Levels Of Cognitive Load Research Articles

Using the ISO Detection response task to measure the cognitive load of driving four separate vehicles on two distinct highways

The ISO Detection Response Task (DRT) is a standard tool for assessing drivers’ cognitive load and it has primarily been used to measure the cognitive load of completing non-driving tasks and interacting with vehicle systems. In this study we use the DRT to measure the workload of driving four separate vehicles (a 2019 Tesla Model 3, a 2018 Cadillac CT6, a 2018 Volvo XC90, a 2019 Nissan Rogue) in manual mode and on two distinct roadways (US Interstate Highway 15 and 80) in and around Salt Lake City, UT. Results showed that the unique road characteristics of I-80 resulted in higher levels of cognitive load as demonstrated by the slower DRT response times. Likewise, different levels of workload were found across the four vehicles, with higher workload levels found for one of the four vehicles. This study expands the use of the DRT outside its original area of application, and advances it as a tool to assess the cognitive demand induced by varying road and vehicle characteristics.

Supporting content and language integrated learning through computer-based dual concept mapping

Among various approaches to teaching and learning English as a foreign language, content and language integrated learning (CLIL), i.e. learning subject content in a non-native language, has received wide attention. Despite its positive effects on language learning, CLIL poses cognitive challenges to learners. To deal with the challenge, prior studies applied concept maps to visualize knowledge structures to support content learning, but paid inadequate attention to visualizing text structure to support language learning. Some studies mixed knowledge structure and text structure in one concept map, failing to help students distinguish between knowledge structure and text structure. It is important to visualize both knowledge structure and text structure and present them in two parallel concept maps to facilitate CLIL. To this end, this study proposed a computer-based dual concept mapping approach visualizing both knowledge structure and text structure of learning content in two parallel concept maps to support science content and English language integrated learning. This study was conducted with 89 eighth-grade students from two classes, who were randomly assigned to either the experimental or control condition. Students’ achievements in English language and science knowledge were assessed by knowledge tests; their cognitive load was measured through a questionnaire survey. By comparing student performance in the two conditions, the study shows that the experimental group experienced a lower level of cognitive load and achieved better learning outcomes in both science knowledge and language performance. Further, there were more significant differences between experimental and control groups for low and medium achievers in English language than for high achievers, indicating that the proposed approach was more beneficial for the former. The findings provide new insights into the pedagogy and strategy for CLIL, that is, visualizing both knowledge structure and text structure of learning content in two parallel concept maps with the support of concept mapping technology.

The effect of reward expectation on working memory of emotional faces under different levels of cognitive load: an ERP study.

Using event-related potentials (ERPs), this study examined the impact of reward expectations on working memory of emotional faces under different levels of cognitive load in a task combining the N-back paradigm and the reward expectation paradigm. The experiment involved presenting high- or low-reward cues followed by an N-back task for emotional faces with different loads. The accuracy results showed that under a high task load, both reward and emotion effects were significantly observed. However, these effects disappeared under a low task load. Analysis of the ERP data revealed that the early P2 and VPP components exhibited greater responses to fearful faces than to neutral faces. In the later stages, the P3 and LPP components showed greater reactions to high rewards than to low rewards. Additionally, the P2 component was found to be modulated by task load in relation to rewards, the EPN component demonstrated task load modulation with respect to emotions, and the N170 component showed an interaction effect between rewards and emotions. These findings imply that load regulates the reward effect and the emotional superiority effect in the process of working memory for emotional faces. In the cognitive processing of working memory, motivation and emotion jointly influence processing. Emotional factors have a greater impact in the early stage of processing, while motivation factors have a greater impact in the late stage of processing.

