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Performance Indicators in Math: Implications for Brief Experimental Analysis of Academic Performance

机译:数学中的绩效指标:对学术绩效进行简短实验分析的含义

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Brief experimental analysis (BEA) can be used to specify intervention characteristics that produce positive learning gains for individual students. A key challenge to the use of BEA for intervention planning is the identification of performance indicators (including topography of the skill, measurement characteristics, and decision criteria) that meaningfully relate to longer term success in the learning environment. This study investigates the utility of various curriculum-based assessment and measurement estimates of mathematics performance for predicting functional outcomes (i.e., retention of learned skills over time and faster learning of related content in the future). All children in grades 2–5 at the participating school participated in protocol-based computational fluency-building intervention 4 days per week for an entire school year. Specific criteria were applied each week to systematically increase intervention difficulty classwide according to a pre-established sequence of computational skill objectives. Three measurements were routinely obtained. Each week children completed a timed probe of the skill for which intervention was currently occurring and a timed probe of previously mastered skills from the sequence of computational skill objectives. Each month, all children completed a timed probe of mathematics skills representing computational skills that students were expected to master by year’s end at each grade level. At all grade levels, learning a skill that appeared early in the hierarchy or sequence of skills related positively to learning of future related and more complex computational skills. Fluency criteria were specified that predicted retention of the skill over several months.
机译:简短的实验分析(BEA)可用于指定干预特征,从而为单个学生带来积极的学习收益。使用BEA进行干预计划的一个主要挑战是确定绩效指标(包括技能的地形,测量特征和决策标准),这些指标与学习环境中的长期成功有意义地相关。这项研究调查了各种基于课程的数学表现评估和测量估计在预测功能结果时的效用(即随着时间的推移保留所学技能并在将来更快地学习相关内容)。参与学校的所有2至5年级的孩子在整个学年中每周参加4天基于协议的计算流畅性干预。根据预先确定的计算技能目标序列,每周应用特定的标准来系统地增加全班干预的难度。常规获得三个测量值。每周,孩子们都会对当前正在进行干预的技能进行定时探查,并从计算技能目标的序列中对先前掌握的技能进行定时探查。每个月,所有孩子都要完成对数学技能的定时探究,这些探究代表了学生预期在每个年级之前掌握的计算技能。在所有年级,学习在技能的等级或序列中较早出现的一项技能与学习未来相关的和更复杂的计算技能有正相关。指定了流利度标准,可以预测技能在几个月内的保留。

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