This chapter summarizes research and theory concerned with the effect of learner motivation and emotional states on multimedia learning. It describes trends and issues in the current approaches, identifies relevant theoretical models, and assesses the importance of motivation (including interest, intrinsic-extrinsic motivation, goal orientation, and self-efficacy) and affect (including positive and negative affective states) as mediators and moderators of the effects of multimedia learning on cognitive outcomes. The reviewed empirical findings indicate the strong influence of multimedia learning environments on learner motivation and affect.

This chapter summarizes research and theory concerned with the effects of learner expertise (prior knowledge) on multimedia learning. According to the expertise reversal principle, in many situations, design principles that are effective for novice learners may not be effective or even hinder learning for more knowledgeable learners. The main theoretical issue associated with this principle concerns the integration in working memory of instructional information with knowledge structures held in long-term memory. The major instructional implication is the need to tailor instructional formats and procedures to changing levels of expertise. The chapter also suggests future research directions.

Extraneous processing occurs when suboptimal instructional design causes learners to engage in cognitive processing irrelevant to the instructional goal. This chapter explores five principles for reducing extraneous processing in multimedia learning: coherence, signaling, redundancy, spatial contiguity, and temporal contiguity. The coherence principle is that people learn better when extraneous information is excluded from multimedia lessons. The signaling principle is that people learn better when cues are added to highlight the organization of the essential information. The redundancy principle is that people learn better when multimedia lessons include graphics and spoken text rather than graphics, spoken text, and printed text. The spatial contiguity principle is that people learn better when words and corresponding graphics are physically integrated rather than separated. The temporal contiguity principle is that people learn better when words and corresponding graphics are presented simultaneously rather than sequentially.

Video is one of the most popular ways to deliver instruction, yet researchers are only beginning to understand how to design effective video lessons. This chapter explores: (a) how to present the learning material (multimedia design), (b) how to present the instructor (instructor presence), and (c) how to foster student engagement (generative activity). The empirical evidence suggests videos are most effective when they adhere to basic multimedia design principles (e.g., coherence, redundancy, or segmenting), when they are sensitive to the benefits and boundaries of specific instructor presence features (e.g., the instructor’s face, eyes, and hands), and when they explicitly prompt learners to retrieve and make sense of the learning material (e.g., practice testing or self-explaining). Future research is needed to specify boundary conditions and apply video design principles to more authentic educational contexts.

Emotional Design is the deliberate use of design elements of learning materials to induce an emotional state in the learner that leads to increased learning outcomes. This emotion induction should not add significantly to the cognitive demands placed on the learner, which is best achieved by using existing design elements rather than adding new elements. In this chapter, we summarize research on the effect of emotion-inducing features of a multimedia lesson on memory, cognition, and learning, provide empirical evidence for the emotional design principle, and discuss design features that have been shown to induce emotion. We will also differentiate emotional design from other emotion induction methods that increase processing demands on the learner by adding seductive details or that take place outside of the learning materials in the form of priming.

Cognitive Tutors are effective AI-based learning environments. The following statement summarizes three core instructional features from past summaries of deliberate practice (shown in italics) along with three elaborations (shown in bold): Good learning-by-doing instruction requires repeated practice on well-tailored tasks in varied contexts with explanatory feedback and as-needed instruction. This chapter describes these six learning-by-doing principles and how they are achieved in Cognitive Tutors. We correct some key misconceptions about cognitive tutors, including that knowledge component (KC) decomposition does not exclude, but includes conceptual connections, teachers are not replaced but valued, and up-front-telling is not the instructional focus whereas learning-by-doing guidance is. We also point to a need for more experimentation on the benefits of as-needed versus up-front instruction, better integration of supports for enhancing student motivation, and better pathways for teachers to participate in co-design (during the inevitable need for Learning Engineering beyond Learning Science) and customization.

This chapter discusses the drawing principle in multimedia learning. It proposes that asking students to create drawings while reading text causes generative processing that leads to better learning outcomes. In drawing, students have to translate the verbal text information into a picture that represents spatial relationships among functional elements referred to in the text. Asking students to draw a picture of the text content as they read encourages them to actively engage in deep cognitive and metacognitive processing and thus fosters deep understanding of the material to be learned. The drawing principle has been supported by many studies, especially when students engage in drawing using paper and pencil. An important logistical issue is to create a form of drawing activity that minimizes extraneous cognitive processing by providing appropriate support for drawing.

