学生学习计算机程序设计的进展:来自关联分析的见解

Candido Cabo
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引用次数: 8

摘要

在这项实践全文的研究中,我们量化了一年级学生(n=54)使用不同复杂程度的计算机编程控制结构(如排序、选择(if/else)和重复(for/while))解决问题的能力进展。学生们使用流程图解释器和Python编写程序。我们发现70%的学生可以使用流程图解释器或Python解决涉及一系列语句的问题(即不使用选择或重复)。大多数不能解决排序问题的学生不能成功地解决涉及选择和重复的问题(69%使用流程图,94%使用Python)。另一方面,能够解决排序问题的学生中,45%(流程图)和71% (Python)能够解决涉及选择和重复的问题。因此,解决包含一系列语句的问题的能力是解决具有更复杂控制结构(如选择和重复)的问题的成功/失败的良好早期预测指标。成功地解决计算机编程问题取决于学生所使用的工具。因此,学生在不同工具(从流程图到Python)之间转移问题解决能力的能力不是自动的。
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Student Progress in Learning Computer Programming: Insights from Association Analysis
In this research to practice full paper we quantified progress in the ability of first-year students (n=54) to solve problems using computer programming control structures with different levels of complexity like sequencing, selection (if/else) and repetition (for/while). Students used both a flowchart interpreter and Python to write programs. We found that 70% of students could solve problems involving a sequence of statements (i.e. without the use of selection or repetition) using a flowchart interpreter or Python. The majority of the students who could not solve sequencing problems were not successful at solving problems involving selection and repetition (69% using flowcharts and 94% using Python). On the other hand, of the students who could solve sequencing problems 45% (flowchart) and 71% (Python) were able to solve problems involving selection and repetition. Therefore, the ability to solve problems involving a sequence of statements is a good early predictor of success/failure in solving problems with more complicated control structures like selection and repetition. Success in solving computer programming problems depends on the tool used for $\sim37$% of students. Therefore, the ability of students to transfer problem solving abilities between tools (from flowcharting to Python) is not automatic.
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