Towards a framework for attention cueing in instructional animations: Guidelines for research and design

This paper examines the transferability of successful cueing approaches from text and static visualization research to animations. Theories of visual attention and learning as well as empirical evidence for the instructional effectiveness of attention cueing are reviewed and, based on Mayer’s theory of multimedia learning, a framework was developed for classifying three functions for cueing: (1) selection—cues guide attention to specific locations, (2) organization—cues emphasize structure, and (3) integration—cues explicate relations between and within elements. The framework was used to structure the discussion of studies on cueing in animations. It is concluded that attentional cues may facilitate the selection of information in animations and sometimes improve learning, whereas organizational and relational cueing requires more consideration on how to enhance understanding. Consequently, it is suggested to develop cues that work in animations rather than borrowing effective cues from static representations. Guidelines for future research on attention cueing in animations are presented

The Effects of Diagrams and Relational Complexity on User Performance in Conditional Probability Problems in a Non-Learning Context

Many disciplines in everyday life depend on improved performance in conditional probability problems. Most adults struggle with conditional probability problems and several prior studies have shown participant accuracy is less than 50%. This study examined user performance when aided with computer-generated Venn and Euler type diagrams in a non-learning context. Despite the prevalence of research into diagrams and extensive research into conditional probability problem solving, this study is one of the only studies to apply theories of working memory to predict user performance in conditional probability problems with diagrams. Following relational complexity theory, this study manipulated problem complexity in computer generated diagrams and text-only displays to improve user performance and perceptions of satisfaction. Partially consistent with the study hypotheses, complex visuals outperformed complex text-only displays and simple text-only displays outperformed complex text-only displays. However, a significant interaction between users’ spatial ability and the use of diagram displays led to a degradation of low-spatial user performance in the diagram displays when compared to high spatial users. Participants with less spatial ability were significantly impaired in their ability to solve conditional probability problems when aided by a diagram

Cognitive and psychological science insights to improve climate change data visualization

Visualization of climate data plays an integral role in the communication of climate change findings to both expert and non-expert audiences. The cognitive and psychological sciences can provide valuable insights into how to improve visualization of climate data based on knowledge of how the human brain processes visual and linguistic information. We review four key research areas to demonstrate their potential to make data more accessible to diverse audiences: directing visual attention, visual complexity, making inferences from visuals, and the mapping between visuals and language. We present evidence-informed guidelines to help climate scientists increase the accessibility of graphics to non-experts, and illustrate how the guidelines can work in practice in the context of Intergovernmental Panel on Climate Change graphics

The 'physics of diagrams' : revealing the scientific basis of graphical representation design

Data is omnipresent in the modern, digital world and a significant number of people need to make sense of data as part of their everyday social and professional life. Therefore, together with the rise of data, the design of graphical representations has gained importance and attention. Yet, although a large body of procedural knowledge about effective visualization exists, the quality of representations is often reported to be poor, proposedly because these guidelines are scattered, unstructured and sometimes perceived as contradictive. Therefore, this paper describes a literature research addressing these problems. The research resulted in the collection and structuring of 81 guidelines and 34 underlying propositions, as well as in the derivation of 7 foundational principles about graphical representation design, called the "Physics of Diagrams", which are illustrated with concrete, practical examples throughout the paper

Are Pictures Always Worth a Thousand Words? Interactions Between Reader, Text, and Diagrams in Multimodal Comprehension

This study investigates the influence of diagrams and spatial layout on interactive effects of text cohesion, domain knowledge, and reading skill on the comprehension of multimodal science text. College undergraduates read either a low or high-cohesion text about cell mitosis that was or was not augmented with diagrams, and then answered text-based and bridging-inference comprehension questions. Results showed overall effects of diagrams and cohesion, but these effects largely depended on an integrated configuration as well as on ability level. Low-knowledge and less-skilled readers benefited from cohesion when the text did not contain diagrams, and only benefited from diagrams when presented with a low-cohesion text in an integrated configuration. In contrast, high-knowledge and skilled readers benefited from high-cohesion text accompanied by diagrams, but only skilled readers benefited independently of configuration. Results offer support for a linear contiguity effect and a text cohesion effect as either new multimedia design principles or as extensions of existing principles

A systematic characterization of cognitive techniques for learning from textual and pictorial representations

Pictorial representations can play a pivotal role in both printed and digital learning material. Although there has been extensive research on cognitive techniques and strategies for learning from text, the same cannot be said for static and dynamic pictorial representations. In this paper we propose a systematic characterization of cognitive learning techniques that is founded on both theoretical and empirical research. The characterization relates the learning techniques to classes of cognitive processes as well as to textual and pictorial representations. We show how successful strategies for learning from both plain text and illustrated text are covered by the characterization. We also exemplify how the construction of new strategies for pictorial representations can be informed by the characterization

Learning by Seeing by Doing: Arithmetic Word Problems

Learning by doing in pursuit of real-world goals has received much attention from education researchers but has been unevenly supported by mathematics education software at the elementary level, particularly as it involves arithmetic word problems. In this article, we give examples of doing-oriented tools that might promote children\u27s ability to see significant abstract structures in mathematical situations. The reflection necessary for such seeing is motivated by activities and contexts that emphasize affective and social aspects. Natural language, as a representation already familiar to children, is key in these activities, both as a means of mathematical expression and as a link between situations and various abstract representations. These tools support children\u27s ownership of a mathematical problem and its expression; remote sharing of problems and data; software interpretation of children\u27s own word problems; play with dynamically linked representations with attention to children\u27s prior connections; and systematic problem variation based on empirically determined level of difficulty