Cognitive Task Analysis Research Articles

An applied cognitive task analysis investigation of professional judgement and decision-making in a small group of high-level, UK-based caving instructors

ABSTRACT The professional judgement and decision-making processes of adventure sports coaches’ leadership practice is a growing area of research. However, the PJDM and underpinning epistemology of caving instructors has recived limited research focus. The decision-making practice of professionals working in complex and constrained environments has significant transferability to domains such as rescue and emergency services. Consequently, this paper investigates the leadership practice of a purposive sample of 3 UK based caving instructors, utilising an Applied Cognitive Task Analysis to access expert cognition. The study aimed specifically to examine the decision-making processes of this sub-group of outdoor professionals who work in difficult, multifaceted and demanding environments. Results supported and built upon previous work in adventure sports, specifically in confirming the complexity of judgement and decision-making underground. In particular, decision-making creates high cognitive loads because of environmental factors inherent in extended caving journeys. Loads are assuaged by the application of heuristics and planning, but naturalistic decision-making processes remain numerous and multifaceted. Findings have implications for National Governing Body instructor training programme design, with particular reference to the development of decision-making expertise in complex environments.

Cognitive Task Analysis: Eliciting Expert Cognition in Context

Cognitive Task Analysis (CTA) is a powerful methodological approach that can enhance the rigorous elicitation and documentation of complex cognitive processes within interview-based qualitative research. We provide insights into this set of semi-structured interviewing techniques that we contend have much to offer management researchers who wish to understand the complexities of expert cognition within specific work-related tasks. Distinct from traditional semi-structured interview methods, CTA is designed to identify the knowledge requirements underpinning expertise in complex work domains. First, we present CTA as a robust approach to eliciting complex cognition and note why, when, and where management scholars might best use its techniques. Second, we provide two examples of how CTA methods have been used to research management; specifically, using the Critical Decision Method to explore management in high-stakes environments, and Applied Cognitive Task Analysis to explore global leadership. In ending, we propose greater use of this pragmatic approach in management research and highlight potential avenues for future research that will advance understanding of complex cognition at work.

Investigating and improving student understanding of the basics of quantum computing

Quantum information science and engineering (QISE) is a rapidly developing field that leverages the skills of experts from many disciplines to utilize the potential of quantum systems in a variety of applications. It requires talent from a wide variety of traditional fields, including physics, engineering, chemistry, and computer science, to name a few. To prepare students for such opportunities, it is important to give them a strong foundation in the basics of QISE, in which quantum computing plays a central role. In this study, we discuss the development, validation, and evaluation of a Quantum Interactive Learning Tutorial, on the basics and applications of quantum computing. These include an overview of key quantum mechanical concepts relevant to quantum computation (including ways a quantum computer is different from a classical computer), properties of single- and multiqubit systems, and the basics of single-qubit quantum gates. The tutorial uses guided inquiry-based teaching-learning sequences. Its development and validation involved conducting cognitive task analysis from both expert and student perspectives and using common student difficulties as a guide. For example, before engaging with the tutorial, after traditional lecture-based instruction, one reasoning primitive that was common in student responses is that a major difference between an N-bit classical and N-qubit quantum computer is that various things associated with a number N for a classical computer should be replaced with the number 2N for a quantum computer (e.g., 2N qubits must be initialized and 2N bits of information are obtained as the output of the computation on the quantum computer). This type of reasoning primitive also led many students to incorrectly think that there are only N distinctly different states available when computation takes place on a classical computer. Research suggests that this type of reasoning primitive has its origins in students learning that quantum computers can provide exponential advantage for certain problems, e.g., Shor’s algorithm for factoring products of large prime numbers, and that the quantum state during the computation can be in a superposition of 2N linearly independent states. The inquiry-based learning sequences in the tutorial provide scaffolding support to help students develop a functional understanding. The final version of the validated tutorial was implemented in two distinct courses offered by the physics department with slightly different student populations and broader course goals. Students’ understanding was evaluated after traditional lecture-based instruction on the requisite concepts and again after engaging with the tutorial. We analyze and discuss their improvement in performance on concepts covered in the tutorial. Published by the American Physical Society 2024

