USE OF POPE ENGAGEMENT INDEX TO MEASURE COGNITIVE LOAD OF PHYSICAL MODELING ACTIVITIES IN ORGANIC CHEMISTRY

Understanding how students learn and process information is critical to developing physical modeling activities that facilitate student learning by decreasing cognitive load in the working memory. Optimizing cognitive load during physical modeling activities in organic chemistry is the key to effective and efficient learning. Using EEG (electroencephalogram) and eye tracking technologies, researchers measured and recorded the cognitive processing of participants while they completed a chiral physical modeling activity. Analysis of the data using the Engagement Index developed by Pope et al provided information necessary to develop curriculum that does not undermine student learning due to excessive cognitive load

Using physiological measures to measure changes in cognitive load associated with automaticity and transfer

This study investigated the ability of two physiological measures, galvanic skin response and heat flux, to reflect changes in cognitive load using a variation of the dot counting task developed by Lassaline and Logan (1993). Concurrently, the robustness of the dual processing theory of automaticity was evaluated via disruption. The utilised task was designed to create a shift from controlled to automatic processing via practice, followed by a return to controlled processing via the introduction of a 6-digit memory recognition task designed to increase working-memory load and disrupt automaticity. As reaction time has previously been demonstrated to be a reliable performance measure of cognitive load, it was expected that there would be a positive relationship between reaction time, heat flux and galvanic skin response. The results found the expected pattern for reaction time, with an increase seen at the introduction of the memory task. Group results suggested automaticity was disrupted at this point, but analysis of individual data suggested automaticity endured for the majority of participants despite the contextual change in the task. This finding provides support for Instance Theory (Logan, 1988). The expected correlation between reaction time and galvanic skin response was not seen. Reductions in reaction time due to practice were correlated with reductions in heat flux due to practice, however, the expected increase at the introduction of the memory task was not seen. Whilst neither physiological measure was found to demonstrate an increase in cognitive load in this experiment, a task that was more cognitively challenging than the 6-digit memory recognition task may have produced more substantial results

Studying the users’ information-seeking behavior by recording brain waves activity with Electroencephalography method: A systematic Review

Despite the novelty in methodologies, User behavior study based on brain activity during information-seeking stages has become popular among information science researchers. This paper reviews scientific publications in which information-seeking behavior has been studied along with recorded brain activity to shed light on research status, challenges, and suggestions for future studies. Based on Kitchenham & Charters (2007) framework, a complete web search was performed in English and Persian scientific databases, and 22 publications in English were found as the final result, from 2007 to 2020. Review results demonstrate that exploring the user status (10 papers) and brain wave activity during information-seeking episodes (12 papers) were the most dominant subjective approaches in the field of user behavior studies. Cognitive load was found as an effective cognitive component on user status. With eye movement measurement and brain waves frequency study, 3 factors were found effective on cognitive load level generated during information searching and processing: searching media type, information representation, and text reading style. Brain wave activity and pupil dilation analysis were the most important measures in user status during search stages, and alpha and theta band waves were demonstrated as an index for cognitive load measurement during the information searching process. A correlation among eye data, search behavior, task complexity based on user experience, and cognitive style – as another effective factor on user status- led to results in different information searching behavior demonstrations. Also, 3 main stages were analyzed in the information-seeking process, based on brain wave activity: information exploring and query formulation, query reformulation and selection, relevance judgment, and decision making. Results showed a difference between brain activity areas, and differences in pupil dilation change level and alpha/beta frequency level during different search episodes. For future research, some suggestions were offered based on reviews. Finding relations between correlations among cognitive styles, task features, and domain knowledge during information searching process, personalized information retrieval improvement, more collaboration between information science and neurocognitive specialists, research in more user affective status like aggression and fatigue during the search process, using more economic methods and portable devices aiming to reduce research costs and expenses, facilitating larger sample studies and designing standard tasks were considered as a suggestion. Finally, some challenges were found based on reviewed studies. Some concepts like relevance feedback in information retrieval need more investigation. Also, it is necessary to investigate and explore user affections during the search process with multiple approaches

Investigation of Breath Counting, Abdominal Breathing and Physiological Responses in Relation to Cognitive Load with University Students

Ph.D.Ph.D. Thesis. University of Hawaiʻi at Mānoa 201

Multiple System Modelling and Analysis of Physiological and Brain Activity and Performance at Rest and During Exercise

