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arXiv 1608.05006physics.ed-ph
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计算自动化与学生在物理科学导论课程中的成功

Automaticity in Computation and Student Success in Introductory Physical Science Courses

JudithAnn R. Hartman, Eric A. Nelson

摘要:

从1984年到2011年,美国授予物理学学士学位的比例下降了25%,化学下降了33%,物理科学和工程总体下降了40%。数据表明,这些下降与大多数国家在数学中练习计算技能的不重视有关。对1990年至2010年实施的州标准的分析发现,大多数州都指示教师在计算问题解决中不强调记忆和学生实践。现有的州考试成绩数据显示,学生的计算能力显着下降。在最近的国际测试中,美国16至24岁的数学成绩在经合组织的22个测试国家中排名最后。最近的认知科学研究发现,要解决科学中结构良好的问题,学生必须首先记住数学和科学中的基本事实和程序,直到它们可以自动回忆起来,然后在各种不同的背景下练习应用这些技能。建议采取行动,通过调整美国数学和科学课程与认知科学的建议,以提高美国STEM毕业率。

英文摘要:

Between 1984 and 2011, the percentage of US bachelor degrees awarded in physics declined by 25%, in chemistry declined by 33%, and overall in physical sciences and engineering fell 40%. Data suggest that these declines are correlated to a deemphasis in most states of practicing computation skills in mathematics. Analysis of state standards put into place between 1990 and 2010 find that most states directed teachers to deemphasize both memorization and student practice in computational problem solving. Available state test score data show a significant decline in student computation skills. In recent international testing, scores for US 16 to 24 year olds in numeracy finished last among 22 tested nations in the OECD. Recent studies in cognitive science have found that to solve well-structured problems in the sciences, students must first memorize fundamental facts and procedures in mathematics and science until they can be recalled with automaticity, then practice applying those skills in a variety of distinctive contexts. Actions are suggested to improve US STEM graduation rates by aligning US math and science curricula with the recommendations of cognitive science.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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