Unraveling the interplay between mental workload, occupational fatigue, physiological responses and cognitive performance in office workers

Recently, cognitive demands in workplaces have surged significantly. This study explored the intricate relationship among mental workload (MWL), occupational fatigue, physiological responses, and cognitive performance in office workers by using collective semi-parametric models. One hundred office workers were selected from twenty offices involved in cognitive performance. MWL was assessed through the NASA Task Load Index (NASA-TLX), and occupational fatigue was measured using the Persian version of the Swedish Occupational Fatigue Inventory. Physiological responses, including respiratory rate, the electrical conductivity of the skin (ECS), Heart Rate (HR), and other heart-related parameters, were recorded from the participants during a work shift. Selective and Divided Attention tests were chosen to evaluate workers' cognitive function based on cognitive task analysis. The mean of MWL and occupational fatigue scores were 66.28 ± 11.76 and 1.62 ± 1.07, respectively. There was a significant moderate correlation between two dimensions, mental demand (0.429) and frustration (0.409), with functional fatigue. Also, Significant and, of course, nonlinear relationships were observed between MWL and HR (R2 = 0.44, P-value < 0.001) and ECS (R2 = 0.45, P-value < 0.001) and reaction time in selected (R2 = 0.34, P-value < 0.001) and divided test (R2 = 0.48, P-value < 0.001). Similarly, nonlinear relationships were observed between physiological responses and cognitive performance with fatigue among participants who had experienced higher levels of occupational fatigue. The MWL and fatigue seem to have a significant and non-linear effect on physiological parameters such as HR and ECS and cognitive parameters such as reaction time. Moreover, MWL can influence the dimension of functional fatigue of workers.

Acceptability of a Mobile App (iMPAKT) for Measurement and Implementation of Person-Centredness: Mixed-Methods Study.

This study tested the acceptability of the iMPAKT App with end users. Cognitive task analysis and semi-structured interviews were used. Twelve participants took part. The majority of tasks were found to be easy to complete but issues were identified with a section of the app that provides Speech-To-Text transcription of patients speaking about their experience of care. Artificial Intelligence (AI) based systems may be needed to address these limitations. Overall views on acceptability of the app were positive and participants valued how it could be used to support practice improvement initiatives and large scale collection of person-centred measures.

Connecting pathogen transmission and healthcare worker cognition: a cognitive task analysis of infection prevention and control practices during simulated patient care

BackgroundRelatively little is known about the cognitive processes of healthcare workers that mediate between performance-shaping factors (eg, workload, time pressure) and adherence to infection prevention and control (IPC) practices. We...

Integrated Language and Science & Technology Instruction: A Cognitive Task Analysis of the Required Teacher Expertise

ABSTRACT Integrated language arts and science & technology (ILS&T) instruction can make learning more meaningful and improve student learning outcomes for both subjects. Although the literature has stressed that such integrated instruction presents pedagogical challenges for elementary school teachers, little is yet known about the specific characteristics of the required pedagogical repertoire. To gain a better understanding of the teacher knowledge and skills required for ILS&T instruction, a cognitive task analysis was conducted. This analysis resulted in a hierarchy consisting of the various required constituent teacher skills for ILS&T instruction. The cognitive task analysis also revealed what knowledge teachers rely on and identified the factors influencing the complexity of ILS&T instruction. The findings presented here contribute to our knowledge about what ILS&T instruction requires from teachers and can serve as a basis for the development of substantiated, 4C/ID-based teacher professional development trajectories. Furthermore, it provides valuable insight into the pros and cons of a relatively new, systematic way of analyzing teacher expertise.

