How Do Students Talk About Intelligence?: An Investigation of Motivation, Self-Efficacy, and Mindsets in Computer Science
How Do Students Talk About Intelligence?: An Investigation of Motivation, Self-Efficacy, and Mindsets in Computer Science
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学生如何谈论智力？：计算机科学中的动机、自我效能和心态的调查
DOI：
10.1145/3291279.3339413
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
O'Rourke, Eleanor
中科院分区：
文献类型：
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作者：
Gorson, Jamie;O'Rourke, Eleanor
计算机科学（CS）的本科课程面临着高辍学率，许多学生在学习编程时都很挣扎。研究表明，感知编程能力是学生决定主修计算机科学的一个重要因素。幸运的是，心理学研究表明，培养成长型思维模式，或者相信智力随着努力而增长，可以提高学生的毅力和表现。然而，与其他领域相比，思维干预在计算机科学领域并不那么成功。我们进行了一项小规模的访谈研究，以探索计算机科学学生如何谈论他们的智力、心态和编程行为。我们发现学生的心态很少与文献中的定义一致；有些人现在的心态结合了固定和成长属性，而另一些人的行为方式与他们的心态不一致。我们还发现，学生们经常通过评估自己的编程智力来评估自我效能感，用打字速度和调试难易等令人惊讶的标准来衡量能力。我们对103名学生进行了一项调查研究，进一步探讨了这些自我评估标准，发现学生使用不同的和相互冲突的标准来评估计算机科学中的智力。我们认为，学生选择的标准可能与思维方式相互作用，影响他们的动机和编程方法，这可以帮助解释思维方式干预在计算机科学中的有限成功。
Undergraduate programs in computer science (CS) face high dropout rates, and many students struggle while learning to program. Studies show that perceived programming ability is a significant factor in students' decision to major in CS. Fortunately, psychology research shows that promoting the growth mindset, or the belief that intelligence grows with effort, can improve student persistence and performance. However, mindset interventions have been less successful in CS than in other domains. We conducted a small-scale interview study to explore how CS students talk about their intelligence, mindsets, and programming behaviors. We found that students' mindsets rarely aligned with definitions in the literature; some present mindsets that combine fixed and growth attributes, while others behave in ways that do not align with their mindsets. We also found that students frequently evaluate their self-efficacy by appraising their programming intelligence, using surprising criteria like typing speed and ease of debugging to measure ability. We conducted a survey study with 103 students to explore these self-assessment criteria further, and found that students use varying and conflicting criteria to evaluate intelligence in CS. We believe the criteria that students choose may interact with mindsets and impact their motivation and approach to programming, which could help explain the limited success of mindset interventions in CS.