A review of driver cognitive load detection using ECG signals

Detection of the driver’s cognitive load while driving is crucial to prevent the likelihood of traffic collisions and improve road safety. A physiological-based approach has gained significant attention due to its potential to provide reliable indicators for the driver’s state. The physiological signal of electrocardiography (ECG) is considered a promising biomarker for detecting the driver’s cognitive load. Despite the interest in cognitive load detection using ECG, an attempt has yet to be made to identify the relationship between ECG measures and driver cognitive load level. This paper seeks to investigate this gap in cognitive load literature. The finding demonstrates that further research is still needed on ECG-based driver’s cognitive load detection by examining and analyzing the limitations of research challenges and earlier studies. This study also addresses the performance and problems faced in the detection of a driver’s cognitive load considering ECG. With a better understanding of how cognitive load affects ECG measures, both researchers and companies can design more effective driver’s state detection systems.

Emotion Detection with AI: Development of Learning Media for Evaluation of Cognitive Load of Prospective Teacher in Genetics Lectures

This research aims to develop learning media by integrating artificial intelligence (AI) that is able to detect the emotions of prospective teacher during genetics lectures. Using AI technology, this system can evaluate the cognitive load of students in real-time through facial expression analysis. The method used involves collecting data from lecture sessions, which are then analyzed using machine learning algorithms to identify cognitive load levels. The results of the study show that this learning media is able to identify students' emotions. This learning media is equipped with accurate emotion detection features, interactive learning materials, and an informative dashboard to monitor student learning progress. The implementation of this technology is expected to improve the quality of learning and help students achieve a better understanding of genetics courses.

Investigation of the neural correlation with task performance and its effect on cognitive load level classification.

Electroencephalogram (EEG)-based cognitive load assessment is now an important assignment in psychological research. This type of research work is conducted by providing some mental task to the participants and their responses are counted through their EEG signal. In general assumption, it is considered that during different tasks, the cognitive workload is increased. This paper has investigated this specific idea and showed that the conventional hypothesis is not correct always. This paper showed that cognitive load can be varied according to the performance of the participants. In this paper, EEG data of 36 participants are taken against their resting and task (mental arithmetic) conditions. The features of the signal were extracted using the empirical mode decomposition (EMD) method and classified using the support vector machine (SVM) model. Based on the classification accuracy, some hypotheses are built upon the impact of subjects' performance on cognitive load. Based on some statistical consideration and graphical justification, it has been shown how the hypotheses are valid. This result will help to construct the machine learning-based model in predicting the cognitive load assessment more appropriately in a subject-independent approach.

Evaluation of tracheostomy suctioning procedure among nursing and respiratory therapy students: wearable manikin vs. standard manikin.

This study aims to evaluate cognitive load (CL), emotional levels (EL), and stress levels (SL) of students when using a wearable manikin vs. a standard manikin for tracheostomy suctioning (TS). This study was approved by the Institutional Review Board. Subjects were recruited by email. Subjects completed a baseline demographics questionnaire, then they were randomized into two groups: wearable manikin group (WMG) or standard manikin group (SMG). For the WMG, an actor simulated a patient by wearing the device. In phase I, both groups were educated on how to perform TS by video and offered hands-on practice. Then I put through a tracheostomy suctioning clinical simulation and completed a post sim-survey. In phase II, the same survey was repeated after encountering a real patient as part of their clinical rotation. A total of 30 subjects with a mean age 26.0 ± 5.5 years participated. 20 (66.7%) were respiratory care students and 10 (33.3%) were nursing students. In the WMG, the median stress level dropped significantly post phase II compared to post phase I [2(1,4) vs.3(1,5), p = 0.04]. There were no significant changes in median CL, confidence, and satisfaction levels between post phase II and post phase I (p > 0.05). In the SMG, the satisfaction level increased significantly post phase II compared to post phase I [5(4,5) vs.4(2,5), p = 0.004], but there were no significant changes in CL, SL, and confidence levels between post phase I and phase II. There was no significant difference in mean EL scores over time and these changes did not differ by group. Subjects in the WMG showed a higher mean competency score than those in the SMG (85.5 ± 13.6 vs. 78.5 ± 20.8, p = 0.14, Cohen's d = 0.4), yet not significant. Our results showed that the WMG is beneficial in helping bridge the gap of learning TS from the sim setting to the real-world clinical setting. More studies with higher sample size and use of other CL scales that assesses the different types of CL are needed to validate our findings.

