Human Information Processing Research Articles

A hybrid human and organisational analysis method for railway accidents based on STAMP-HFACS and human information processing

Safety is a constant priority for the railway industry and there are numerous hazards in and around the rail system which may result in damage to train and environment, human injury and fatalities. Low levels of human and organisational performance have been shown to be a prime cause of railway accidents and a number of accident models and methods have been developed in order to probe deeper into the role played by organisational factors in accident causation. The Systems–Theoretical Accident Modelling and Processes (STAMP) method for example, represents a promising systematic and systemic way of examining sociotechnical systems such as the railway. Another method, the Human Factors Analysis and Classification System (HFACS), based upon Reason's model of human error in an organisational context, has also proved popular as a human factors accident analysis framework. However, human factors elements are still somewhat limited and under-specified and these managerial and social issues within an organisation are simply regarded as sources of failure in the control constraints of STAMP. HFACS likewise, categorises accident data rather than analysing it in more depth. In this context, a hybrid human and organisational analysis method based on HFACS-STAMP (HFACS-STAMP method for railway accidents, HS-RAs) is proposed to identify and analyse human and organisational factors involved in railway accidents. Using the categories of human errors derived from HFACS and the structured systematic analysis process of STAMP, the HS-RAs method provides a mechanism by which active failures can promulgate across organisations and give a systemic analysis of human error in accidents. Combined with human information processing, the HS-RAs method gives a detailed causal analysis of human errors from receiving information to implement control actions. At last, the HS-RAs method is demonstrated using a case study of the 2011 Yong-Wen railway collision. A number of prominent accident causes of human factors are revealed and necessary countermeasures are proposed to avoid the recurrence of similar accidents. The HFACS-STAMP hybrid method has several advantages and can contribute to railway safety by providing a detailed analysis of the role of human error in railway accidents.

Cross-Level Moderation of Team Cohesion in Individuals’ Utilitarian and Hedonic Information Processing: Evidence in the Context of Team-Based Gamified Training

Today firms use teams extensively to accomplish organizational objectives. In addition, gamification has recently received much attention as a means of persuading employees and customers to engage in desired behaviors. Despite the importance of teams and the growing interest in gamification as a persuasion tool, past researchers have paid little attention to team-based gamification from a multilevel perspective. Based on motivational consistency theories, we propose that at the team level, team performance has a positive effect on team cohesion. Drawing upon the elaboration likelihood model (ELM), we further propose two cross-level effects in the context of team-based gamified training: first, that team cohesion will positively moderate the relationship between utilitarian perceptions (i.e., perceived quality of learning) and attitude; and second, that team cohesion will negatively moderate the relationship between hedonic perceptions (i.e., perceived enjoyment of learning) and attitude. We tested our research model using an enterprise resource planning (ERP) simulation game involving 232 participants in 78 teams. The results of Ordinary Least Squares and Hierarchical Linear Modeling analysis support our hypotheses. This study makes three substantive contributions to the team literature and to the ELM in the context of team-based gamified training. First, it theorizes and empirically tests the effect of team performance on team cohesion at the team level. Second, it extends the ELM by examining the cross-level moderation of team cohesion in human information processing. Third, it demonstrates that the utilitarian and hedonic aspects of information technology do not influence user attitudes equally.

Automation-Adoption Approach Maps Human/System Interaction

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 191408, “Automating Directional Drilling: Technology-Adoption Staircase Mapping Levels of Human Interaction,” by Robert Wylie, SPE, xnDrilling; Kevin McClard, Performance Drilling Technologies; and John de Wardt, SPE, De Wardt and Company, prepared for the 2018 SPE Annual Technical Conference and Exhibition, Dallas, 24–26 September. The paper has not been peer reviewed. This paper describes the progress of directional-drilling-automation systems along the cognitive functions and levels of automation as defined by the Levels of Automation Taxonomy (LOAT) hierarchy introduced by the Drilling Systems Automation Roadmap Industry Initiative. LOAT is based on incremental automation of the four cognitive functions of interaction. Levels of human/system interaction are described on a nine-point scale ranging from fully manual, to levels of system support for the human, to levels of automation overseen by the human, to full automation. The LOAT Hierarchy LOAT is a powerful tool for mapping the transition from a purely manual process, to the degree of automation that any system can achieve in the early transition phase, through a timeline to full automation. The transition levels from manual to autonomous were likened to the four cognitive functions that occur in both human interaction with machinery and automated interaction with machinery. These four functions, based on a staged model of human information processing, were translated into equivalent sequential functions applicable to both human processing and automated processing. These functions are Information acquisition Information analysis Decision and action selection Action implementation Automation is often perceived as automation of the action-sequence execution, the implementation of the decision for action by a robot or robotic mechanism. In reality, it is easier and more reliable to apply degrees of automation to the information-acquisition and information-analysis cognitive functions of the control process before decision-making and certainly before action-sequence execution. In a first phase of automation implementation, the automated system acquires the data and undertakes an analysis of its information. The output from this process in many automated systems is typically in the form of alarms designed to attract the attention of the human overseers. However, challenges are inherent in this process: Does the human receiving the alarm believe the alarm is real and relevant, and, if so, does the human react to the alarm effectively by making a good decision and then implementing the appropriate action as a consequence of that decision? Drilling case studies often describe human indecision and failure to act in a timely manner as a cause of catastrophic events. The human/machine interface is the point at which the system displays to the human the situation and the human reacts and provides input through control devices. In a purely manual mode, systems simply display data that the human analyzes and uses to decide on and implement action. In staged automated modes, the system is designed to advance the automated collection and processing of data. Initially, the data are presented to the human operator to prompt a decision and implementation of an action. In the next stage, the system provides advice on which action should be taken.

