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Mechanistic models play a crucial role in algorithms for numerical problem-solving, particularly in nonlinear mixed effects modeling (NMEM). These models aim to minimize specific objective functions by evaluating various parameter estimates, leading to the development of systematic algorithms. In some cases, linearization techniques approximate the model using linear equations.
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Language serves as a bridge between ideas and communication, influencing how individuals perceive and interact with the world. Psychologists have long debated whether language shapes thought or vice versa. This discussion gained grip with Edward Sapir and Benjamin Lee Whorf in the 1940s, who proposed that language determines thought, a concept known as linguistic determinism. They suggested that the vocabulary and structure of a language influence how its speakers think and perceive reality.
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STEM考试成绩:在大型语言模型时代,开放式与封闭式的方法.

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  • 1GKT School of Medicine, Faculty of Life Sciences & Medicine, King's College London, London, UK.

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在STEM教育中,开放式考试 (OBEs) 通常优于封闭式考试 (CBEs),但像LLM这样的复杂AI工具挑战了它们的学术完整性. 需要进一步的研究,以确保在不断变化的技术环境中进行公平的评估.

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科学领域:

  • 在STEM教育方面.
  • 教育技术的教育技术
  • 学术诚信 学术诚信

背景情况:

  • 由于COVID-19大流行加速了远程学习,在STEM中增加了对开放式考试 (OBEs) 和封闭式考试 (CBEs) 的审查.
  • 复杂的大型语言模型 (LLM) 正在成为教育评估的重要因素.

研究的目的:

  • 与CBEs相比,评估OBEs在STEM科目中的学生表现和感知方面的有效性.
  • 考虑LLM对OBE有效性的影响.

主要方法:

  • 从2013年开始发表的同行评审文章的系统审查,遵守PRISMA指南.
  • 用随机效应模型评估标准化平均差异的八项研究的元分析.
  • 使用I平方统计,科克兰的Q测试和Tau统计评估异质性.

主要成果:

  • 一般来说,OBE比CBE更好的学生成绩,尽管观察到显著的异质性 (I2 = 97%).
  • 观察性研究表明,OBE的效果更为明显,同时还存在对技术困难和作弊的担忧.

结论:

  • 与CBEs相比,OBE评估能力与当前的教育范式更好地协调一致.
  • 法律学士学位的出现对OBE的有效性和学术完整性提出了挑战,需要进一步调查.
  • 机构必须谨慎考虑OBE能力,考虑到不断发展的技术,并确保公平的学生评估.