The effects of increased mental workload of air traffic controllers on time perception: Behavioral and physiological evidence

Research has shown that timing is modulated by mental workload, making duration judgments a measure of cognitive demand, alongside subjective assessments, and physiological measurements. Yet, it is unclear whether such findings can be extended in less controlled setups. By employing air traffic controllers in a real aviation environment, we tested whether tasks with different levels of cognitive load can affect their timing behavior. Participants completed temporal production, verbal estimation, and passage of time judgments, while actively engaging in real flight control sessions. Subjective assessments of task demands, as well as physiological responses (cardiac and electrodermal activity) were also measured. Accuracy of the produced intervals was measured at two distinct phases of the flight (during low-load cruising vs. high-load landing) and under two different task load manipulations (controlling one vs. two helicopters and speaking in native vs. non-native language). Analysis of interval production accuracy showed that during the high-load landing phase significant overproductions were made, compared to the low-load cruising phase, and landing two helicopters led to greater overproductions compared to landing only one. The duration of the two-helicopter sessions was significantly overestimated compared to the single-helicopter ones, and the passage of time was felt significantly faster. Subjective assessments of workload were positively correlated with the temporal estimations and passage of time judgments, and skin responses were positively correlated with the produced intervals. Overall, our results are consistent with past research, suggesting that mental workload modulates time perception in complex, real-world environments, thus making timing behavior a reliable index of the workload changes.

Impacts of mobile phone texting on vertical ground reaction forces during stair negotiation

Stairs are one of the most dangerous places for accidental falls in both daily life and occupational settings. Knowledge about ground reaction force (GRF) characteristics during stair negotiation can facilitate a better understanding of the causal mechanisms for stair falls. The objective of this study was to investigate the effects of mobile phone texting on GRF during stair negotiation and reveal their implications associated with the safety during stair negotiation. Twelve young male adults were involved in an experimental study. They were instructed to carry out texting tasks with different levels of cognitive load while performing stair negotiation. Vertical GRF (vGRF) parameters accounting for force amplitude and loading/unloading rates were compared between texting conditions. Texting tasks resulted in slower force loading and unloading rates during stair ascent, while weight acceptance force during stair descent decreased with the application of texting tasks. These findings suggested that mobile phone texting can compromise postural stability and increase the risk of falls during stair negotiation. The findings from the present study highlight the necessity of avoiding mobile phone usage during stair negation to prevent accidental stair falls. They also have practical implications for developing effective fall prevention interventions.

Characterisation of Cognitive Load Using Machine Learning Classifiers of Electroencephalogram Data.

A high cognitive load can overload a person, potentially resulting in catastrophic accidents. It is therefore important to ensure the level of cognitive load associated with safety-critical tasks (such as driving a vehicle) remains manageable for drivers, enabling them to respond appropriately to changes in the driving environment. Although electroencephalography (EEG) has attracted significant interest in cognitive load research, few studies have used EEG to investigate cognitive load in the context of driving. This paper presents a feasibility study on the simulation of various levels of cognitive load through designing and implementing four driving tasks. We employ machine learning-based classification techniques using EEG recordings to differentiate driving conditions. An EEG dataset containing these four driving tasks from a group of 20 participants was collected to investigate whether EEG can be used as an indicator of changes in cognitive load. The collected dataset was used to train four Deep Neural Networks and four Support Vector Machine classification models. The results showed that the best model achieved a classification accuracy of 90.37%, utilising statistical features from multiple frequency bands in 24 EEG channels. Furthermore, the Gamma and Beta bands achieved higher classification accuracy than the Alpha and Theta bands during the analysis. The outcomes of this study have the potential to enhance the Human-Machine Interface of vehicles, contributing to improved safety.