Work design in future industrial production: Transforming towards cyber-physical systems

Rapid advancements in an array of digital technologies and applications promote the transformation of industrial production into cyber-physical systems (CPS). This process is projected to lead to a completely new level of process automation, thereby redefining the role of humans and altering current work designs in yet unknown ways. However, existing literature is rather ambiguous and not explicit on how the transformation towards CPS affects work design. In this study, we therefore consider this transformation at a much more detailed level. Our main contribution is the development of a framework to assess work design changes in the transformation towards CPS, and the consideration of the role of management choice therein. The framework relates (future) capabilities of CPS on the machine, production line, factory and supply chain scope to functions of human information processing. We then evaluate how the potential automation or augmentation of those functions by CPS affects job characteristics. Automation in this context is defined as the transfer of control and decision-making from humans to CPS, while augmentation means that technology is used to enhance human productivity or capability. We expect that the transformation towards CPS and the resulting automation and augmentation of tasks will shift the majority of human work to jobs characterized by high levels of job complexity, job autonomy and skill variety. This effect will become more severe when tasks are increasingly automated in the transformation towards CPS. During this development, human skills and knowledge will presumably remain critical in near future industrial production. Nevertheless, the ultimate implications for work design are strongly dependent on management choice. Strategic decisions are required on (1) which functions to automate across different scopes of operations and (2) how to group the resulting pool of tasks into jobs. This may result in various work designs. However, this choice is to a certain degree limited, and the role of technology is to restrict, rather than determine management choice.

Постуральные ответы на движущиеся звуковые образы в зависимости от ведущей сенсорной модальности при ориентации в пространстве

Influences of individual characteristics of sensory information processing in humans on postural responses to approaching and receding sound images were investigated. Two groups of subjects with different cognitive style were examined (8 field-dependent and 9 field-independent individuals). Stabilographic signals before, during and after sound stimulation of different types (approaching, receding and unmoving sound images) were recorded, and the following characteristics of the center of pressure (COP) sway along sagittal axis were analyzed: COP trajectory length, average linear velocity, COP shift, and variation. Substantial differences were revealed between the strategies of equilibrium maintenance in the two groups of subjects. COP variation was higher for the field-independent group of subjects in all time intervals. Comparative analysis of COP characteristics received during sound stimulation showed that COP trajectory length and average linear velocity in the field-independent group was higher than ones in the field-dependent group only for receding sound images. Field-dependent subjects demonstrated reliable backward COP shift during listening by subject to approaching sound images. Unmoving sound images received during their listening did not influence any of the studied COP characteristics. The differences in postural control system responses, which were revealed, are in good agreement with the idea about predominant usage of sensory information of different modalities by the investigated groups of subjects: exteroceptive information in field-dependent, and proprioceptive in field-independent individuals.

Information processing in a sensorimotor operation: Atkinson and Shiffrinrsquo;s model revisited

Authors present the model of memory by Atkinson and Shiffrin as a starting point to a new interpretation and base for new model of information processing in humans. They point to the fact that already in their seminal paper, Atkinson and Shiffrin mentioned about some control processes. Therefore, though they termed specific units of memory “sensory register”, “short term store” and “long term store”, in their model information was not only preserved, but also somehow processed in particular “memory drawers”. The authors of this paper assume that the base of science are facts and observation, but it consists of interpretations and theories. Hence, the same facts may be interpret differently by different scientists. In the paper they present another concept of human memory, less mathematical, but more psychological than that by Atkinson and Shiffrin.

