It's what you do and the way that you do it:team task, team size, and innovation-related group processes

This article describes a study of the relationships between team inputs (task type and team size) and team processes in 87 cross industry Portuguese teams, some of which had high and some low requirements to innovate. Team processes were measured using the Team Climate Inventory (TCI), which focuses on clarity of and commitment to team objectives, levels of participation, support for innovation, and quality emphases. Three hypotheses were tested. The first proposed that teams carrying out tasks with a high innovation requirement would have high scores on a measure of team processes. This was supported insofar as such teams reported higher levels of participation and support for innovation. The second hypothesis proposed that large teams would have poorer team processes. This hypothesis was confirmed. The third hypothesis concerned the interaction between size and innovation. The results suggested that large teams operating under a relatively high pressure to innovate have poorer team processes than large teams that do not have a high requirement to innovate.

Types of task, types of audience, types of actor: interactions between mere presence and personality type in a simple mathematical task

Research into social facilitation effects reveals three factors affecting response performance: types of task, types of audience and type of actor. This study attempts to establish a minimal baseline for task and audience type in order to examine difference between personality types in the actors. Results indicate that performance in both extraverts and introverts increases in the minimal conditions of the mere presence of another person whilst carrying out a simple mathematical task. These results are interpreted through an analysis of Zajonc's (1965) drive theory with Eysenck's (1967) personality theory indicating that through further investigation performance curves might be devised for introverts and extraverts performing under a variety of task and audience conditions.

Task classification and decision processes in monitoring behaviour

Task classification is introduced as a method for the evaluation of monitoring behaviour in different task situations. On the basis of an analysis of different monitoring tasks, a task classification system comprising four task 'dimensions' is proposed. The perceptual speed and flexibility of closure categories, which are identified with signal discrimination type, comprise the principal dimension in this taxonomy, the others being sense modality, the time course of events, and source complexity. It is also proposed that decision theory provides the most complete method for the analysis of performance in monitoring tasks. Several different aspects of decision theory in relation to monitoring behaviour are described. A method is also outlined whereby both accuracy and latency measures of performance may be analysed within the same decision theory framework. Eight experiments and an organizational study are reported. The results show that a distinction can be made between the perceptual efficiency (sensitivity) of a monitor and his criterial level of response, and that in most monitoring situations, there is no decrement in efficiency over the work period, but an increase in the strictness of the response criterion. The range of tasks exhibiting either or both of these performance trends can be specified within the task classification system. In particular, it is shown that a sensitivity decrement is only obtained for 'speed' tasks with a high stimulation rate. A distinctive feature of 'speed' tasks is that target detection requires the discrimination of a change in a stimulus relative to preceding stimuli, whereas in 'closure' tasks, the information required for the discrimination of targets is presented at the same point In time. In the final study, the specification of tasks yielding sensitivity decrements is shown to be consistent with a task classification analysis of the monitoring literature. It is also demonstrated that the signal type dimension has a major influence on the consistency of individual differences in performance in different tasks. The results provide an empirical validation for the 'speed' and 'closure' categories, and suggest that individual differences are not completely task specific but are dependent on the demands common to different tasks. Task classification is therefore shovn to enable improved generalizations to be made of the factors affecting 1) performance trends over time, and 2) the consistencv of performance in different tasks. A decision theory analysis of response latencies is shown to support the view that criterion shifts are obtained in some tasks, while sensitivity shifts are obtained in others. The results of a psychophysiological study also suggest that evoked potential latency measures may provide temporal correlates of criterion shifts in monitoring tasks. Among other results, the finding that the latencies of negative responses do not increase over time is taken to invalidate arousal-based theories of performance trends over a work period. An interpretation in terms of expectancy, however, provides a more reliable explanation of criterion shifts. Although the mechanisms underlying the sensitivity decrement are not completely clear, the results rule out 'unitary' theories such as observing response and coupling theory. It is suggested that an interpretation in terms of the memory data limitations on information processing provides the most parsimonious explanation of all the results in the literature relating to sensitivity decrement. Task classification therefore enables the refinement and selection of theories of monitoring behaviour in terms of their reliability in generalizing predictions to a wide range of tasks. It is thus concluded that task classification and decision theory provide a reliable basis for the assessment and analysis of monitoring behaviour in different task situations.

