Seeing the woods for the trees: the problem of information inefficiency and information overload on operator performance

One of the recurring questions in designing dynamic control environments is whether providing more information leads to better operational decisions. The idea of having every piece of information and increasing situation awareness is so tempting (and in safety critical domains often mandatory) that has become an obstacle for designers and operators. This research examined this challenge within a railway control setting. A laboratory study was conducted to investigate the presentation of different levels of information (taken from data processing framework, Dadashi et al., 2014) and the association with, and potential prediction of, the performance of a human operator when completing a cognitively demanding problem solving scenario within railways. Results indicated that presenting users with information corresponding to their cognitive task (and no more) improves the performance of their problem solving/alarm handling. Knowing the key features of interest to various agents (machine or human) and using the data processing framework to guide the optimal level of information required by each of these agents could potentially lead to safer and more usable designs

Harnessing Technology: new modes of technology-enhanced learning: opportunities and challenges

A report commissioned by Becta to explore the potential impact on education, staff and learners of new modes of technology enhanced learning, envisaged as becoming available in subsequent years. A generative framework, developed by the researchers is described, which was used as an analytical tool to relate the possibilities of the technology described to learning and teaching activities. This report is part of the curriculum and pedagogy strand of Becta's programme of managed research in support of the development of Harnessing Technology: Next Generation Learning 2008-14. A system-wide strategy for technology in education and skills. Between April 2008 and March 2009, the project carried out research, in three iterative phases, into the future of learning with technology. The research has drawn from, and aims to inform, all UK education sectors

Modelling decision-making within rail maintenance control rooms

This paper presents a cognitive task analysis to derive models of decision-making for rail maintenance processes. Maintenance processes are vital for safe and continuous availability of rail assets and services. These processes are increasingly embracing the ‘Intelligent Infrastructure’ paradigm, which uses automated analysis to predict asset state and potential failure. Understanding the cognitive processes of maintenance operators is critical to underpin design and acceptance of Intelligent Infrastructure. A combination of methods, including observation, interview and an adaptation of critical decision method, was employed to elicit the decision-making strategies of operators in three different types of maintenance control centre, with three configurations of pre-existing technology. The output is a model of decision-making, based on Rasmussen’s decision ladder, that reflects the varying role of automation depending on technology configurations. The analysis also identifies which types of fault were most challenging for operators and identifies the strategies used by operators to manage the concurrent challenges of information deficiencies (both underload and overload). Implications for design are discussed

Using widgets to provide portable services for IMS Learning Design

Since the publication of the IMS LD specification it has been recognised that the lack of a rich set of runtime services is a major barrier to adoption. The approaches taken to resolving this problem are reviewed, and their strengths and limitations identified. A generic widget server developed by the authors is described. Integration of the widget server with the IMS LD runtime system provides an extensible set of services. This has been demonstrated with the creation of widgets for forums, messaging, vote, and Google maps which are provided for users within the context of their role and activities in a Unit of Learning. Authoring and administration are described, showing how the system is both extensible and portable

Seeing the woods for the trees: the problem of information inefficiency and information overload on operator performance

One of the recurring questions in designing dynamic control environments is whether providing more information leads to better operational decisions. The idea of having every piece of information and increasing situation awareness is so tempting (and in safety critical domains often mandatory) that has become an obstacle for designers and operators. This research examined this challenge within a railway control setting. A laboratory study was conducted to investigate the presentation of different levels of information (taken from data processing framework, Dadashi et al., 2014) and the association with, and potential prediction of, the performance of a human operator when completing a cognitively demanding problem solving scenario within railways. Results indicated that presenting users with information corresponding to their cognitive task (and no more) improves the performance of their problem solving/alarm handling. Knowing the key features of interest to various agents (machine or human) and using the data processing framework to guide the optimal level of information required by each of these agents could potentially lead to safer and more usable designs

Development of a technique for predicting the human response to an emergency situation

This paper presents development work on a new approach for predicting the human response to an emergency situation. The study builds upon an initial investigation in which 20 participants were asked to predict what actions they would take in the event of a domestic fire [1]. The development work involved a retest with an additional 20 participants to investigate the reliability of the approach. Furthermore, the analysis procedure was improved such that the results represented more accurately those which could be obtained from practical application of the approach. As found in the initial investigation, the frequencies and sequences of the reported acts had significant relationships with a study of behavior in real fires [2] (Spearman’s rho: 0.323, N=55, p<0.05) and (Spearman’s rho: 0.340, N=37, p<0.05), respectively. Further development work is required, but the results indicate that the approach may have use for predicting human behavior in emergencies

Design Requirements for Effective Hybrid Decision Making with Evolvable Assembly Systems

This paper examines 10 challenges for making automation a team player (Klein et al., 2004) in the context of Evolvable Assembly Systems (EAS) with the aim of delivering requirements for effective hybrid human-automation decision making. Specific decision making use cases for a demonstrator system were analysed to capture opportunities and requirements for effective human-agent cooperative decision making. These requirements covered agent design, human-machine interface design, context aware computing requirements and human competency. As such, the paper provides concrete examples of how general principles for hybrid decision making can be applied to EAS, and presents a pilot of a method for future requirements elicitation