Exploring the development of ‘understanding’ in high-level youth soccer players

ABSTRACT Background Developing understanding, and tactical understanding in particular, is an important goal for coaches in high-level youth sport. Deeper understanding can be associated with metacognition, which in soccer, is suggestive of players who can outwit the opponent by strategising. Although attractive, however, the construct is difficult to operationalise and hence, is seen as a challenging area, albeit a crucial one. Purposes This study tested how one team of under 13–14 academy players’ depth of understanding changed using a mixed methods approach with data collection over 18-months. Methods Players’ (n = 10) experienced a metacognitive coaching method, Digital Video Game Design (DVGD) throughout the study duration. Testing occurred on four occasions using Applied Cognitive Task Analysis (ACTA) to elicit how player thinking when playing evolved, combined with a Game Understanding (GU) comparative rating scale. In parallel, players’ coaches (n = 3) completed quantitative measurement of GU. Quantitative data analysis employed a repeated measures ANOVA whilst. Qualitative analysis of ACTA interviews used a deductive framework focussed on metacognitive skills and strategy. Findings Players’ depth of understanding significantly improved during and post exposure to the metacognitive coaching method. Post the initial intervention, understanding showed further improvements at a steady but not significant rate. Qualitative findings indicated that players’ metacognition became more sophisticated, with a particular improvement in strategising based on team mates and opponent’s capabilities. The most dominant metacognitive skills were planning and problem setting, whilst information gathering was least deployed. Conclusions Results show that young players are capable of rapidly developing metacognitive skills and strategy. Sports should upskill their coach education workforce to enhance their understanding of metacognition and its role within GU.

P9. Combating the Learning Curve for DIEP Flaps: Preliminary Results from a Cognitive Task Analysis Study

P9. Combating the Learning Curve for DIEP Flaps: Preliminary Results from a Cognitive Task Analysis Study

Task Analysis in Human-Computer Interaction: A Comparison between Four Task Analysis Techniques

Task analysis is an integral part of human-computer interaction, as it permits the client to comprehend, complete, and benefit from the utilization of an interaction system. Task analysis methodologies differ based on the selected approach and the motivation behind its use. The present study aims to compare several task analysis methodologies (i.e. hierarchical task analysis, cognitive task analysis, GOMS task analysis, and emotion task analysis), initially outlining their commonalities and distinctions in structure and usability. After that, it will go into each technique's benefits and drawbacks and how well-suited it is for different jobs. The main results that have been obtained by this research are: the HTA technique is an appropriate selection when the analysis seeks to explore the connections and interdependencies among different components of the task, whereas CTA is appropriate for the analysis that necessitates a technique with an undefined structure comprising of interviews. If the analysis system seeks to identify a cognitive process with a clearly defined structure, the GOMs technique can be a superb option. Lastly, when the task analysis aims to comprehend the emotional aspects of task performance, the ETA serves as an effective instrument to employ. In terms of usability, HTA is widely utilized in the fields of task assistance design and error prediction. CTA proves to be beneficial for tasks that demand sophisticated cognitive functions, GOMS is typically employed in the creation of training tools, the design of assist frameworks, and the documentation for clients, and ETA examines how users' psychological or emotional states influence their responses to tasks as they complete them. It is advised that readers go over this comparison paper in order to obtain a better knowledge of how to select the precise strategy that can aid in finishing an assignment.

