The Role of Knowledge Retrieval in Inference-making among Rural, Middle Grade Struggling Readers

项目摘要/摘要 最近的研究表明，在6-12年级，推理能力都有所提高，这是唯一能解释 句子和篇章层面的理解与推理中的个体差异有原则上的联系 不同阅读能力的读者阅读理解的差异(Barth等人，2015年；Barnes等人，2015年)。这些 研究结果表明，理解需要推理，而当读者不这样做时，理解就会失败 拥有相关知识，或者只能缓慢地从文本或语义记忆中提取和整合知识 阅读期间(肯迪欧，2015)。然而，很少有研究研究推理是如何作为一种函数变化的 知识的变化。为了扩展这一有限的研究主体，这项申请需要三年的资金 进行两项实验研究，旨在(A)考察知识检索和 推理(目标1)和(B)确定改善知识检索的干预措施的有效性 推论(目标2)在农村、中等水平的有困难的读者中。这项提议还寻求扩大研究 为布埃纳维斯塔大学本科生提供机会(目标3)。研究设计使用了316个奋斗者 在乡村学校就读的5-8年级的读者。为了测试目标1，知识检索的效果(准确性和 速度)对推论进行建模，而不会对分布进行二分法。线性混合效应模型将是 是否适合确定读者特征(即知识检索、元认知、阅读理解、 单词阅读效率、背景知识、工作记忆和年级)对 跨后测和后续数据收集时间点进行推理。为了测试目标2，我们将首先考虑 作为学生的几种结构模型可能嵌套在教师、学校和导师中。我们将无条件地运行 为研究设计的每个水平估计组内相关性的模型。如果存在显著的类间关联 ，我们将建立多水平模型来评估干预的有效性，同时控制 协变量，如推理相关测量的预试成绩和子属性，如英语 学习者状态。我们的主要分析计划假设了意向治疗模型，在该模型中我们测试了两种药物的疗效 完好无损。我们还将估计效应大小以报告两者之间的差异大小 条件。预期成果包括：(A)确定有效促进知识的方法 农村、中等收入、贫困人口的检索及相关知识的应用 (B)证实了一种干预措施，该干预措施教会农村、苦苦挣扎的中产阶层读者如何激活， 检索相关知识，并将相关知识与文本中的信息交织在一起，准确地形成推理 可在中学课堂上广泛实施的阅读；以及(C)扩大本科生 在Buena Vista大学通过将研究团队中的学生与 成功实施这些随机对照试验的知识和技能。

Project Summary/Abstract Recent research shows that inferencing improves across grades 6-12, uniquely accounts for variance in sentence- and passage-level comprehension, and individual differences in inferencing relate in a principled way to variations in reading comprehension for readers of all abilities (Barth et al., 2015; Barnes et al., 2015). These findings suggest that comprehension requires inferencing and that comprehension fails when readers do not possess relevant knowledge or can only slowly retrieve and integrate knowledge from text or semantic memory during reading (Kendeou, 2015). Yet, very little research has examined how inferencing changes as a function of changes in knowledge. To extend this limited body of research, this application requests three years of funding to conduct two experimental studies designed to (a) examine the relationship between knowledge retrieval and inferencing (Aim 1) and (b) determine the effectiveness of an intervention that improves knowledge retrieval and inferencing (Aim 2) among rural, middle grade struggling readers. This proposal also seeks to expand research opportunities for undergraduates at Buena Vista University (Aim 3). The research design uses 316 struggling readers in grades 5-8 who attend a rural school. To test Aim 1, the effects of knowledge retrieval (accuracy and speed) on inferencing will be modeled without dichotomizing the distribution. Linear mixed effect models will be fit to determine whether reader characteristics (i.e., knowledge retrieval, metacognition, reading comprehension, word reading efficiency, background knowledge, working memory, and grade) make unique contributions to inferencing across the posttest and follow-up data collection time points. To test Aim 2, we will first consider several structural models as students may be nested in teachers, schools, and tutors. We will run unconditional models to estimate the intraclass correlation for each level of the study design. If significant interclass correlations emerge, we will fit multilevel models to evaluate the effectiveness of the intervention while controlling for covariates such as pre-test performance on inference-related measures and child-attributes such as English learner status. Our primary analysis plan assumes an intent-to-treat model in which we test the efficacy of two intact conditions. We will also estimate effect sizes to report the magnitude of difference between the two conditions. Expected outcomes include (a) the identification of a method that effectively facilitates knowledge retrieval and the application of relevant knowledge to form inferences among rural, middle grade, struggling readers; (b) the validation of an intervention that teaches rural, struggling middle grade readers how to activate, retrieve, and interweave relevant knowledge with information in the text and accurately form inferences while reading that can be broadly implemented in middle grade classrooms; and (c) expansion of undergraduate research opportunities at Buena Vista University by integrating students on the research team with the knowledge and skills to successfully implement these randomized controlled trials.