The Role of Emotions in Advertising: A Call to Action

Emotions play a central role in advertising. Starting from the extensive and ever-developing literature on the role of emotions in human information processing and behavior, as studied within general psychology, we discuss how advertising literature has tackled this topic throughout the years. This review reveals that the potential of direct behavioral effects of discrete integral emotions, meaning specific emotions evoked by an advertising message, has remained underexploited. After specifying this research gap, we outline the theoretical rationale behind this behavioral approach and sketch challenges and opportunities to address the potential of discrete emotions and their advertising-relevant behavioral outcomes. We thereby take advantage of the nature of digital media environments and recent methodological advances in this context. We provide guidelines to apply this rationale in advertising research, discuss its strength in comparison with current practice and its potential to extend to incidental emotions, and consider the ethical implications of our proposal.

Psychophysiology of communication and its impact on human information processing and self-regulation: A case study in Ukraine.

Psychophysiology of communication and its impact on human information processing and self-regulation: A case study in Ukraine.

Psychophysiology of Communication and Its Impact on Human Information Processing and Self-Regulation: A Case Study in Ukraine

Psychophysiology of Communication and Its Impact on Human Information Processing and Self-Regulation: A Case Study in Ukraine

EEG time signature in Alzheimer´s disease: Functional brain networks falling apart.

Spontaneous mental activity is characterized by dynamic alterations of discrete and stabile brain states called functional microstates that are thought to represent distinct steps of human information processing. Electroencephalography (EEG) directly reflects functioning of brain synapses with a uniquely high temporal resolution, necessary for investigation of brain network dynamics. Since synaptic dysfunction is an early event and best correlate of cognitive status and decline in patients along Alzheimer's disease (AD) continuum, EEG microstates might serve as valuable early markers of AD. The present study investigated differences in EEG microstate topographies and parameters (duration, occurrence and contribution) between a large cohort of healthy elderly (n=308) and memory clinic patients: subjective cognitive decline (SCD, n=210); mild cognitive impairment (MCI, n=230) and AD (n=197) and how they correlate to conventional cerebrospinal fluid (CSF) markers of AD. Four most representative microstate maps assigned as classes A, B (asymmetrical), C and D (symmetrical) were computed from the resting state EEGs since it has been shown previously that this is sufficient to explain most of the resting state EEG data. Statistically different topography of microstate maps were found between the controls and the patient groups for microstate classes A, C and D. Changes in the topography of microstate class C were associated with the CSF Aβ42 levels, whereas changes in the topography of class B were linked with the CSF p-tau levels. Gradient-like increase in the contribution of asymmetrical (A and B) and gradient-like decrease in the contribution of symmetrical (C and D) maps were observed with the more severe stage of cognitive impairment. Our study demonstrated extensive relationship of resting state EEG microstates topographies and parameters with the stage of cognitive impairment and AD biomarkers. Resting state EEG microstates might therefore serve as functional markers of early disruption of neurocognitive networks in patients along AD continuum.

Characterizing Mobile-Enhanced Cognitive Abilities: Implications for Accounting Jobs

The purpose of this research paper is to characterise mobile-enhanced cognitive job requirements and analyse implications on accounting jobs for performance improvement and human resource management. This paper first develops a mobile cognitive task analysis (MCTA) model based on the human information processing theory, which identifies the cognitive abilities that can be enhanced by mobile devices when performing cognitive-intensive jobs. Second, these mobile cognitive abilities are decomposed into 52 measurable items and assessed by surveys. Data were collected for 50 cognitive-oriented jobs from 400 surveys with 368 valid surveys (92% of valid survey). Third, results from factor analysis indicate that there are nine dimensions of mobile-enhanced cognitive abilities. Fourth, the mobile-enhanced cognitive ability topographies on three accounting jobs (Accountant, Auditor, and Tax Accountant) were constructed based on the weighted factor score analysis, which indicate that the accounting jobs have different requirements on the derived mobile-enhanced cognitive ability intensities. Finally, theoretical and practical implications are also presented in this paper.