The development of a model of decision-making during an act of serious violence using the Critical Decision Method

ABSTRACT To date, psychological theories of aggression have shown limited applicability to the first-hand experience of real-world violence. Examining the experiences of those directly involved in violent offending, may enable professionals to develop a strengthened and more refined understanding. The current study aimed to develop a theoretical model of offender experiences of decision-making, during the commission of a violent offence. The Critical Decision Method (CDM) for cognitive task analysis was conducted within a British prison, with nine participants who had been convicted of a serious violent offence. Interview transcripts were analysed using constructivist Grounded Theory (CGT). Seven themes were interpreted from participant narratives: (i) predisposing influences, (ii) environment, (iii) emotion, (iv) triggering events, (v) decision to act, (vi) identity and (vii) severity of harm caused to the victim. Participants’ narratives were found to focus upon a process of decision-making which followed a sequence of events, from the impact of early experiences, through to the in-the-moment decisions, that led to acting in a violent manner. This study provides novel insights into the experience of violent decision-making. Participants emphasised the role of emotion and identity. A range of clinical implications are discussed which highlight the important role of emotion regulation and identity transformation in the rehabilitation of violent offenders.

Sociotechnical feasibility of natural language processing-driven tools in clinical trial eligibility prescreening for Alzheimer's disease and related dementias.

Alzheimer's disease and related dementias (ADRD) affect over 55 million globally. Current clinical trials suffer from low recruitment rates, a challenge potentially addressable via natural language processing (NLP) technologies for researchers to effectively identify eligible clinical trial participants. This study investigates the sociotechnical feasibility of NLP-driven tools for ADRD research prescreening and analyzes the tools' cognitive complexity's effect on usability to identify cognitive support strategies. A randomized experiment was conducted with 60 clinical research staff using three prescreening tools (Criteria2Query, Informatics for Integrating Biology and the Bedside [i2b2], and Leaf). Cognitive task analysis was employed to analyze the usability of each tool using the Health Information Technology Usability Evaluation Scale. Data analysis involved calculating descriptive statistics, interrater agreement via intraclass correlation coefficient, cognitive complexity, and Generalized Estimating Equations models. Leaf scored highest for usability followed by Criteria2Query and i2b2. Cognitive complexity was found to be affected by age, computer literacy, and number of criteria, but was not significantly associated with usability. Adopting NLP for ADRD prescreening demands careful task delegation, comprehensive training, precise translation of eligibility criteria, and increased research accessibility. The study highlights the relevance of these factors in enhancing NLP-driven tools' usability and efficacy in clinical research prescreening. User-modifiable NLP-driven prescreening tools were favorably received, with system type, evaluation sequence, and user's computer literacy influencing usability more than cognitive complexity. The study emphasizes NLP's potential in improving recruitment for clinical trials, endorsing a mixed-methods approach for future system evaluation and enhancements.

Contextual design requirements for decision-support tools involved in weaning patients from mechanical ventilation in intensive care units

Weaning patients from ventilation in intensive care units (ICU) is a complex task. There is a growing desire to build decision-support tools to help clinicians during this process, especially those employing Artificial Intelligence (AI). However, tools built for this purpose should fit within and ideally improve the current work environment, to ensure they can successfully integrate into clinical practice. To do so, it is important to identify areas where decision-support tools may aid clinicians, and associated design requirements for such tools. This study analysed the work context surrounding the weaning process from mechanical ventilation in ICU environments, via cognitive task and work domain analyses. In doing so, both what cognitive processes clinicians perform during weaning, and the constraints and affordances of the work environment itself, were described. This study found a number of weaning process tasks where decision-support tools may prove beneficial, and from these a set of contextual design requirements were created. This work benefits researchers interested in creating human-centred decision-support tools for mechanical ventilation that are sensitive to the wider work system.

A cognitive task analysis of final year nursing students' situation awareness in simulated deteriorating patient events: A mixed methods study.

