811 resultados para Analyzing human behavior


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We are soon approaching the pervasive-era ofcomputing, where computers are embedded intoobjects and the environment in order to provide newservices to users. Significant levels of data arerequired in order for these services to function asintended, and it is this collection of data which werefer to as ubiquitous monitoring. Existing monitoringtechniques have often been known to cause undesirableeffects, and it is anticipated that ubiquitousmonitoring, with its increased coverage, will lead toincreases in their occurrence and impact. To date, theeffects of ubiquitous monitoring on human behaviourhave not been sufficiently investigated, furtherincreasing the risk of undesirable effects. We propose apreliminary model consisting of a series of factorsbelieved to influence human behavior and augmentedby the Theory of Planned Behaviour. This model mayallow us to understand, predict, and therefore preventany undesirable effects caused by ubiquitousmonitoring.

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Previous studies of ignorance-driven decision-making have either analyzed when ignorance should prove advantageous on theoretical grounds, or else they have examined whether human behavior is consistent with an ignorance driven inference strategy (e.g., the recognition heuristic). The current study merges these research goals by examining whether – under conditions where ignorance driven inference might be expected – the type of advantages theoretical analyses predict are evident in human performance data. A single experiment shows that, when asked to make relative wealth judgments, participants reliably use recognition as a basis for their judgments. Their wealth judgments under these conditions are reliably more accurate when some of the target names are unknown than when participants recognize all the names (the “less-is-more effect”). these data are robust against a number of variations on the size of the pool from which participants have to choose and the nature of the wealth judgment.