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The effect of positive and negative messages on problem solving in computer programming tasks.

机译:正面和负面消息对解决计算机编程任务中的问题的影响。

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摘要

Many supervisory control systems require the operator to solve any problems that the system's automation cannot accommodate. Consequently, this class of systems would benefit from designs and methods which improve operator problem solving performance. Currently, human factors researchers develop designs and methods emphasizing the cognitive capacities and abilities of operators. For the most part, these approaches neglect the emotional state of the operator, although emotion has been shown to have an important impact on performance in many other domains.;This dissertation introduces the modified Multidimensional Problem Solving (m-MPS) Model, a theoretical model predicting how affect, one aspect of emotion, will influence problem solving performance. The model was tested in an experiment in which 32 participants attempted to correct a series of 5 bugs in a computer program. During their task, they received compiler messages with keywords specifically chosen to create a positive or negative affective state. The model predicted that the participants with messages designed to increase positive affect would seek solutions with a more divergent thought process, and this would be indicated with a more diverse set of problem-solving approaches, along with higher scores on a divergent thought measuring test administered throughout the experiment. Those with less positive affect would seek solutions in a smaller, less creative space and demonstrate less divergent thought. Unfortunately, the feedback messages did not appear to evoke an emotional response powerful enough to create a measurable change in emotional state. However, the messages did affect various aspects of the participants' performance in ways consistent with the model, including fewer repeated solutions with increasing divergent thought scores (F(1,423) = 12.39, p 0.01) and the probability of continuing the problem solving process declines with each unsuccessful attempt (Z = -2.98, p = 0.003). The most compelling result was that participants receiving the negative messages were significantly less likely to successfully complete the problem-solving task (Wald X2 = 4.06, p = 0.044). These results suggest that in human-computer interactions, messages are an important factor in creative problem solving performance. Further research is necessary to determine the source of these effects in supervisory control interfaces.
机译:许多监督控制系统要求操作员解决系统自动化无法解决的任何问题。因此,此类系统将从改进操作员解决问题性能的设计和方法中受益。当前,人为因素研究人员开发了强调操作员认知能力的设计和方法。尽管已经证明情绪对许多其他领域的绩效具有重要影响,但是这些方法在很大程度上忽略了操作员的情绪状态。本文将介绍一种改进的多维问题解决模型(m-MPS)模型预测情感的一方面的模型将如何影响解决问题的表现。在一个实验中测试了该模型,其中32位参与者试图纠正计算机程序中的5个错误。在执行任务期间,他们收到带有专门选择的关键字的编译器消息,以创建正面或负面的情感状态。该模型预测,具有旨在增加积极影响力的信息的参与者将寻求具有更多样化思维过程的解决方案,并且这将通过更多样化的问题解决方法集以及在所进行的不同思维测量测试中获得的更高分数来表明在整个实验中那些正面影响较小的人会在较小的,较少创造的空间中寻求解决方案,并表现出较少分歧的思想。不幸的是,反馈消息似乎并未唤起足够强大的情绪反应,从而无法引起可测量的情绪状态变化。但是,这些消息确实以与模型一致的方式影响了参与者的表现的各个方面,包括更少的重复解决方案以及不同的思维得分(F(1,423)= 12.39,p <0.01)以及继续解决问题的可能性每次失败尝试都会下降(Z = -2.98,p = 0.003)。最令人信服的结果是,收到负面消息的参与者成功完成问题解决任务的可能性大大降低(Wald X2 = 4.06,p = 0.044)。这些结果表明,在人机交互中,消息是创造性地解决问题的性能的重要因素。为了确定这些影响在监控界面中的来源,有必要做进一步的研究。

著录项

  • 作者

    Thornburg, Kristopher M.;

  • 作者单位

    The University of Iowa.;

  • 授予单位 The University of Iowa.;
  • 学科 Engineering Industrial.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 136 p.
  • 总页数 136
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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