One of the current interests of exercise physiologists is to understand the nature and control of fatigue related to physical activity to optimise athletic performance. Therefore, this research focuses on the mathematical modelling and analysis of the energy system pathways and the system control mechanisms to investigate the various human metabolic processes involved both at rest and during exercise. The first case study showed that the PCr utilisation was the highest energy contributor during sprint running, and the rate of ATP production for each anaerobic subsystem was similar for each athlete. The second study showed that the energy expenditure derived from the aerobic and anaerobic processes for different types of pacing were significantly different. The third study demonstrated the presence of the control mechanisms, and their characteristics as well as complexity differed significantly for any physiological organ system. The fourth study showed that the control mechanisms manifest themselves in specific ranges of frequency bands, and these influence athletic performance. The final study demonstrated a significant difference in both reaction time and accuracy of the responses to visual cues between the control and exercise-involved cognitive trials. Moreover, the difference in the EEG power ratio at specific regions of the brain; the difference in the ERP components’ amplitudes and latencies; and the difference in entropy of the EEG signals represented the physiological factors in explaining the poor cognitive performance of the participants following an exhaustive exercise bout. Therefore, by using mathematical modelling and analysis of the energy system pathways and the system control mechanisms responsible for homeostasis, this research has expanded the knowledge how performance is regulated during physical activity and together with the support of the existing biological control theories to explain the development of fatigue during physical activity

The Application of Physiological Metrics in Validating User Experience Evaluation on Automotive Human Machine Interface Systems

Automotive in-vehicle information systems have seen an era of continuous development within the industry and are recognised as a key differentiator for prospective customers. This presents a significant challenge for designers and engineers in producing effective next generation systems which are helpful, novel, exciting, safe and easy to use. The usability of any new human machine interface (HMI) has an implicit cost in terms of the perceived aesthetic perception and associated user experience. Achieving the next engaging automotive interface, not only has to address the user requirements but also has to incorporate established safety standards whilst considering new interaction technologies. An automotive (HMI) evaluation may combine a triad of physiological, subjective and performance-based measurements which are employed to provide relevant and valuable data for product evaluation. However, there is also a growing interest and appreciation that determining real-time quantitative metrics to drivers’ affective responses provide valuable user affective feedback. The aim of this research was to explore to what extent physiological metrics such as heart rate variability could be used to quantify or validate subjective testing of automotive HMIs. This research employed both objective and subjective metrics to assess user engagement during interactions with an automotive infotainment system. The mapping of both physiological and self-report scales was examined over a series of studies in order to provide a greater understanding of users’ responses. By analysing the data collected it may provide guidance within the early stages of in-vehicle design evaluation in terms of usability and user satisfaction. This research explored these metrics as an objective, quantitative, diagnostic measure of affective response, in the assessment of HMIs. Development of a robust methodology was constructed for the application and understanding of these metrics. Findings from the three studies point towards the value of using a combination of methods when examining user interaction with an in-car HMI. For the next generation of interface systems, physiological measures, such as heart rate variability may offer an additional dimension of validity when examining the complexities of the driving task that drivers perform every day. There appears to be no boundaries on technology advancements and with this, comes extra pressure for car manufacturers to produce similar interactive and connective devices to those that are already in use in homes. A successful in-car HMI system will be intuitive to use, aesthetically pleasing and possess an element of pleasure however, the design components that are needed for a highly usable HMI have to be considered within the context of the constraints of the manufacturing process and the risks associated with interacting with an in-car HMI whilst driving. The findings from the studies conducted in this research are discussed in relation to the usability and benefits of incorporating physiological measures that can assist in our understanding of driver interaction with different automotive HMIs