Experiments and observations on the behaviour and brain of the aging female mouse with special reference to dementia of the Alzheimer type

The objective of this research was to investigate the effects of normal aging and the additional effects of chronic exposure to two experimental diets, one enriched in aluminium, the other enriched in lecithin, on aspects of the behaviour and brain histology of the female mouse. The aluminium diet was administered in an attempt to develop a rodent model of Dementia of the Alzheimer Type (DAT). With normal aging, almost all assessed aspects of behaviour were found to be impaired. As regards cognition, selective impairments of single-trial passive avoidance and Morris place learning were observed. While all aspects of open-field behaviour were impaired, the degree of impairment was directly related to the degree of motoric complexity. Deficits were also observed on non-visual sensorimotor coordination tasks and in olfactory discrimination. Histologically, neuron loss, gliosis, vacuolation and congophilic angiopathy were observed in several of the brain regions/fibre tracts believed to contribute to the control of some of the assessed behaviours. The aluminium treatment had very selective effects on both behaviour and brain histology, inducing several features observed in DAT. Behaviourally, the treatment induced impaired spatial reference memory; reduced ambulation; disturbed olfactory function and induced the premature development of the senile pattern of swimming. Histologically, significant neuron loss and gliosis were observed in the hippocampus, entorhinal cortex, amygdala, medial septum, pyriform and pr-frontal cortex. In addition, the brain distribution of congophilic angiopathy was significantly increased by the treatment. The lecithin treatment had effects on both non-cognitive and cognitive aspects of behaviour. The effects of aging on open-field ambulation and rearing were partially ameliorated by the treatment. A similar effect was observed for single-trial passive avoidance performance. Age-dependent improvements in acquisition/retention were observed in 17-23 month mice and Morris place task performance was improved in 11 and 17 month mice. Histologically, a partial sparing of neurons in the cerebellum, hippocampus, entorhinal cortex and subiculum was observed.

Evolution of competing strategies in a threshold model for task allocation

A nature inspired decentralised multi-agent algorithm is proposed to solve a problem of distributed task allocation in which cities produce and store batches of different mail types. Agents must collect and process the mail batches, without global knowledge of their environment or communication between agents. The problem is constrained so that agents are penalised for switching mail types. When an agent process a mail batch of different type to the previous one, it must undergo a change-over, with repeated change-overs rendering the agent inactive. The efficiency (average amount of mail retrieved), and the flexibility (ability of the agents to react to changes in the environment) are investigated both in static and dynamic environments and with respect to sudden changes. New rules for mail selection and specialisation are proposed and are shown to exhibit improved efficiency and flexibility compared to existing ones. We employ a evolutionary algorithm which allows the various rules to evolve and compete. Apart from obtaining optimised parameters for the various rules for any environment, we also observe extinction and speciation.

Learning task specific distributed paragraph representations using a 2-tier convolutional neural network

We introduce a type of 2-tier convolutional neural network model for learning distributed paragraph representations for a special task (e.g. paragraph or short document level sentiment analysis and text topic categorization). We decompose the paragraph semantics into 3 cascaded constitutes: word representation, sentence composition and document composition. Specifically, we learn distributed word representations by a continuous bag-of-words model from a large unstructured text corpus. Then, using these word representations as pre-trained vectors, distributed task specific sentence representations are learned from a sentence level corpus with task-specific labels by the first tier of our model. Using these sentence representations as distributed paragraph representation vectors, distributed paragraph representations are learned from a paragraph-level corpus by the second tier of our model. It is evaluated on DBpedia ontology classification dataset and Amazon review dataset. Empirical results show the effectiveness of our proposed learning model for generating distributed paragraph representations.

Perception while watching movies:effects of physical screen size and scene type

Over the last decade, television screens and display monitors have increased in size considerably, but has this improved our televisual experience? Our working hypothesis was that the audiences adopt a general strategy that “bigger is better.” However, as our visual perceptions do not tap directly into basic retinal image properties such as retinal image size (C. A. Burbeck, 1987), we wondered whether object size itself might be an important factor. To test this, we needed a task that would tap into the subjective experiences of participants watching a movie on different-sized displays with the same retinal subtense. Our participants used a line bisection task to self-report their level of “presence” (i.e., their involvement with the movie) at several target locations that were probed in a 45-min section of the movie “The Good, The Bad, and The Ugly.” Measures of pupil dilation and reaction time to the probes were also obtained. In Experiment 1, we found that subjective ratings of presence increased with physical screen size, supporting our hypothesis. Face scenes also produced higher presence scores than landscape scenes for both screen sizes. In Experiment 2, reaction time and pupil dilation results showed the same trends as the presence ratings and pupil dilation correlated with presence ratings, providing some validation of the method. Overall, the results suggest that real-time measures of subjective presence might be a valuable tool for measuring audience experience for different types of (i) display and (ii) audiovisual material.