Neural mechanisms of working memory dysfunction in patients with chronic insomnia disorder

ObjectiveThis study aimed to investigate the neural mechanisms underlying working memory impairment in patients with chronic insomnia disorder (CID) using event-related potentials (ERP) and resting-state functional connectivity (rsFC) approaches. MethodsParticipants, including CID patients and healthy controls (HCs), completed clinical scales and underwent electroencephalography (EEG) and functional magnetic resonance imaging (fMRI). EEG analysis compared reaction times, P3 amplitudes, event-related spectral perturbations (ERSP), and inter-trial phase synchronisation (ITPS) between CID patients and HCs. Subsequently, frontal regions (i.e., the Superior Frontal Gyrus [SFG] and Middle Frontal Gyrus [MFG]) corresponding to the EEG were selected as seeds for rsFC analysis. Correlation analyses were conducted to further investigate the relationship between functional connectivity abnormalities in brain regions and clinical symptom severity and P3 amplitude in CID patients. ResultsCompared to HCs, CID patients exhibited slower reaction times across all working memory conditions, with the deficits becoming more pronounced as memory load increased. ERP analysis revealed increased P3 amplitude, theta wave power, and reduced inter-trial synchrony in CID patients. rsFC analysis showed decreased connectivity of SFG-posterior cingulated cortex (PCC), SFG-MFG, and MFG-frontal pole (FP), and increased connectivity of MFG- Middle Temporal Gyrus (MTG)in CID patients. Importantly, a significant correlation was found between the rsFC of SFG-MTG and P3 amplitude during 1-back. ConclusionThis study confirms deficits in working memory capacity in patients with CID, specifically in the neural mechanisms of cognitive processing that vary depending on the level of cognitive load. Alterations in connectivity patterns within and between the frontal and temporal regions may be the neural basis of the cognitive impairment.

The Impact of Feedback Modalities and the Influence of Cognitive Load on Interpersonal Communication in Nonclinical Settings: Experimental Study Design.

The escalating demands of modern health care systems, combined with the emotional toll of patient care, have led to an alarming increase in physician burnout rates. This burnout, characterized by emotional exhaustion, depersonalization, and reduced personal accomplishment, can hinder doctors' ability to connect with patients effectively. Moreover, the cognitive load arising from information overload and the need for multitasking can further hinder doctors' ability to connect with patients effectively. Understanding the complex relationship between physician burnout and cognitive load is crucial for devising targeted interventions that enhance physician well-being and promote effective physician-patient interactions. Implementing strategies to alleviate burnout and cognitive load can lead to improved health care experiences and patient outcomes. Our study explores the interplay between physician burnout and its potential impact on interpersonal communication, particularly focusing on the role of cognitive load using a pilot study in a nonclinical setting involving nonclinical participants. This study uses an experimental design to evaluate 3 feedback tools (haptic, visual, and postvisit summary) and measure the cognitive load they impose on nonclinical participants in a nonclinical environment. The NASA Task Load Index, a widely accepted measure of cognitive load, was used to quantify the cognitive load associated with the feedback tools. The study used a within-subject design, meaning participants experienced all 3 feedback methods. A sample of 18 nonclinical participants was selected using counterbalancing techniques. Postsession feedback not only enhancing performance but also mitigating the influence of cognitive load as compared with real-time feedback (haptic+visual). Participants with interview experience showed lower cognitive load levels when exposed to real-time feedback as compared with novice users. In contrast, postsession feedback was more effective for novice users. In addition, cognitive workload emerged as a moderating factor in the relationship between feedback tools and their impact on performance, particularly in terms of speaking balance and pace. This moderating effect suggests that the correlation between feedback tool efficacy and performance varies based on an individual's cognitive load while using the feedback tool. The comparison of postfeedback with haptic feedback yielded a Z score of -3.245 and a P value of .001, while the comparison with visual feedback resulted in a Z score of -2.940 and a P value of .003. These outcomes underscore a significant disparity in the means between postsession feedback and real-time feedback (haptic+visual), with postsession feedback indicating the lowest mean score. Through the examination of various feedback tools, this study yields significant and insightful comparisons regarding their usability and appropriateness in nonclinical settings. To enhance the applicability of these findings to clinical environments, further research encompassing diverse participant cohorts and clinical scenarios is warranted.