EEG-Based Mental States Identification

In this thesis, we focus on the identification of mental states described according to the definition of awareness and wakefulness. Using algorithmic methods, we show that it is possible to differentiate between two brain states based on the brain electrical activity collected by EEG. We begin by explaining the overall theoretical framework which enabled us to develop the detection of brain states. It starts with data acquisition. Following that, we analyse the pre-processing of the data before the extraction of features. Finally, we go on to statistically evaluate the results. In order to achieve this task, we propose four experiments. We will first focus on exploring different brain states for patients in Intensive Care Unit (ICU) such as coma and quasi-brain-death states. To distinguish these states, we use a signal processing method based on the EEG signal phase. A phase synchrony index based on Shannon entropy was used to separate the two states. Statistical validation revealed a significant difference between the two via delta-alpha and theta-alpha frequency couplings. Next, we studied the neuronal mechanisms which is used to understand consciousness. We did that by using dipole modelling. This method was applied to local-global experiment and the paradigm of auditory deviance with two hierarchical levels. A modulation of this experiment is generated by a sedative Propofol to study the effect on conscious states. This experiment was analysed in greater detail using the Imaging Method to do the source localisation. We analysed three different time-windows. The first window corresponds to the local effect during the initial response of the brain. We assume that this input is related to auditory areas and activates the temporal lobe. The second window is at the interface between the local effect and the global effect. In here we are especially interested in the interaction between these two effects during the second window. Finally, the third window will enable us to study the overall effect. We hypothesize a global activation of neural networks corresponding to consciousness as described by the global workspace theory. The third experiment focused on brain states high-level athletes experience during a cognitive task. Two different groups of cyclists, endurances and sprinters, were asked to do a Stroop task for 30 minutes. We studied the influence of the task and the potential differences in brain activity between the two groups. We found through the frequency analysis that the brain activity between the two groups can be distinguished, but was not modified by the cognitive task. Finally, we studied the influence of the sensorimotor loop on the brain. A physical task was applied, consisting in lifting a weight with two measurements, where the lifting arm can also be in fatigued state. Using sources reconstruction from EEG, we studied the impact of weight-lifting and the physical fatigue upon neuronal activities and the neuronal origins of these effects. We found that only weight has an effect, whereas fatigue effect is not significant. We conclude with a discussion of the mechanisms of consciousness analysed via algorithmic methods and some future work for the possibility to distinguish better between different cognitive states

Multiple system modelling and analysis of physiological and brain activity and performance at rest and during exercise

One of the current interests of exercise physiologists is to understand the nature and control of fatigue related to physical activity to optimise athletic performance. Therefore, this research focuses on the mathematical modelling and analysis of the energy system pathways and the system control mechanisms to investigate the various human metabolic processes involved both at rest and during exercise. The first case study showed that the PCr utilisation was the highest energy contributor during sprint running, and the rate of ATP production for each anaerobic subsystem was similar for each athlete. The second study showed that the energy expenditure derived from the aerobic and anaerobic processes for different types of pacing were significantly different. The third study demonstrated the presence of the control mechanisms, and their characteristics as well as complexity differed significantly for any physiological organ system. The fourth study showed that the control mechanisms manifest themselves in specific ranges of frequency bands, and these influence athletic performance. The final study demonstrated a significant difference in both reaction time and accuracy of the responses to visual cues between the control and exercise-involved cognitive trials. Moreover, the difference in the EEG power ratio at specific regions of the brain; the difference in the ERP components’ amplitudes and latencies; and the difference in entropy of the EEG signals represented the physiological factors in explaining the poor cognitive performance of the participants following an exhaustive exercise bout. Therefore, by using mathematical modelling and analysis of the energy system pathways and the system control mechanisms responsible for homeostasis, this research has expanded the knowledge how performance is regulated during physical activity and together with the support of the existing biological control theories to explain the development of fatigue during physical activity.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Model konsep reka bentuk antaramuka koswer berbantu mahasiswa Tunakerna

The era of global education today is in need of educational media, especially those involving people with disabilities, as an effective media can have an impact on the quality of education for this group. However, in previous studies revealed that the medium of learning for this group is very limited and more focused on conventional learning because the lack of learning technology support has made it difficult for the learning process. The main purpose of this study is to propose a conceptual design model of assistive courseware interface for hearing impaired undergraduates.The development of student learning that has a hearing problem known as „tunakerna‟ according to the Fourth Edition Kamus Dewan Bahasa dan Pustaka (2008). The theoretical framework of scientific research design was chosen as the methodology used in this study. Expert validation approach has been implemented on Conceptual Design Model of Assistive Courseware Interface for Hearing Impaired Undergraduates (KOSMAT) model is designed with seven reserve components of a generic component structure, multimedia design elements, multiple intelligences for visual, interpersonal and intrapersonal, a model of instructional design, learning theory, object-oriented learning styles, and development process. Prototype courseware was developed by applying the applicability of KOSMAT model that aims to test the usability of the target users among hearing impaired undergraduates. The study found that usability testing showed a satisfactory performance for the three dimensions of ease of use, ease of learn and content. KOSMAT model is the improved results of the expert validation through consultation with experts. Hence, it should serve as a guideline or a reference to develop a learning courseware to hearing impaired undergraduates especially in special education