Multimedia learning from multiple documents involves the construction of new knowledge, beliefs, or opinions from more than a single source of information. First, we introduce the specific discourse processes that come into play when considering multiple-source documents as opposed to single-source texts or multimedia documents. We focus on the definition and role of sources, and on the semantic and rhetorical relationships at an intertextual level. Then we examine learning from multiple documents from a cognitive standpoint. We define two core principles: the sourcing principle and the multiple document integration principle. Finally, we examine some implications of these principles for a general theory of text-based learning and for instructional practice throughout the K12 and higher education curricula.

The multimedia principle is that people learn better from words and pictures than from words alone. For example, a multimedia lesson consists of an animation depicting the steps in lightning formation along with concurrent narration describing the steps in the lightning formation, whereas a single-medium lesson consists of narration alone. Based on research carried out by myself and my colleagues, in 13 out of 13 tests, learners who received text and illustrations or narration and animation (dual representation group) performed better on transfer tests than did learners who received text alone or narration alone (single representation group), with a median effect size of d = 1.35.

This chapter outlines the tight connections between multimedia learning and worked examples in that worked examples can make multimedia learning more effective, and applying instructional multimedia guidelines makes learning from worked examples more effective. The to-be-expected effect sizes when using worked examples are discussed, and the theoretical rationale of the worked-example effect is explained (e.g., example study replaces unproductive learning by problem-solving). In addition, a set of instructional guidelines for optimizing learning from worked examples is derived from findings on factors that moderate the worked-example effect, such as fading worked steps or including incorrectly worked examples. Furthermore, the theoretical implications of the general pattern of findings on worked examples are discussed (e.g., with respect to the role of generative learning or extraneous processing). Finally, important questions to be addressed in further research are proposed.

When dealing with instructional information, working memory can be divided into auditory and visual processors. The capacity limits of each processor are a major impediment when students are required to learn new material. Nevertheless, there is one strategy that can effectively expand working memory capacity by using the partially independent status of the auditory and visual processors. Under specific and well-defined conditions, presenting some information in visual mode and other information in auditory mode can increase effective working memory capacity and so reduce the effects of cognitive overload. This effect is called the instructional modality effect or modality principle. It is an instructional principle that can substantially increase learning. This chapter discusses the theory and data that underpin the principle and the instructional implications that flow from the principle.

According to the embodiment principle, students learn better when they engage in task-relevant sensorimotor experiences during learning, such as gesturing or manipulating objects. Students may benefit from enacting movements themselves and/or observing them performed by others. Embodied instruction supports learning by offloading thinking to the physical world (i.e., reduced cognitive load) and by drawing analogies between abstract concepts and meaningful actions (i.e., increased generative processing). Prior research has identified a wide range of promising embodiment methods – using gestures to represent math concepts or to trace important elements of diagrams; manipulating concrete (or virtual) objects to understand stories, math concepts, molecular structures, or physics principles; and designing visualizations that present lessons from the learner’s perspective.

This chapter describes diverse research methods to study multimedia learning. In light of the wide range of methods to study learning with multimedia and to stay in line with the focus of this Handbook, I target experimental research where a variation of multimedia design is tested against (at least) a control design. Thus, I omit case studies, technical developments, design-based research, etc. Moreover, I only take into consideration research in which the main dependent measure was some sort of learning outcome, such as performance, retention, or transfer. In addition, I look into variables mediating the way to this learning outcome. In this way I come to the following structuring of measures: tests that a priori capture characteristics of learners, measures that online trace the process of learning, self-reports of how learners experienced this learning, and learning outcome measures. For each type of measure, I provide a description and concrete examples of their use in multimedia research. Lastly, I explore thus far, less-frequently used methods in multimedia research, that have, however, the potential to shed new light on multimedia learning.

Cognitive and metacognitive strategies are key to successful learning with multimedia; however, research shows that learners rarely use these strategies effectively and consequently fail to develop a deep understanding of complex topics and domains. Dynamically and accurately monitoring and regulating one’s own cognitive and metacognitive strategies is necessary to be a successful learner but demands an enormous amount of effort. In this chapter, we (1) define metacognitive strategies during multimedia learning; (2) review recent empirical literature on metacognitive strategies during multimedia learning; (3) present a new model of multimedia learning ; (4) provide recommendations for augmenting contemporary cognitive theories of multimedia learning to account for metacognition; (5) propose empirically-based principles for designing multimedia environments aimed at fostering metacognitive strategies; and finally (6) highlight directions for future research.