An experimental study on reading in high‐immersion virtual reality

AbstractHigh‐immersion virtual reality (VR) is an increasingly valued environment for language learners. Although reading constitutes a core language skill, practicing reading in VR has received little attention. In this between‐subject, quantitative study, 79 intermediate learners of English at a German university were randomly assigned to view an interactive, multimedia‐rich story under two conditions. In the experimental condition, subjects (the VR group) experienced the story using a high‐immersion VR headset. In the comparison condition, subjects (the video group) watched a video recording (ie, screencast) of the same VR experience. In both conditions, the story was presented using identical captions in English, which served as the reading comprehension text. In addition to measuring the impact of VR on reading comprehension, validated questionnaires yielded data on the subjects' intrinsic motivation, sense of presence and cognitive load. The analysis produced several findings. First, t‐tests revealed the VR group was associated with statistically significantly higher reading comprehension scores compared with the video group (p = 0.03). Second, Wilcoxon signed‐rank tests showed that the VR treatment elicited statistically significantly higher levels of motivation (p ≤ 0.0001) and sense of presence (p ≤ 0.0001). Cognitive load was not significantly different between the groups (p = 0.22). Our main implication is that VR can be beneficial for reading practice. Practitioner notesWhat is already known about this topic High‐immersion virtual reality (VR) is engaging and motivational. Engaging students to practice reading is important. Research on practicing reading in VR has received little attention. What this paper adds It examines the effectiveness of using VR for practicing reading. It shows that VR enhances motivation and the sense of presence when reading. Students report equal levels of cognitive load while reading subtitles in VR and reading subtitles in videos. Implications for practice and/or policy Our main implication is that VR can be beneficial for reading practice. VR could be used as a motivational tool to engage students in reading activities.

LAUREATE

The latest developments in wearable sensors have resulted in a wide range of devices available to consumers, allowing users to monitor and improve their physical activity, sleep patterns, cognitive load, and stress levels. However, the lack of out-of-the-lab labelled data hinders the development of advanced machine learning models for predicting affective states. Furthermore, to the best of our knowledge, there are no publicly available datasets in the area of Human Memory Augmentation. This paper presents a dataset we collected during a 13-week study in a university setting. The dataset, named LAUREATE, contains the physiological data of 42 students during 26 classes (including exams), daily self-reports asking the students about their lifestyle habits (e.g. studying hours, physical activity, and sleep quality) and their performance across multiple examinations. In addition to the raw data, we provide expert features from the physiological data, and baseline machine learning models for estimating self-reported affect, models for recognising classes vs breaks, and models for user identification. Besides the use cases presented in this paper, among which Human Memory Augmentation, the dataset represents a rich resource for the UbiComp community in various domains, including affect recognition, behaviour modelling, user privacy, and activity and context recognition.

Assessing focus through ear-EEG: a comparative study between conventional cap EEG and mobile in- and around-the-ear EEG systems.

