大学学生的计算思维:流体智能和视觉空间能力的作用
Gabor Aranyi1,2, Kristof Kovacs3, Ferenc Kemény1,4
1Faculty of Education and Psychology, ELTE Eötvös Loránd University, Budapest, Hungary.
PloS one
|August 30, 2024
概括
计算思维 (CT) 依赖于流体智能,而不是先前知识,用于非程序员的解决问题. 视觉空间能力和CT错误地联系在一起,男性显示出轻微的CT优势.
科学领域:
- 认知心理学 认知心理学
- 教育技术的教育技术
背景情况:
- 计算思维 (CT) 对于学术和职业成功至关重要.
- 在非编程学生中了解CT的认知基础对于有效的教学至关重要.
研究的目的:
- 调查流体智能,结晶智能和视觉空间能力在CT表现中的作用在没有编程经验的大学生中.
- 通过流体智能检查性别和视觉空间能力在CT上的调解效应.
主要方法:
- 从97名非编程大学学生在监督环境中收集的数据.
- 认知能力 (流体智能,结晶智能,视觉空间能力) 通过计算机自适应测试进行评估.
- 使用标准化计算思维测试测量CT性能;用于分析的序列多个介质模型.
主要成果:
- 流体智能显著预测CT性能,即使在控制性别,年龄和视觉空间能力之后.
- 结晶智能与CT没有显著的预测关系.
- 当认知能力保持不变时,男性在CT性能上表现出了小的优势;视觉空间能力没有直接预测CT.
结论:
- 编程天真的人利用流动推理,独立于所获得的知识,来解决CT问题.
- 视觉空间能力和CT之间的关联是间接的,可能是虚假的,这表明共享的底层过程与流体智能.
- 对CT的教育策略应该强调一般推理技能的发展,而不是仅仅依赖于先前的知识或视觉空间培训.
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