Abstract

School science is often very different from “real world” science. One important difference, and possibly the main one, is that in school science the relationships between variables have often been sanitized – essentially “cleaned up” – so that there is very little (and often no) variation in the data from the relationship students are being taught about. This happens because school science often (a) deals with “settled” or “consensus” science where scientists have essentially agreed on what the relationships between the variables are; (b) involves bivariate (i.e., two-variable) relationships where all other variables that might be in a “real world” relationship have been identified and are removed from the example dataset/activity (e.g., minimizing friction so it becomes negligible to understand movement); and, (c) involve known “controlled variables” that can be easily controlled to reduce their influence on the outcomes. This type of removal of variation is problematic as it can make it more difficult for students to learn about, understand, and make sense of "real world" data relationships outside of school settings. It is therefore important for them to engage in school investigations that help them learn to make sense of data with considerable variation in the measured variables. This paper describes and discusses such an activity.

摘要

学校科学通常与“现实世界”科学截然不同。一个重要的差异，也可能是主要的差异是，在学校科学中，变量之间的关系经常被清理掉-本质上是“清理过”的，因此，来自学生的关系数据几乎没有（通常没有）变化。被教导。之所以发生这种情况，是因为学校科学经常（a）处理“已解决”或“共识”的科学，其中科学家基本上就变量之间的关系达成了一致；（b）涉及双变量（即二变量）关系，其中所有其他可能处于“现实世界”关系中的变量均已被识别，并已从示例数据集/活动中删除（例如，使摩擦最小化，因此可以忽略）移动）; 和，（c）涉及已知的“控制变量”，可以轻松控制这些变量以减少其对结果的影响。这种消除差异的方法是有问题的，因为它会使学生更加难以了解，理解和理解学校环境之外的“现实世界”数据关系。因此，对他们而言，进行学校调查很重要，这有助于他们学习如何在测量变量有很大差异的情况下理解数据。本文描述并讨论了这种活动。因此，对他们来说，进行学校调查很重要，这有助于他们学习理解数据，并且测量变量的变化很大。本文描述并讨论了这种活动。因此，对他们而言，进行学校调查很重要，这有助于他们学习如何在测量变量有很大差异的情况下理解数据。本文描述并讨论了这种活动。