A framework for guiding the learning of ultrasound scanning

Ultrasound scanning is provided by a range of health professionals who need to be trained to a proficient level. In respect of education and training in ultrasound scanning, little attention has been given to how scanning skills are acquired and what assists and hinders the learning process. This study aims to develop a framework for guiding learning in ultrasound scanning. Overt participant observation and semi-structured interviews generated data on four learners undertaking a 12-month postgraduate ultrasound programme. Narrative analysis of the interview data was used to reveal dominant themes related to stages in learning to scan. Dominant themes associated with learning to scan were; communication with the patient, navigation skills, image interpretation skills, observation of practice, feedback on performance, random practise. Detailed interpretation of the themes through narrative analysis provided characteristics of learning for each stage of a four staged process. This study provides an insight into the key features of scan performance and how scanning skills are acquired over a four staged approach. These themes and characteristics are presented in a framework for guiding learning in ultrasound scanning

Human performance and strategies while solving an aircraft routing and sequencing problem: an experimental approach

As airport resources are stretched to meet increasing demand for services, effective use of ground infrastructure is increasingly critical for ensuring operational efficiency. Work in operations research has produced algorithms providing airport tower controllers with guidance on optimal timings and sequences for flight arrivals, departures, and ground movement. While such decision support systems have the potential to improve operational efficiency, they may also affect users’ mental workload, situation awareness, and task performance. This work sought to identify performance outcomes and strategies employed by human decision makers during an experimental airport ground movement control task with the goal of identifying opportunities for enhancing user-centered tower control decision support systems. To address this challenge, thirty novice participants solved a set of vehicle routing problems presented in the format of a game representing the airport ground movement task practiced by runway controllers. The games varied across two independent variables, network map layout (representing task complexity) and gameplay objective (representing task flexibility), and verbal protocol, visual protocol, task performance, workload, and task duration were collected as dependent variables. A logistic regression analysis revealed that gameplay objective and task duration significantly affected the likelihood of a participant identifying the optimal solution to a game, with the likelihood of an optimal solution increasing with longer task duration and in the less flexible objective condition. In addition, workload appeared unaffected by either independent variable, but verbal protocols and visual observations indicated that high-performing participants demonstrated a greater degree of planning and situation awareness. Through identifying human behavior during optimization problem solving, the work of tower control can be better understood, which, in turn, provides insights for developing decision support systems for ground movement management

Trust in an autonomously driven simulator and vehicle performing maneuvers at a T-junction with and without other vehicles

Autonomous vehicle (AV) technology is developing rapidly. Level 3 automation assumes the user might need to respond to requests to retake control. Levels 4 (high automation) and 5 (full automation) do not require human monitoring of the driving task or systems [1]: the AV handles driving functions and makes decisions based on continuously updated information. A gradual switch in the role of the human within the vehicle from active controller to passive passenger comes with uncertainty in terms of trust, which will likely be a key barrier to acceptability, adoption and continued use [2]. Few studies have investigated trust in AVs and these have tended to use driving simulators with Level 3 automation [3, 4]. The current study used both a driving simulator and autonomous road vehicle. Both were operating at Level 3 autonomy although did not require intervention from the user; much like Level 4 systems. Forty-six participants completed road circuits (UK-based) with both platforms. Trust was measured immediately after different types of turns at a priority T-junction, increasing in complexity: e.g., driving left or right out of a T-junction; turning right into a T-junction; presence of oncoming/crossing vehicles. Trust was high across platforms: higher in the simulator for some events and higher in the road AV for others. Generally, and often irrespective of platform, trust was higher for turns involving an oncoming/crossing vehicle(s) than without traffic, possibly because the turn felt more controlled as the simulator and road AVs always yielded, resulting in a delayed maneuver. We also found multiple positive relationships between trust in automation and technology, and trust ratings for most T-junction turn events across platforms. The assessment of trust was successful and the novel findings are important to those designing, developing and testing AVs with users in mind. Undertaking a trial of this scale is complex and caution should be exercised about over-generalizing the findings

Development of a Situation Awareness Assessment Tool for Rail Signalers

Situation awareness (SA) is of utmost importance for the signaler as part of the infrastructure management in railway operations. However, in previous studies assessing signaler SA, a good performance was accompanied by mediocre results for SA. This unexpected result can be explained using the theory of situated SA, which posits that operators store knowledge important for situation awareness internally as well as externally in the work environment. To further investigate whether the theory of situated SA can be applied in rail signaling, an assessment tool for signaler SA was developed. Furthermore, by applying the developed assessment tool, it can be investigated which factors determine if information is stored externally or internally. Knowing which information signalers store where will help to develop more precise measures to assess and support signaler SA, ensuring a better performance of these crucial operators in the safety and efficiency of the railway system