As our attention is becoming a commodity that an ever-increasing number of applications are competing for, investing in modern day tools and devices that can detect our mental states and protect them from outside interruptions holds great value. Mental fatigue and distractions are impacting our ability to focus and can cause workplace injuries. Electroencephalography (EEG) may reflect concentration, and if EEG equipment became wearable and inconspicuous, innovative brain-computer interfaces (BCI) could be developed to monitor mental load in daily life situations. The purpose of this study is to investigate the potential of EEG recorded inside and around the human ear to determine levels of attention and focus. In this study, mobile and wireless ear-EEG were concurrently recorded with conventional EEG (cap) systems to collect data during tasks related to focus: an N-back task to assess working memory and a mental arithmetic task to assess cognitive workload. The power spectral density (PSD) of the EEG signal was analyzed to isolate consistent differences between mental load conditions and classify epochs using step-wise linear discriminant analysis (swLDA). Results revealed that spectral features differed statistically between levels of cognitive load for both tasks. Classification algorithms were tested on spectral features from twelve and two selected channels, for the cap and the ear-EEG. A two-channel ear-EEG model evaluated the performance of two dry in-ear electrodes specifically. Single-trial classification for both tasks revealed above chance-level accuracies for all subjects, with mean accuracies of: 96% (cap-EEG) and 95% (ear-EEG) for the twelve-channel models, 76% (cap-EEG) and 74% (in-ear-EEG) for the two-channel model for the N-back task; and 82% (cap-EEG) and 85% (ear-EEG) for the twelve-channel, 70% (cap-EEG) and 69% (in-ear-EEG) for the two-channel model for the arithmetic task. These results suggest that neural oscillations recorded with ear-EEG can be used to reliably differentiate between levels of cognitive workload and working memory, in particular when multi-channel recordings are available, and could, in the near future, be integrated into wearable devices.

Effects of Urgency and Cognitive Load on Interaction in Highly Automated Vehicles

In highly automated vehicles, passengers can engage in non-driving-related activities. Additionally, the technical advancement allows for novel interaction possibilities such as voice, gesture, gaze, touch, or multimodal interaction, both to refer to in-vehicle and outside objects (e.g., thermostat or restaurant). This interaction can be characterized by levels of urgency (e.g., based on late detection of objects) and cognitive load (e.g., because of watching a movie or working). Therefore, we implemented a Virtual Reality simulation and conducted a within-subjects study with N=11 participants evaluating the effects of urgency and cognitive load on modality usage in automated vehicles. We found that while all modalities were possible to use, participants relied on touch the most. This was followed by gaze, especially for external referencing. This work helps to further understand multimodal interaction and the requirements this poses on natural interaction in (automated) vehicles.

Pupillometry in telerobotic surgery: A comparative evaluation of algorithms for cognitive effort estimation

Background: Eye gaze tracking and pupillometry are emerging topics in telerobotic surgery as it is believed that they will enable novel gaze-based interaction paradigms and provide insights into the user’s cognitive load (CL). Further, the successful integration of CL estimation into telerobotic systems is thought to catalyze the development of new human-computer interfaces for personalized assistance and training processes. However, this field is in its infancy, and identifying reliable gaze and pupil-tracking solutions in robotic surgery is still an area of ongoing research and high uncertainty. Methods: Considering the potential benefits of pupillometry-based CL assessments in telerobotic surgery, we seek to better understand the possibilities and limitations of contemporary pupillometry-based cognitive effort estimation algorithms in telerobotic surgery. To this end, we conducted a user study using the da Vinci Research Kit (dVRK) and performed two experiments where participants were asked to perform a series of N-Back tests, either while (i) idling or (ii) performing a peg transfer task. We then compare four contemporary CL estimation methods based on direct analysis of pupil diameter in the spatial and frequency domains. Results: We find that some methods can detect the presence of cognitive effort in simple scenarios (e.g., when the user is not performing any manual task), they fail to differentiate the different levels of CL. Similarly, when the manual peg transfer task is added, the reliability of all models is compromised, highlighting the necessity of more robust methods that consider different factors that complement the pupil diameter information. Conclusion: Our results offer a quantitative perspective of the limitations of the current solutions and highlight the necessity of developing tailored designs for the telerobotic surgery environment.

Cognitive Ergonomics: A Review of Interventions for Outpatient Practice.

