1,872 research outputs found

    When cheating is an honest mistake

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    Dishonesty is an intriguing phenomenon, studied extensively across various disciplines due to its impact on people’s lives as well as society in general. To examine dishonesty in a controlled setting, researchers have developed a number of experimental paradigms. One of the most popular approaches in this regard, is the matrix task, in which participants receive matrices wherein they have to find two numbers that sum to 10 (e.g., 4.81 and 5.19), under time pressure. In a next phase, participants need to report how many matrices they had solved correctly, allowing them the opportunity to cheat by exaggerating their performance in order to get a larger reward. Here, we argue, both on theoretical and empirical grounds, that the matrix task is ill-suited to study dishonest behavior, primarily because it conflates cheating with honest mistakes. We therefore recommend researchers to use different paradigms to examine dishonesty, and treat (previous) findings based on the matrix task with due caution

    Reducing the standard deviation in multiple-assay experiments where the variation matters but the absolute value does not

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    You measure the value of a quantity x for a number of systems (cells, molecules, people, chunks of metal, DNA vectors, etc.). You repeat the whole set of measures in different occasions or assays, which you try to design as equal to one another as possible. Despite the effort, you find that the results are too different from one assay to another. As a consequence, some systems' averages present standard deviations that are too large to render the results statistically significant. In this work, we present a novel correction method of very low mathematical and numerical complexity that can reduce the standard deviation in your results and increase their statistical significance as long as two conditions are met: inter-system variations of x matter to you but its absolute value does not, and the different assays display a similar tendency in the values of x; in other words, the results corresponding to different assays present high linear correlation. We demonstrate the improvement that this method brings about on a real cell biology experiment, but the method can be applied to any problem that conforms to the described structure and requirements, in any quantitative scientific field that has to deal with data subject to uncertainty.Comment: Supplementary material at http://bit.ly/14I718

    Cheating: A Comparison of its Incidence in Self-Scoring and on a Paper and Pencil Test at Fort Hays Kansas State College

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    The perennial problem for students of every generation is the problem of cheating or cribbing on assignments and examinations. Many people consider themselves capable of understanding and partially solving the problem, hence a great flood of literature is continually being written over the years. Much of the literature is repetitious as persons from different localities and different college generations say essentially the same things. However, there has been much said which has been significant. It is of crucial importance that continuing research in this area be done with as many new techniques as can be devised. Despite the mass of articles on cheating, the majority pertain to the opinions of persons as to the causes and solutions of the problem, there is a shortage of competent research published which either demonstrates that cheating takes place or is able to study its many motivational forces. It is proposed in the present investigation to study the responses of college students when given the opportunity to cheat. One reason for the lack of responsible research is the difficulty in determining when cheating is actually taking place. New and better methods of studying the problem are in need of discovery. It is proposed in this experiment to utilize one method of studying the incidence of classroom cheating which has by now become almost standard among researchers. This method will be compared with a new test which has not, to this writer\u27s knowledge, been formally published in the literature. However, the fundamental idea of this new method has been utilized in a previous study. This will be a new innovation
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