Realism as a retrieval cue: Evidence for concreteness‐specific effects of realistic, schematic, and verbal components of visualizations on learning and testing

Abstract

Previous research in technology‐enhanced learning suggests that realism in visualizations can overwhelm learners and lower their learning performance. However, some studies offer evidence that realism may be helpful in learning tests that require detailed visual knowledge. A potential mechanism may be that realistic details act as retrieval cues (i.e., visual cues that facilitate retrieval during testing). In order to assess the impact of realism in learning and testing, we conducted an experiment (N = 40) using realistic and schematic renderings generated for this study. Realism was varied as a between‐subjects factor while participants completed both a schematic and realistic retention test. As hypothesized, a realistic test visualization primarily benefits those who had learned using a realistic rather than a schematic visualization. In addition, the realistic test led to higher retention scores regardless of the realism level of the learning materials. A second experiment (n = 50) was conducted to assess whether schematic visualizations can be made more learner‐friendly by including verbal descriptions that enhance the less detailed visualizations with additional cues. The experiment revealed that learning with schematic visualizations can be fostered using verbal descriptions for a multiple‐choice retention test, but at the cost of lower scores in an image‐based retention test. Both studies suggest that matching the realism and concreteness in the learning and testing stages lead to the best performance. Our results have implications for the design of a range of technology‐enhanced learning contexts such as virtual reality education.

Understanding Cognitive Load in Digital and Online Learning: a New Perspective on Extraneous Cognitive Load

“…As in the design of assessments for interactive learning media described in an earlier section, this result further underlines that the specific design of a test can greatly affect performance. In line with this assumption, the benefits of realism were found to be best detectable with a test that is aimed at the advantages of realistic details, for example, visual retention tests (Skulmowski & Rey, 2021). It has been argued that the usefulness of realistic details in digital learning is tied to the objective of a test (e.g., Nebel et al, 2020), thereby deciding whether these details are relevant or irrelevant for the task.…”

“…While the explanation of positive effects of realism despite an increase in extraneous load could potentially be due to a low level of disfluency that triggers more effortful processing, other explanations that assume a higher interest being generated through realistic visualizations could also be true (e.g., Goldstone & Son, 2005). Another study that found a specific advantage of realistic details over schematic visualizations during testing concerning performance on a retention test revealed the concreteness of learning and testing materials should be matched in order to foster learning (Skulmowski & Rey, 2021). As in the design of assessments for interactive learning media described in an earlier section, this result further underlines that the specific design of a test can greatly affect performance.…”

Visualizing pathogens: Disfluent shapes of pathogens increase their perceived complexity and danger while realism and disfluency boost the credibility of visualizations

“…Further consideration should be given to the potential of realistic visualizations to be more memorable than more abstract representations (Skulmowski & Rey, 2020a). In case of future pandemics or smaller outbreaks of pathogenic diseases, more detailed representations of the (usually rather amorphous shapes of) pathogens could help the public to distinguish between these different agents of disease.…”

“…A previous study investigating the confidence in visualizations differing in their level of realism resulted in a very large effect of η p 2 = .71 (Zanola et al, 2009). However, we chose to align our power calculation for the smallest effect of interest with sample sizes used in recent research on the cognitive processing of realistic visualizations (e.g., Skulmowski & Rey, 2020a). We planned to continue data collection until at least 40 participants had completed the study based on a power calculation for within‐subject factors using G*Power (Version 3.9.1.2; Faul, Erdfelder, Buchner, & Lang, 2009) with α = .05, power = .80, correlation between measures = .5, and η p 2 = .05.…”

Is a Preference for Realism Really Naive After All? A Cognitive Model of Learning with Realistic Visualizations

“…An often-cited theory arguing against the use of realistic graphics is called naive realism (Smallman & St. John, 2005) and emphasizes that studies found negative effects of realistic visualizations on different types of performance measures. Several studies have resulted in evidence that abstract visualizations can be more effective in terms of learning than realistic versions (e.g., Menendez et al, 2020;Scheiter et al, 2009), while other authors argue that realistic details can have beneficial effects, such as helping learners to retrieve information (e.g., Skulmowski & Rey, 2021a). Some of the earliest investigations into the effects of realistic visualizations in the context of anatomy learning by Dwyer showed that realism can be detrimental to learning, but also that the performance on visual test types can benefit from viewing more detailed material (e.g., Dwyer, 1969; see Nebel et al, 2020, for a discussion).…”