Doctoring is difficult mental work, involving many cognitively demanding processes such as diagnosing, decision-making, parallel processing, communicating, and managing the emotions of others. According to cognitive load theory (CLT), working memory is a limited cognitive resource that can support a finite amount of cognitive load. While the intrinsic cognitive load is the innate load associated with a task, the extraneous load is generated by inefficiency or suboptimal work conditions. Causes of extraneous cognitive load in healthcare include inefficiency, distractions, interruptions, multitasking, stress, poor communication, conflict, and incivility. High levels of cognitive load are associated with impaired function and an increased risk of burnout among physicians. Cognitive ergonomics is the branch of human factors and ergonomics (HFE) focused on supporting the cognitive processes of individuals within a system. In health care, where the cognitive burden on physicians is high, cognitive ergonomics can establish practices and systems that decrease extraneous cognitive load and support pertinent cognitive processes. In this review, we present cognitive ergonomics as a useful framework for conceptualizing an oft-overlooked dimension oflaborand apply theory to practice by summarizing evidence-based cognitive ergonomics interventions for outpatient care settings. Our proposed interventions are structured within four general recommendations: 1. minimize distractions, interruptions, and multitasking; 2. optimize the use of the electronic health record (EHR); 3. optimize the use of health information systems (HIS); and 4. support good communication and teamwork. Best practices in cognitive ergonomics can benefit patients, minimize practice inefficiency, and support physician career longevity.

Mutual Information between EDA and EEG in Multiple Cognitive Tasks and Sleep Deprivation Conditions.

Sleep deprivation, a widespread phenomenon that affects one-third of normal American adults, induces adverse changes in physical and cognitive performance, which in turn increases the occurrence of accidents. Sleep deprivation is known to increase resting blood pressure and decrease muscle sympathetic nerve activity. Monitoring changes in the interplay between the central and autonomic sympathetic nervous system can be a potential indicator of human's readiness to perform tasks that involve a certain level of cognitive load (e.g., driving). The electroencephalogram (EEG) is the standard to assess the brain's activity. The electrodermal activity (EDA) is a reflection of the general state of arousal regulated by the activation of the sympathetic nervous system through sweat gland stimulation. In this work, we calculated the mutual information between EDA and EEG recordings in order to consider linear and non-linear interactions and provide an insight of the relationship between brain activity and peripheral autonomic sympathetic activity. We analyzed EEG and EDA data from ten participants performing four cognitive tasks every two hours during 24 h (12 trials). We decomposed EEG data into delta, theta, alpha, beta, and gamma spectral components, and EDA into tonic and phasic components. The results demonstrate high values of mutual information between the EDA and delta component of EEG, mainly in working memory tasks. Additionally, we found an increase in the theta component of EEG in the presence of fatigue caused by sleep deprivation, the alpha component in tasks demanding inhibition and attention, and the delta component in working memory tasks. In terms of the location of brain activity, most of the tasks report high mutual information in frontal regions in the initial trials, with a trend to decrease and become uniform for all the nine analyzed EEG channels as a consequence of the sleep deprivation effect. Our results evidence the interplay between central and sympathetic nervous activity and can be used to mitigate the consequences of sleep deprivation.

Effects of Refutational Texts and Seductive Pictures on Conceptual Change

As educators, we often seek to engage students’ prior knowledge to help them learn new and potentially difficult science content. However, sometimes our experiences with the world lead us to create misconceptions that run counter to the scientific consensus. Refutational texts have been shown to be more effective at changing individuals’ misconceptions compared to traditional (i.e., expository) texts. Sometimes, conceptual change materials might include irrelevant but interesting pictures geared toward increasing engagement or positive affect while learning. These are referred to as seductive pictures, and although they are intended to promote the situational interest of readers, they may hinder learning since they might cause cognitive overload. The current study sought to investigate the effects of text structure and seductive pictures on individuals’ knowledge of genetically modified foods, situational interest, and cognitive loads. We found significant learning advantages for the refutational text groups and significant disadvantages for the seductive pictures groups. Additionally, the individuals who were exposed to seductive pictures demonstrated higher levels of extraneous cognitive load than those who were not. Implications and limitations of the present study are discussed.