Influence of Multimedia and Cognitive Strategies in Deep and Surface Verbal Processing: A Verbal-Linguistic Intelligence Perspective

Influence of Multimedia and Cognitive Strategies in Deep and Surface Verbal Processing: A Verbal-Linguistic Intelligence Perspective

Robert Z. Zheng (University of Utah, USA)
DOI: 10.4018/978-1-7998-0249-5.ch009
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The traditional view of linguistic-verbal intelligences focuses on individual linguistic abilities at the levels of phonology, syntax, and semantics. This chapter discusses the individual linguistic abilities from a text-comprehension perspective. The chapter examines the roles of multimedia and cognitive prompts in deep and surface verbal processing. Drawn from research in working memory, multimedia learning, and deep processing, a theoretical framework is proposed to promote learners' deep and surface learning in reading. Evidence from empirical studies are reviewed to support the underlying theoretical assumptions of the framework. The theoretical and practical significance of the theoretical framework is discussed with suggestions for future research.
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Learners learn differently due to their individual differences in terms of age, gender, cognitive abilities, intelligence, interest, and personality traits (Colby, Clayards, & Baum, 2018; Kubat, 2018; Zheng, Flygare, Dahl, & Hoffman, 2009). It is believed that individual intelligence can be significantly influenced by a range of factors related to learning and performance (Cifuentes & Hughey, 1998; Iyer, 2006). Previous research has demonstrated the relationship between intelligence and its associated factors like age, working memory capacity, spatial ability, and processing speed (Salthouse, 2012). It was found that changes in working memory capacity, processing speed, and spatial ability can significantly influence learners’ performance in verbal information processing (Pazzaglia, Toso, & Cacciamani, 2008; Rast, 2011; Smith et al., 2019). Smith et al. (2019) pointed out that due to cognitive impairments caused by the ageing process, older people experience tremendous challenges when learning new skills like browsing the Internet and engaging in online social communication. In additional to age factor, studies have shown that multimedia play an important role in influencing individuals’ cognitive abilities in performances like verbal learning (Pazzaglia et al., 2008; Shadiev, Hwang, Liu, 2018), analytical thinking (Zheng, 2007), and scientific reasoning (Mayer & Anderson, 1992). Given the unique cognitive features in multimedia, Reiser (1994) suggested that educators, trainers, and instructional designers need to take into perspective the relationship between multimedia and cognitive abilities when designing and developing instruction for learners. Despite a growing body of research on multimedia and learning, studies that focus on the relation of age, visual-spatial ability, and multimedia in verbal learning are rare and research in this area is undertheorized. The current chapter therefore seeks to examine the influence of multimedia on cognitive processing ability in verbal learning. By reading the chapter, the readers will be able to:

  • 1.

    Understand the role of multimedia in verbal-linguistic processing,

  • 2.

    Explain the age factor in the design of multimedia for verbal learning, and

  • 3.

    Describe the relationship between working memory capacity and multimedia in verbal learning.

Key Terms in this Chapter

Working Memory: Working memory refers to the temporary storage in human brain. It is characterized by a central executive function which has two sub-systems: phonological loop and visuo-spatial sketchpad.

Redundancy Effect: Redundancy effect in multimedia learning refers to a state of learning caused by improper design in multimedia. With redundant design, unnecessary media elements (visual, or auditory) are added to the multimedia learning which causes additional cognitive processes, therefore additional cognitive resources are needed to handle the process in learning which can impose extra cognitive load on working memory.

Schema: Schema refers an organized body of knowledge in human mind. It can be a mental structure of preconceived ideas and concepts, a framework representing aspects of a domain, or a system of organizing and perceiving new information or procedures. Schema influences learners’ attention and process of new knowledge.

Compensatory Hypothesis: Compensatory hypothesis states the diminishing function of one sensory process (e.g., auditory) may be compensated by adding a second sensory process (e.g., visual).

Deep Learning: Deep learning refers to learning activities that the learner interacts with the content, engages in understanding and reasoning the material, and applies and transfers knowledge to new learning situations.

Executive Function: Executive function refers to the subsystem in working memory which controls and coordinates the information from phonological loop and visuo-spatial sketchpad. The phonological loop stores phonological information and prevents its decay by silently articulating its contents, thereby refreshing the information in a rehearsal loop. The visuo-spatial sketchpad (VSS) is believed to process and manipulate visuo-spatial images

Cognitive Prompts: Cognitive prompts are learning questions placed throughout an educational presentation—be they in person or through multimedia—that aim at activating prior knowledge or focusing on the learners’ attention during learning. Cognitive prompts can support both cognitive processes—including memory retrieval—and metacognitive development in learning.

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