Can Students' Spatial Skills Predict Their Programming Abilities?

Can Students' Spatial Skills Predict Their Programming Abilities?
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学生的空间技能可以预测他们的编程能力吗?

DOI:
10.1145/3341525.3387380
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发表时间:
2020
期刊:
ITiCSE 2020
影响因子:
--
通讯作者:
Dorodchi, Mohsen
Dorodchi, Mohsen
中科院分区:
--
文献类型:
--
作者:
Bockmon, Ryan;Cooper, Stephen;Gratch, Jonathan;Zhang, Jian;Dorodchi, Mohsen

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空间能力已被证明对学生在STEM相关领域的成功具有很高的可预测性。研究还表明,学生的空间技能和编程能力之间存在相关性,但学生先前的空间能力如何预测学生在学期末的入门编程能力尚不清楚。在这项研究中,我们使用了多项逻辑回归来创建一个预测模型,以预测学生在学期末的入门编程能力。最高的模型准确性(64.6%)时,占学生的事先编程能力,空间技能,社会经济地位,以及三个因素,学生对计算的态度。研究还发现,当观察每个变量的可预测性时,与所有其他变量相比,学生的先前空间能力具有最高的可预测性(56.6%的准确性)。
Spatial abilities have been shown to have high predictability in students' success in STEM related fields. Studies have also shown that there is a correlation between students' spatial skills and programming abilities, but it is unknown how well students' prior spatial abilities can predict students' introductory programming abilities at the end of the semester. During this study we used a multinomal logistic regression to create a predictive model to predict students' introductory programming abilities at the end of the semester. The highest model accuracy (64.6%) was obtained when accounting for students' prior programming abilities, prior spatial skills, socioeconomic status, and three factors regarding students' attitudes towards computing. It was also found that when looking at the predictability of each individual variable, students' prior spatial ability had the highest predictability (56.6% accuracy) when compared to all other variables.
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发表时间: 2019
期刊: 50th ACM Technical Symposium on Computer Science Education
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