confidence: 99%

Visualizing the Greenhouse Effect: Restructuring Mental Models of Climate Change Through a Guided Online Simulation

Thacker

2019

Education Sciences

The purpose of this design based research study was to better understand and build from students’ perceptual experiences of visual representations of the greenhouse effect. Twenty undergraduate students were interviewed as they engaged with an online visualization for the learning of the greenhouse effect. We found that, even though all students agreed that climate change is happening, a majority initially held a misconception about how it works. Upon engaging with the visualization, students made perceptual inferences and formulated causal rules that culminated in an improved description of how climate change works. This trajectory was supported with prompts from the interviewer to make predictions, observe specific interactions in the visualization and revise their causal inferences based on these observations. A case study is presented to illustrate a typical learning trajectory.