The influence of memory in a threshold model for distributed task assignment

A nature inspired decentralised multi-agent algorithm is proposed to solve a problem of distributed task selection in which cities produce and store batches of different mail types. Agents must collect and process the mail batches, without a priori knowledge of the available mail at the cities or inter-agent communication. In order to process a different mail type than the previous one, agents must undergo a change-over during which it remains inactive. We propose a threshold based algorithm in order to maximise the overall efficiency (the average amount of mail collected). We show that memory, i.e. the possibility for agents to develop preferences for certain cities, not only leads to emergent cooperation between agents, but also to a significant increase in efficiency (above the theoretical upper limit for any memoryless algorithm), and we systematically investigate the influence of the various model parameters. Finally, we demonstrate the flexibility of the algorithm to changes in circumstances, and its excellent scalability.

Speech and non-speech stimuli in the prediction of early reading skills:the influence of processing demands and response-type

Purpose: Both phonological (speech) and auditory (non-speech) stimuli have been shown to predict early reading skills. However, previous studies have failed to control for the level of processing required by tasks administered across the two levels of stimuli. For example, phonological tasks typically tap explicit awareness e.g., phoneme deletion, while auditory tasks usually measure implicit awareness e.g., frequency discrimination. Therefore, the stronger predictive power of speech tasks may be due to their higher processing demands, rather than the nature of the stimuli. Method: The present study uses novel tasks that control for level of processing (isolation, repetition and deletion) across speech (phonemes and nonwords) and non-speech (tones) stimuli. 800 beginning readers at the onset of literacy tuition (mean age 4 years and 7 months) were assessed on the above tasks as well as word reading and letter-knowledge in the first part of a three time-point longitudinal study. Results: Time 1 results reveal a significantly higher association between letter-sound knowledge and all of the speech compared to non-speech tasks. Performance was better for phoneme than tone stimuli, and worse for deletion than isolation and repetition across all stimuli. Conclusions: Results are consistent with phonological accounts of reading and suggest that level of processing required by the task is less important than stimuli type in predicting the earliest stage of reading.

What drives the prediction of early reading? An analysis of stimulus and response-type

Purpose: Phonological accounts of reading implicate three aspects of phonological awareness tasks that underlie the relationship with reading; a) the language-based nature of the stimuli (words or nonwords), b) the verbal nature of the response, and c) the complexity of the stimuli (words can be segmented into units of speech). Yet, it is uncertain which task characteristics are most important as they are typically confounded. By systematically varying response-type and stimulus complexity across speech and non-speech stimuli, the current study seeks to isolate the characteristics of phonological awareness tasks that drive the prediction of early reading. Method: Four sets of tasks were created; tone stimuli (simple non-speech) requiring a non-verbal response, phonemes (simple speech) requiring a non-verbal response, phonemes requiring a verbal response, and nonwords (complex speech) requiring a verbal response. Tasks were administered to 570 2nd grade children along with standardized tests of reading and non-verbal IQ. Results: Three structural equation models comparing matched sets of tasks were built. Each model consisted of two 'task' factors with a direct link to a reading factor. The following factors predicted unique variance in reading: a) simple speech and non-speech stimuli, b) simple speech requiring a verbal response but not simple speech requiring a non-verbal-response, and c) complex and simple speech stimuli. Conclusions: Results suggest that the prediction of reading by phonological tasks is driven by the verbal nature of the response and not the complexity or 'speechness' of the stimuli. Findings highlight the importance of phonological output processes to early reading.

Deconstructing phonological tasks:the contribution of stimulus and response type to the prediction of early decoding skills

Abstract Phonological tasks are highly predictive of reading development but their complexity obscures the underlying mechanisms driving this association. There are three key components hypothesised to drive the relationship between phonological tasks and reading; (a) the linguistic nature of the stimuli, (b) the phonological complexity of the stimuli, and (c) the production of a verbal response. We isolated the contribution of the stimulus and response components separately through the creation of latent variables to represent specially designed tasks that were matched for procedure. These tasks were administered to 570 6 to 7-year-old children along with standardised tests of regular word and non-word reading. A structural equation model, where tasks were grouped according to stimulus, revealed that the linguistic nature and the phonological complexity of the stimulus predicted unique variance in decoding, over and above matched comparison tasks without these components. An alternative model, grouped according to response mode, showed that the production of a verbal response was a unique predictor of decoding beyond matched tasks without a verbal response. In summary, we found that multiple factors contributed to reading development, supporting multivariate models over those that prioritize single factors. More broadly, we demonstrate the value of combining matched task designs with latent variable modelling to deconstruct the components of complex tasks.