PASSENGER RESPONSE TIME DATA-SETS FOR LARGE PASSENGER FERRIES AND CRUISE SHIPS DERIVED FROM SEA TRIALS

This paper describes research that was carried-out under the EU FP7 research project SAFEGUARD and presents passenger response time data generated from five full-scale semi-unannounced assembly trials at sea. The data-sets were generated from three different types of passenger ships, a RO-PAX ferry without cabins (RP1), a cruise ship (CS) and a RO-PAX ferry with cabins (RP2). In total, response times from 2366 people were collected making it the largest response time data-set ever collected – on land or sea. The analysis methodology used to extract the response time data and the resultant response time distributions (RTD) is presented. A number of key findings from the data analysis are presented along with three recommendations to modify the IMO guidelines governing ship evacuation analysis, namely; (a) it is inappropriate to use the same RTD for cruise ships and RO-PAX vessels; (b) a new Day Case RTD is suggested for RO-PAX vessels and (c) new Day and Night RTDs are suggested for cruise ships.

Analysis of speed-accuracy trade-offs using the Wiener diffusion model for choice reaction times

A methodology review paper on the utility and challenges of modelling speed-accuracy trade-offs in response time data. The paper reviews the importance of accounting for speed-accuracy trade-offs when measuring response times, and provides background on diffusion models for response time data. It then describes a practical software implementation of the EZ-diffusion model to model speed-accuracy trade-offs in choice response time data using the R programming language.

Application of Change Point Analysis of Response Time Data to Detect Test Speededness

Computer-based and web-based testing have become increasingly popular in recent years. Their popularity has dramatically expanded the availability of response time data. Compared to the conventional item response data that are often dichotomous or polytomous, response time has the advantage of being continuous and can be collected in an unobstrusive manner. It therefore has great potential to improve many measurement activities. In this paper, we propose a change point analysis (CPA) procedure to detect test speededness using response time data. Specifically, two test statistics based on CPA, the likelihood ratio test and Wald test, are proposed to detect test speededness. A simulation study has been conducted to evaluate the performance of the proposed CPA procedure, as well as the use of asymptotic and empirical critical values. Results indicate that the proposed procedure leads to high power in detecting test speededness, while keeping the false positive rate under control, even when simplistic and liberal critical values are used. Accuracy of the estimation of the actual change point, however, is highly dependent on the true change point. A real data example is also provided to illustrate the utility of the proposed procedure and its contrast to the response-only procedure. Implications of the findings are discussed at the end.

Investigating the role of attention in the identification of associativity shortcuts using a microgenetic measure of implicit shortcut use

Many mathematics problems can be solved in different ways or by using different strategies. Good knowledge of arithmetic principles is important for identifying and using strategies that are more sophisticated. For example, the problem “6 + 38 − 35” can be solved through a shortcut strategy where the subtraction “38 − 35 = 3” is performed before the addition “3 + 6 = 9,” a strategy that is derived from the arithmetic principle of associativity. However, both children and adults make infrequent use of this shortcut and the reasons for this are currently unknown. To uncover these reasons, new sensitive measures of strategy identification and use must first be developed, which was one goal of our research. We built a novel method to detect the time-point when individuals first identify an arithmetic strategy, based on trial-by-trial response time data. Our second goal was to use this measure to investigate the contribution of one particular factor, attention, in the identification of the associativity shortcut. In two studies, we found that manipulating visual attention made no difference to the number of people who identified the shortcut, the trial number on which they first identified it, or their accuracy and response time for solving shortcut problems. We discuss the theoretical and methodological contribution of our findings and argue that the origin of people’s difficulty with associativity shortcuts may lie beyond attention.