Characterising mobile-enhanced cognitive abilities: implications for accounting jobs

The purpose of this research paper is to characterise mobile-enhanced cognitive job requirements and analyse implications on accounting jobs for performance improvement and human resource management. This paper first develops a mobile cognitive task analysis (MCTA) model based on the human information processing theory, which identifies the cognitive abilities that can be enhanced by mobile devices when performing cognitive-intensive jobs. Second, these mobile cognitive abilities are decomposed into 52 measurable items and assessed by surveys. Data were collected for 50 cognitive-oriented jobs from 400 surveys with 368 valid surveys (92% of valid survey). Third, results from factor analysis indicate that there are nine dimensions of mobile-enhanced cognitive abilities. Fourth, the mobile-enhanced cognitive ability topographies on three accounting jobs (Accountant, Auditor, and Tax Accountant) were constructed based on the weighted factor score analysis, which indicate that the accounting jobs have different requirements on the derived mobile-enhanced cognitive ability intensities. Finally, theoretical and practical implications are also presented in this paper.

Attending to the Chemical Senses.

Theorizing around the topic of attention and its role in human information processing largely emerged out of research on the so-called spatial senses: vision, audition, and to a lesser extent, touch. Thus far, the chemical senses have received far less research interest (or should that be attention) from those experimental psychologists and cognitive neuroscientists interested in the topic. Nevertheless, this review highlights the key role that attentional selection also plays in chemosensory information processing and awareness. Indeed, many of the same theoretical approaches/experimental paradigms that were originally developed in the context of the spatial senses, can be (and in some cases already have been) extended to provide a useful framework for thinking about the perception of taste/flavour. Furthermore, a number of those creative individuals interested in modifying the perception of taste/flavour by manipulating product-extrinsic cues (such as, for example, music in the case of sonic seasoning) are increasingly looking to attentional accounts in order to help explain the empirical phenomena that they are starting to uncover. However, separate from its role in explaining sonic seasoning, gaining a better understanding of the role of attentional distraction in modulating our eating/drinking behaviours really ought to be a topic of growing societal concern. This is because distracted diners (e.g., those who eat while watching TV, fiddling with a mobile device or smartphone, or even while driving) consume significantly more than those who mindfully pay attention to the sensations associated with eating and drinking.

Tactile, Visual, and Crossmodal Visual-Tactile Change Blindness: The Effect of Transient Type and Task Demands.

The present study examined whether tactile change blindness and crossmodal visual-tactile change blindness occur in the presence of two transient types and whether their incidence is affected by the addition of a concurrent task. Multimodal and tactile displays have been proposed as a promising means to overcome data overload and support attention management. To ensure the effectiveness of these displays, researchers must examine possible limitations of human information processing, such as tactile and crossmodal change blindness. Twenty participants performed a unmanned aerial vehicle (UAV) monitoring task that included visual and tactile cues. They completed four blocks of 70 trials each, one involving visual transients, the other tactile transients. A search task was added to determine whether increased workload leads to a higher risk of change blindness. The findings confirm that tactile change detection suffers in terms of response accuracy, sensitivity, and response bias in the presence of a tactile transient. Crossmodal visual-tactile change blindness was not observed. Also, change detection was not affected by the addition of the search task and helped reduce response bias. Tactile displays can help support multitasking and attention management, but their design needs to account for tactile change blindness. Simultaneous presentation of multiple tactile indications should be avoided as it adversely affects change detection. The findings from this research will help inform the design of multimodal and tactile interfaces in data-rich domains, such as military operations, aviation, and healthcare.

ANÁLISE FATORIAL EXPLORATÓRIA DE UMA ESCALA DE ESTRATÉGIAS DE APRENDIZAGEM

As estratégias de aprendizagem são técnicas, métodos, procedimentos ou sequências de ações escolhidas pelo estudante, de forma consciente, para a realização de uma determinada tarefa e para atingir objetivos de aprendizagem. O estudo das estratégias é fundamental para a educação, visto que elas funcionam como ferramenta do aprendiz. Esta pesquisa tem como objetivo descrever os passos relativos à construção da Escala de Estratégias de Aprendizagem para Estudantes Jovens e Adultos (EEA-JA), apresentar dados preliminares de suas propriedades psicométricas e buscar evidências de validade de construto. Participaram 800 estudantes de uma universidade particular do Sul de Minas Gerais, matriculados em nove cursos. A maioria dos participantes é do sexo feminino (N=453) e a idade média de 22 anos. Da análise fatorial exploratória dos 40 itens da escala, emergiram dois fatores coerentes com a descrição das estratégias de aprendizagem cognitivas e metacognitivas descritas pelas teorias Cognitiva e do Processamento Humano da Informação, com consistência interna medida pelo alfa de Cronbach, (0,85). Esses resultados iniciais revelam propriedades psicométricas promissoras da escala para uso no contexto educativo.
 Palavras-chave: Estratégias de Aprendizagem. Escala. Validação.

Two good reasons to say 'change!' - ensemble representations as well as item representations impact standard measures of VWM capacity.

