Color is a perceptual stimulus that has a significant impact on improving human emotion and memory. Studies have revealed that colored multimedia learning materials (MLMs) have a positive effect on learner’s emotion and learning where it was assessed by subjective/objective measurements. This study aimed to quantitatively assess the influence of colored MLMs on emotion, cognitive processes during learning, and long-term memory (LTM) retention using electroencephalography (EEG). The dataset consisted of 45 healthy participants, and MLMs were designed in colored or achromatic illustrations to elicit emotion and that to assess its impact on LTM retention after 30-min and 1-month delay. The EEG signal analysis was first started to estimate the effective connectivity network (ECN) using the phase slope index and expand it to characterize the ECN pattern using graph theoretical analysis. EEG results showed that colored MLMs had influences on theta and alpha networks, including (1) an increased frontal-parietal connectivity (top–down processing), (2) a larger number of brain hubs, (3) a lower clustering coefficient, and (4) a higher local efficiency, indicating that color influences information processing in the brain, as reflected by ECN, together with a significant improvement in learner’s emotion and memory performance. This is evidenced by a more positive emotional valence and higher recall accuracy for groups who learned with colored MLMs than that of achromatic MLMs. In conclusion, this paper demonstrated how the EEG ECN parameters could help quantify the influences of colored MLMs on emotion and cognitive processes during learning.

Teaching adult learners is challenging because the characteristics of adult learners and their expectations are different from children/early adolescence. Recent advances in digital technology offer various opportunities that are particularly useful in fostering adult learning by transforming traditional "live" classroom-based into "virtual." This chapter aims to explore how the digital technologies affect the way the brain learns and memorizes, including cognitive, emotional, and behavioral dimensions to promote personal and professional development. First, this chapter presents the application of digital technologies that support and engage adult learners in enhancing knowledge acquisition and retention, discusses the specific engagement techniques for adult, along with the research on multimedia learning. This chapter also covered neuroscience studies related to brain-based learning and strategies. The opportunities and challenges of the use of digital technology and multimedia platform to be effective learning tools for academic context and lifelong learning are also presented.

No abstract

Color has the exceptional ability to capture visual attention and is also capable of enhancing positive emotions, leading to a significant impact on human learning and memory. However, the influence of color on the spatiotemporal dynamics of brain connectivity networks during learning has remained unexplored. This study aimed to propose an analytical approach based on time-frequency decomposition and microstate analysis to capture temporal variations in dynamic directed connectivity networks using electroencephalography (EEG) signals for investigating the influence of visual color on network dynamics of the brain during a learning task. Wavelet transform and phase slope index were employed to estimate the dynamic directed connectivity networks of EEG signals. The estimated dynamic directed connectivity networks were then characterized using graph theoretical analysis. The recurring patterns of dynamic directed connectivity networks were classified using cluster analysis before the temporal dynamics of directed connectivity networks were quantified using microstate analysis. Forty-five healthy participants participated in the experiment, which included memorizing learning materials presented in three different colors (achromatic, cool, and warm). The results revealed that the dynamic directed connectivity networks could be grouped into several quasi-stable states and the presence of common and unique brain states repetitive across frequency bands under individual conditions. A joint analysis of all conditions revealed that the temporal dynamics (coverage, mean duration, and state transition probability) differed significantly between the achromatic and colored conditions. Few dynamic brain states were shared between conditions and tended to remain in particular brain states for a longer duration in specific frequency bands. Our observations provided the first evidence of temporal dynamics of frequency-specific directed connectivity networks in the brain during multimedia learning tasks, that is, increased coverage of top-down interactions in the θ and α bands and switching between top-down and bottom-up interactions (information flow from anterior to posterior regions and vice versa) in the α band, in colored conditions compared to that of achromatic conditions. Therefore, these results suggest that several frequency-specific directed connectivity networks cooperate during knowledge acquisition and may change over time (from one state to another). The proposed framework captures the temporal dynamics of directed connectivity networks, and provides implications for monitoring and assessing emotional and cognitive processes in various contexts.INDEX TERMS Complex Morlet wavelet, directionality index, dynamic directed connectivity network, electroencephalography, k-means clustering, microstate analysis, phase slope index.The associate editor coordinating the review of this manuscript and approving it for publication was Ludovico Minati .