The aim of this study was to: (1) use cognitive task analysis to describe final year nursing students situation awareness in recognising, responding and escalating care of deteriorating patients in ward settings; and (2) make recommendations for training and practice. A mixed methods cognitive task analysis with a convergent triangulation design. Data collection involved observations of 33 final year nursing students in simulated deteriorating patient scenarios and retrospective cognitive interviews. A process tracing technique was applied to identify the cues to deterioration participants perceived; how cue perception altered as situational demands increased; the extent that participants made connections between perceived cues and reached a situational understanding; and the factors that influenced and constrained participants situation awareness. Qualitative and quantitative findings are woven together and presented using descriptive statistics, illustrative quotations and timeline extractions. The median cue perception was 65.4% and 57.6% in the medical and surgical scenarios, respectively. Perception was negatively influenced by incomplete vital sign monitoring as situations escalated; limited physical assessments; passive scanning behaviours; poor task automaticity; and excessive cognitive demands. Incomplete perception, poor cue integration and underdeveloped mental models influenced situational understanding. Escalation calls did not always accurately reflect situations and a reporting mindset was evident. Clinical exposure to deteriorating patients was described as variable and opportunistic. The study is reported in accordance with the Good Reporting of a Mixed Methods Study (GRAMMS) checklist. Patients and public were not involved in this research.

69. Combating The Learning Curve For DIEP Flaps: Preliminary Results From A Cognitive Task Analysis Study

69. Combating The Learning Curve For DIEP Flaps: Preliminary Results From A Cognitive Task Analysis Study

Cognitive task analysis-driven intelligent steering wheel interaction design

With the increasing levels of intelligence and automation, the relationship between humans and vehicles has evolved from a utilitarian perspective to a partnership. Among the crucial factors for enhancing user experiences are the analysis of driving tasks, the construction of user needs models, and the design of intelligent interfaces. Based on this background, this paper proposes a cognitive task analysis model using intelligent steering wheel information interaction design as the vehicle. The model aims to extract key design elements to assist designers in making design decisions, thereby improving the human-machine cooperation performance of intelligent automobiles and enhancing user perceptual experiences. Firstly, within the context of human-machine cooperation systems, a cognitive task analysis method integrating the SRK model is proposed. By analyzing the behavioral decision characteristics between the vehicle and the user, a framework for the human-machine interface (HMI) logic of the steering wheel and a dynamic layout prototype are established. Secondly, the design of the steering wheel’s HMI interaction is based on an analysis of users’ affective needs and rational physiological characteristics. This paper integrates the analysis of users’ affective needs to identify design elements that align with a high level of user satisfaction. Lastly, the design methodology model is applied to a navigation scenario, resulting in the creation of a steering wheel HMI prototype within a human-machine cooperation system. The prototype is then subjected to a combined subjective and objective experimental analysis, thereby validating the superiority of the steering wheel HMI’s detection indicators over those of the central control HMI and establishing the design pattern for the steering wheel HMI.

Get on the Round Dial: Fighter Pilot Strategies for Recovering Situation Awareness After Disorienting Physiological Events

Despite decades of research and training, adverse physiological events continue to present a significant risk to pilots. This paper describes a naturalistic study of fighter pilot experiences with disorienting physiological events such as gravity-induced loss of consciousness (G-LOC), hypoxia, and spatial disorientation. We conducted a cognitive task analysis with 10 experienced fighter pilots to elicit incidents in which the pilot or another pilot in the flight experienced a physiological event, exploring how they recognized something was wrong, assessed the level of impairment, and regained situation awareness. We describe cognitive requirements, specific cues and strategies, as well as complexities associated with managing these disorienting physiological events. Implications for decision support design and training are discussed.

Defining competencies in robotic thyroidectomy: development of a model assessing an expert operator's intraoperative performance skills and cognitive strategies.

