ABSTRACT

Stability is an important underlying assumption in any form of assessment-supported decision-making. Since early years development is frequently described as unstable, the concept plays a central role in the discussion surrounding early years assessment. This paper describes stability as a set of assumptions about the way individual scores change over time. Here, an analytical framework developed by Tisak and Meredith, which can be used to evaluate these assumptions, is extended and applied to evaluate the stability of mathematics scores of 1402 children between kindergarten and third grade. Multilevel models are used to evaluate the assumption that each child has a unique individual growth rate, as well as the assumption that the ranking of children’s test scores is consistent over time. The results show that for a large proportion of the children, assuming unique individual growth rates leads to similar predictions as assuming that children develop at an equal pace. While individual differences in growth rate may provide relevant information, these differences only become apparent after several test administrations. As such, decisions should not be based on perceived stagnated or accelerated growth over a short period.

摘要

在任何形式的评估支持的决策中，稳定性都是重要的基本假设。由于早期发展经常被描述为不稳定的，因此该概念在围绕早期评估的讨论中起着核心作用。本文将稳定性描述为一组关于个人分数随时间变化的假设。在此，扩展了由Tisak和Meredith开发的分析框架，该框架可用于评估这些假设，并被用于评估1402名幼儿园和三年级之间儿童数学分数的稳定性。多级模型用于评估每个孩子都有独特的个人成长率的假设，以及每个孩子的考试成绩排名随时间变化的假设。结果表明，对于很大比例的儿童，假设独特的个体增长率会导致类似的预测，就像假设儿童以相同的速度发展一样。虽然个体增长率的差异可能会提供相关信息，但这些差异仅在几次测试给药后才变得明显。因此，决策不应基于短期内感觉到的停滞或加速增长。