Learning to drive: learners' self-reported cognitive failure level predicts driving instructor's observation rating of driving performance

OBJECTIVES Evidence increases that cognitive failure may be used to screen for drivers at risk. Until now, most studies have relied on driving learners. This exploratory pilot study examines self-report of cognitive failure in driving beginners and error during real driving as observed by driving instructors. METHODS Forty-two driving learners of 14 driving instructors filled out a work-related cognitive failure questionnaire. Driving instructors observed driving errors during the next driving lesson. In multiple linear regression analysis, driving errors were regressed on cognitive failure with the number of driving lessons as an estimator of driving experience controlled. RESULTS Higher cognitive failure predicted more driving errors (p < .01) when age, gender and driving experience were controlled in analysis. CONCLUSIONS Cognitive failure was significantly associated with observed driving errors. Systematic research on cognitive failure in driving beginners is recommended.

Learning real-world stimuli in a neural network with spike-driven synaptic dynamics

We present a model of spike-driven synaptic plasticity inspired by experimental observations and motivated by the desire to build an electronic hardware device that can learn to classify complex stimuli in a semisupervised fashion. During training, patterns of activity are sequentially imposed on the input neurons, and an additional instructor signal drives the output neurons toward the desired activity. The network is made of integrate-and-fire neurons with constant leak and a floor. The synapses are bistable, and they are modified by the arrival of presynaptic spikes. The sign of the change is determined by both the depolarization and the state of a variable that integrates the postsynaptic action potentials. Following the training phase, the instructor signal is removed, and the output neurons are driven purely by the activity of the input neurons weighted by the plastic synapses. In the absence of stimulation, the synapses preserve their internal state indefinitely. Memories are also very robust to the disruptive action of spontaneous activity. A network of 2000 input neurons is shown to be able to classify correctly a large number (thousands) of highly overlapping patterns (300 classes of preprocessed Latex characters, 30 patterns per class, and a subset of the NIST characters data set) and to generalize with performances that are better than or comparable to those of artificial neural networks. Finally we show that the synaptic dynamics is compatible with many of the experimental observations on the induction of long-term modifications (spike-timing-dependent plasticity and its dependence on both the postsynaptic depolarization and the frequency of pre- and postsynaptic neurons).

Projecting a relevant "next": Instruction sequences in driving lessons

Car interaction and the organisation of multi-activity in cars have become a fertile topic of research within CA and EM (Laurier 2005, Haddington & Keisanen 2009). While previous research has focused exclusively on everyday car rides, in this paper we will analyse a specific kind of car interaction, namely driving lessons. In addition to"driving" and"talking", as the two main parallel activities in everyday car rides (Mondada in press), in driving lessons a central activity is"instructing", that we understand to be a collaborative accomplishment (Sanchez Svensson et al. 2009). Drawing on a corpus of 7 video-recorded driving lessons, we will analyse the sequential organisation of"instruction sequences", i.e. of those actions that are initiated by the driving instructor with a turn projecting the next relevant action to be executed by the learner. Learners carry out next actions in two different ways: a) as"single" actions (e.g. using the indicator); b) as a complex series of overlapping or parallel actions. We will show that"single" actions occur as responses to instructions concerning the learner's command of the car, while complex actions occur when the instructors formulate direction indications. The aims of our analyses are twofold. Firstly, we will analyse how instruction sequences are fitted to the emerging contingencies of the car ride (movement in space, changing environment): we will show that a) the turn format of the instruction initiation displays the degree of"urgency" of the requested action; b) learners have the possibility to start the relevant"next" before the instruction initiation comes to completion. Secondly, we will focus on those"seconds" that the driving instructor treats as problematic by initiating a repair sequence (e.g. an improper use of the indicator). Our research contributes to the discussion about the multimodal resources that participants can employ to fulfil a projected action. In addition, it offers insights in a hitherto scarcely investigated topic, namely the organisation of instructions and the ecology of apprenticeship. References HADDINGTON, P. & KEISANEN, T. (2009) Location, mobility and the body as resources in selecting a route. Journal of Pragmatics 41 (10), 1938-1961. LAURIER, Eric (2005): Searching for a parking space. Intellectica 41-42/2-3: 101-116. MONDADA, Lorenza (in press). Talking and driving: multi-activity in the car. Semiotica. SANCHEZ SVENSSON, M. et al. (2009) "Embedding instruction in practice: contingency and collaboration during surgical training", Sociology of Health & Illness, 31/6: 889-906.

An exploratory study about the perception and justification of violence in Mixed Martial Arts and kickboxing athletes

THE INFLUENCE of combat sport practice on behaviour, attitude, personality and other factors was, and still remains, a research topic of great interest as well as conflicting points of view. Findings are as yet inconclusive since a direct or causal effect is difficult to establish and other factors external to the individual, such as the instructor’s coaching style, also need to be taken into consideration. Furthermore, the wide range of disciplines pertaining to the category combat sports differ from each other on a number of characteristics, such as the extent of physical contact or competition rules, and in fact, attempts have been made to distinguish between various sub-types (e.g. Trulson, 1986). A common distinction made is that between the traditional martial arts, which place emphasis on the art’s philosophy, its traditions and hierarchy (e.g. traditional karate, aikido) and the modern (or Western) combat sports (e.g. boxing, Mixed Martial Arts). An ongoing debate exists about the potential positive and/or negative influence of combat sport practice in comparison to other sport disciplines that do not include this element of fighting and direct aggression. On the one hand, combat sports have been presented by some researchers and sport practitioners as a means of promoting positive social and individual behavior, such as in Theeboom, De Knop and Wylleman’s (2008) evaluation of a martial arts Programme for socially disadvantaged youths in Belgium. Results revealed a positive effect of this project; however, it also highlighted the crucial role played by the instructors or leaders of such programmes. In another intervention using martial arts, Trulson (1986) reported a positive effect of a six month traditional martial art (Korean Tae Kwon Do) intervention with male juvenile delinquents including a reduction in aggressiveness and anxiety, thus confirming the positive influence of such an activity. Nevertheless, this effect was not observed in the other group participating in a modern Adaptation of this martial art led by the same instructor, where the philosophical aspect of this discipline was not emphasised. Moreover, an opposite effect was ascertained in this case where an increased tendency towards delinquency was reported. These results support the distinction between the various types of combat sports together with the way this sport is presented and taught by the instructor.

Decision Support Models for Composing and Navigating through e-Learning Objects

Libraries of learning objects may serve as basis for deriving course offerings that are customized to the needs of different learning communities or even individuals. Several ways of organizing this course composition process are discussed. Course composition needs a clear understanding of the dependencies between the learning objects. Therefore we discuss the metadata for object relationships proposed in different standardization projects and especially those suggested in the Dublin Core Metadata Initiative. Based on these metadata we construct adjacency matrices and graphs. We show how Gozinto-type computations can be used to determine direct and indirect prerequisites for certain learning objects. The metadata may also be used to define integer programming models which can be applied to support the instructor in formulating his specifications for selecting objects or which allow a computer agent to automatically select learning objects. Such decision models could also be helpful for a learner navigating through a library of learning objects. We also sketch a graph-based procedure for manual or automatic sequencing of the learning objects.