The changing medical education environment emphasizes the need for time efficiency, increasing the demand for competency-based medical education to improve trainees' learning strategies. This study was performed to determine the competencies required for successful performance of robotic thyroidectomy (RT) and to determine the consensus of experts for performance of RT. Data were collected through 12 semi-structured interviews with RT experts and 11 field observations. Cognitive task analysis was performed to determine the competencies required for experts to perform RT. A modified Delphi methodology was used to determine how 20 experts rated the importance of each item of RT performance on a Likert 7-point scale. The criteria for the Delphi consensus were set at a Cronbach's α≥0.80 with two survey rounds. After 11 field observations and 12 semi-structured interviews, 89 items were identified within six modules. These items were grouped into sub-modules according to their theme. The modified Delphi survey, involving 21 experts, reached the consensus standard during the second round (Cronbach's α=0.954), enabling the identification of the 64 most important items within six modules related to RT performance: midline incision to isthmectomy (MID module; n=8), lateral dissection (LAT module; n=7), preservation of inferior parathyroid glands (INF module; n=16), preservation of recurrent laryngeal nerve and dissection of the ligament of Berry (BER module; n=21), dissection of the thyroid upper pole (SUP module; n=10), and specimen removal and closure (END module; n=2). This mixed-method study combining qualitative and quantitative methodology identified modules of core competencies required to perform RT. These modules can be used as a standard and objective guide to train surgeons to perform RT and evaluate outcomes.

Enhancing Cognitive and Readiness Skills: An Integrated Assessment of Perceptual and Memory Abilities for SLD students

Abstract: This study explores how cognitive and readiness skills in students with Specific Learning Disabilities (SLD) can be improved through an integrated assessment of their perceptual and memory abilities. SLD students often struggle with processing information, retaining knowledge, and preparing for tasks in academic environments. Recognizing the crucial link between perceptual and memory abilities is essential for tailoring interventions to support these students effectively. Utilizing a comprehensive assessment framework, the research aims to elucidate how perceptual and memory abilities influence cognitive processing and readiness skills in SLD students. It employs a variety of methodologies, including traditional psychometric measures and innovative approaches such as virtual reality simulations and cognitive task analyses, to offer a holistic perspective By integrating multiple methodologies, the study seeks to uncover the intricate interplay between perceptual and memory abilities and their impact on cognitive readiness among SLD students. The findings are expected to guide the development of targeted interventions and educational practices tailored to their unique needs. The implications of this research extend beyond academia, potentially informing the design of training programs and cognitive enhancement interventions for SLD students. By addressing their specific challenges, the study aims to foster inclusivity and equity in education. This research highlights the importance of assessing perceptual and memory abilities in SLD students to enhance their cognitive readiness and academic outcomes. By identifying factors contributing to their cognitive challenges, educators and practitioners can devise more effective strategies to support their learning and development.

Mapping the Discharge Process After Surgery

Care transition models are structured approaches used to ensure the smooth transfer of patients between health care settings or levels of care, but none currently are tailored to the surgical patient. Tailoring care transition models to the unique needs of surgical patients may lead to significant improvements in surgical outcomes and reduced care fragmentation. The first step to developing surgical care transition models is to understand the surgical discharge process. To map the surgical discharge process in a sample of US hospitals and identify key components and potential challenges specific to a patient's discharge after surgery. This qualitative study followed a cognitive task analysis framework conducted between January 1, 2022, and April 1, 2023, in Veterans Health Administration (VHA) hospitals. Observations (n = 16) of discharge from inpatient care after a surgical procedure were conducted in 2 separate VHA surgical units. Interviews (n = 13) were conducted among VHA health care professionals nationwide. Postoperative hospital discharge. Data were coded according to the principles of thematic analysis, and a swim lane process map was developed to represent the study findings. At the hospitals in this study, the discharge process observed for a surgical patient involved multidisciplinary coordination across the surgery team, nursing team, case managers, dieticians, social services, occupational and physical therapy, and pharmacy. Important components for a surgical discharge that were not incorporated in the current care transition models included wound care education and supplies; pain control; approvals for nonhome postdischarge locations; and follow-up plans for wounds, ostomies, tubes, and drains at discharge. Potential challenges to the surgical discharge process included social situations (eg, home environment and caregiver availability), team communication issues, and postdischarge care coordination. These findings suggest that current and ongoing studies of discharge care transitions for a patient after surgery should consider pain control; wounds, ostomies, tubes, and drains; and the impact of challenging social situations and interdisciplinary team coordination on discharge success.