Visual working memory (VWM) is a central bottleneck in human information processing. Its capacity is most often measured in terms of how many individual-item representations VWM can hold (k). In the standard task employed to estimate k, an array of highly discriminable colour patches is maintained and, after a short retention interval, compared to a test display (change detection). Recent research has shown that with more complex, structured displays, change-detection performance is, in addition to individual-item representations, supported by ensemble representations formed as a result of spatial subgroupings. Here, by asking participants to additionally localize the change, we reveal indication for an influence of ensemble representations even in the very simple, unstructured displays of the colour-patch change-detection task. Critically, pure-item models from which standard formulae of k are derived do not consider ensemble representations and, therefore, potentially overestimate k. To gauge this overestimation, we develop an item-plus-ensemble model of change detection and change localization. Estimates of k from this new model are about 1 item (~30%) lower than the estimates from traditional pure-item models, even if derived from the same data sets.

Modem hypermedia systems, which encompass the ability to adapt to the properties of human memory and cognition

In this article we would like to show the need for developing knowledge access systems that can account for the imperfections in human perception, information processing and memory (Higgins et al., 1996). The implementation of such systems will result in enormous savings in the process of learning at all three stages of knowledge acquisition (by the mind): (1) access knowledge to, (2) learning and (3) knowledge retention (Clark et al., 1997). In particular, we will try to stress the importance of repetition spacing algorithms (Woźniak and Gorzelańczyk, 1994), as well as the importance of (1) (2) and the application of the newly introduced concept of processing, ordinal attributes in hypertext documents, semantics (Wiesman et al., 1997; Gillham, 1988).

Precision Inhibitory Stimulation of Individual-Specific Cortical Hubs Disrupts Information Processing in Humans.

Noninvasive brain stimulation (NIBS) is a promising treatment for psychiatric and neurologic conditions, but outcomes are variable across treated individuals. In principle, precise targeting of individual-specific features of functional brain networks could improve the efficacy of NIBS interventions. Network theory predicts that the role of a node in a network can be inferred from its connections; as such, we hypothesized that targeting individual-specific "hub" brain areas with NIBS should impact cognition more than nonhub brain areas. Here, we first demonstrate that the spatial positioning of hubs is variable across individuals but reproducible within individuals upon repeated imaging. We then tested our hypothesis in healthy individuals using a prospective, within-subject, double-blind design. Inhibition of a hub with continuous theta burst stimulation disrupted information processing during working-memory more than inhibition of a nonhub area, despite targets being separated by only a few centimeters on the right middle frontal gyrus of each subject. Based upon these findings, we conclude that individual-specific brain network features are functionally relevant and could leveraged as stimulation sites in future NIBS interventions.

A Flexible Scheme to Model the Cognitive Influence on Emotions in Autonomous Agents

Autonomous agents (AAs) are designed to embody the natural intelligence by incorporating cognitive mechanisms that are applied to evaluate stimuli from an emotional perspective. Computational models of emotions (CMEs) implement mechanisms of human information processing in order to provide AAs for a capability to assign emotional values to perceived stimuli and implement emotion-driven behaviors. However, a major challenge in the design of CMEs is how cognitive information is projected from the architecture of AAs. This article presents a cognitive model for CMEs based on appraisal theory aimed at modeling AAs' interactions between cognitive and affective processes. The proposed scheme explains the influence of AAs' cognition on emotions by fuzzy membership functions associated to appraisal dimensions. The computational simulation is designed in the context of an integrative framework to facilitate the development of CMEs, which are capable of interacting with cognitive components of AAs. This article presents a case study and experiment that demonstrate the functionality of the proposed models.

Military Object Real-Time Detection Technology Combined with Visual Salience and Psychology

This paper presents a method of military object detection through the combination of human visual salience and visual psychology, so as to achieve rapid and accurate detection of military objects on the vast and complex battlefield. Inspired by the process of human visual information processing, this paper establishes a salient region detection model based on double channel and feature fusion. In this model the pre-attention channel is to process information on the position and contrast of images, and the sub-attention channel is to integrate information on primary visual features first and then merges results of the two channels to determine the salient region. The main theory of Gestalt visual psychology is then used as the constraint condition to integrate the candidate salient regions and to obtain the object figure with overall perception. After that, the efficient sub-window search method is used to detect and filter the object in order to determine the location and range of objects. The experimental results show that, when compared with the existing algorithms, the algorithm proposed in this paper has prominent advantages in precision, effectiveness, and simplicity, which not only significantly reduces the effectiveness of battlefield camouflage and deception but also achieves the rapid and accurate detection of military objects, thus promoting its application prospect.