How the poor get richer: Signaling guides attention and fosters learning from text‐graph combinations for students with low, but not high prior knowledge

Abstract

In multimedia learning, graphs are seen as just one specific instance of pictorial representations requiring the same cognitive processes as realistic depictions. Accordingly, learning from text‐graph combinations should also benefit from the same instructional support such as signaling of text‐picture correspondences depending on learners' prior knowledge. We investigated whether this expertise reversal of the signaling effect could be replicated for text‐graph combinations. Students (N = 101) with different prior knowledge levels learned with text‐graph combinations that were either enhanced with signals or not. Results indicate an expertise reversal effect on learning outcomes. A moderated mediation analysis of students' visual attention showed that this pattern could be explained by the fact that students with low prior knowledge (LPK) fixated the graph information earlier, whereas high prior knowledge students fixated the graph later when signals were present. Our results suggest that instructional support should be adapted to students' prior knowledge.

Dynamic signals in instructional videos support students to navigate through complex representations: An eye‐tracking study

“…Hence, our results underscore the importance of coordinating which features of the representations are relevant and when, in order to follow the explanation (Mayer & Fiorella, 2014). reversal effect; see, e.g., Richter et al, 2021;Richter & Scheiter, 2019) or how visual expertise supported through signals develops over time (see, e.g., Eder et al, 2021). However, for wide-ranging conclusions, it is crucial to replicate our findings in larger samples, with different materials, and in other areas of STEM education that also use complex representations (e.g., physics or mathematics).…”

“…Future research should also directly investigate the role of sequencing effects in terms of fading‐out the visual support by signals over larger periods of time when learners become more advanced in their understanding of the task and the described processes. It might also be relevant to investigate if signals could become distracting with advanced expertise (i.e., expertise reversal effect; see, e.g., Richter et al, 2021; Richter & Scheiter, 2019) or how visual expertise supported through signals develops over time (see, e.g., Eder et al, 2021). However, for wide‐ranging conclusions, it is crucial to replicate our findings in larger samples, with different materials, and in other areas of STEM education that also use complex representations (e.g., physics or mathematics).…”

“…Eye‐tracking recordings offer direct and objective data based on visual attention that help to better understand the processing of multimedia materials (Alemdag & Cagiltay, 2018; Hyönä, 2010; Lindner et al, 2017; Scheiter & van Gog, 2009). Signaling studies that implement eye‐tracking measures provide evidence that students actually allocate more attention to the signaled parts of the learning material (Groen & Noyes, 2010; Jamet, 2014; Ouwehand et al, 2015; Ozcelik et al, 2010; Ponce & Mayer, 2014; Richter et al, 2021; Wang et al, 2020). Jamet (2014) reported that dynamic signals in instructional videos improved learning outcomes and increased the time learners spent fixating on relevant features of the material.…”

Does active or passive signaling support integration of text and graphs?

“…One may wonder whether the missing replication is related to the usage of graphs rather than cause‐effect diagrams or realistic depictions as learning material. Acarturk et al (2008) found that signals aimed at supporting text‐picture‐integration even hampered learning when applied to graphs; in contrast, (Richter et al, 2021) found a positive effect of multimedia integration signals for low prior knowledge learners also in the case of text‐graph combinations. To the best of our knowledge, these are the only two studies that have investigated the effects of providing signals to support integration of text and graphs so far.…”

“…The material in economics was based on material used in a previous study (Richter et al, 2021) but slightly revised to better fit the aims of this study; the biology material was newly developed for this study. Both materials were reviewed by experts in the relevant fields to ensure not only technical correctness but also to guarantee that the signals really highlighted the most relevant information.…”