Improving Online Learning with Interpolated Retrieval

通过插值检索改进在线学习

• 批准号: 2017333
• 负责人: Chun-Kit Chan
• 金额: $ 64.2万
• 依托单位: Iowa State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-09-01 至 2025-08-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2017333&HistoricalAwards=false
• 关键词: Improving; Online; Learning; Interpolated; Retrieval

Online learning represents a rapidly growing feature of post-secondary education. According to a recent report from the National Center for Education Statistics, it is estimated that 1 in 7 students enroll exclusively online, and that 1 in 3 students have taken at least one online course, notwithstanding the fact that COVID-19 has forced most education online, at least temporarily. Within the context of online learning, video-recorded lectures represent the primary mode of information delivery, but learning from online lectures is often plagued by bouts of inattention that impede effective learning. This award will allow the researchers to build on their preliminary work demonstrating that breaking long lecture videos into shorter, more manageable segments, and asking students to express what they have learned during these breaks can reliably improve attention and learning. More specifically, the researchers will aim to (1) develop and evaluate a theoretical framework to better understand why it is effective to intersperse video-recorded lectures with brief quizzes, (2) test the generalizability of this behavioral intervention across multiple STEM areas and student populations, including both students who enroll in public universities and in community colleges, and (3) construct evidence-based guidelines around optimal parameters for interspersing video-recorded lectures with brief quizzesHigher education is increasingly being delivered online, where students are prone to inattention and poor learning outcomes relative to in-person instruction. One technique that supports attention and learning is interpolated retrieval—the act of inserting brief test questions into prolonged sequences of learning. Although substantial empirical data have provided support for its effectiveness, existing research has progressed in the absence of a guiding theoretical framework, without which future research would likely remain limited in scope. In this proposal, the investigators introduce and evaluate an Attention-Integration theoretical framework of interpolated retrieval practice. According to this framework, interpolated retrieval enhances learning via two routes. First, interpolated retrieval increases learners’ engagement with and test expectancy for the material, which improves processes associated with attention. Second, interpolated retrieval induces changes in learners’ strategy and increases the accessibility of the tested information, which allows learners to meaningfully integrate the contents of study into a coherent mental representation. Four studies will test the critical assumptions of this framework. Studies 1 and 2 are designed to test the attention component of the framework; Studies 3 and 4 are designed to test the integration component of the framework. All four studies will use the same set of materials and similar participant samples, which allows the investigators to conduct a large-scale mediation-moderation analysis at the conclusion of data collection for all studies. This analysis will be instrumental to the refinement and clarification of the interrelations among the various components of the Attention-Integration framework.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

在线学习代表了大专教育的快速增长。根据国家教育统计中心的最新报告，据估计，只有七分之一的学生仅在线注册，而三分之一的学生至少参加了一门在线课程，尽管Covid-19至少在网上迫使大多数教育在线，至少是暂时的。在在线学习的背景下，视频录制的讲座代表了信息传递的主要方式，但是从在线讲座中学习通常会受到阻碍有效学习的陷入困境的困扰。该奖项将使研究人员能够以他们的初步工作为基础，表明将长期的演讲视频分为较短，更易于管理的细分市场，并要求学生表达他们在这些休息期间所学到的知识可以可靠地改善关注和学习。更具体地说，研究人员将旨在（1）开发和评估一个理论框架，以更好地理解为什么用简短的测验中的视频录制的视频录制的讲座有效，（2）测试这种行为干预跨多个STEM领域和学生群体的行为干预的普遍性，包括在社区大学和（3）中构建循证参数的学生，以及（3），以及（3），以及（3），在社区大学和（3）构建了（3）跨越的循证范围。简短的Quizzeshigher教育越来越多地在线交付，在该教育中，学生容易受到注意，而相对于面对面的指导，学习成果不佳。一种支持关注和学习的技术是插值检索 - 将简短的测试问题插入长期学习序列的行为。尽管实质性的经验数据为其有效性提供了支持，但在没有指导理论框架的情况下，现有的研究仍在进行，没有这些框架的情况下，未来的研究可能会在范围内仍然有限。该提案，调查人员介绍并评估了插值检索实践的关注融合理论框架。根据此框架，插值检索通过两条路线增强了学习。首先，插值的检索增加了学习者对材料的参与和测试期望，这改善了与注意力相关的过程。其次，插值检索会导致学习者策略的变化，并增加了测试信息的可访问性，这使学习者可以将研究内容集成到连贯的心理表示中。四项研究将测试该框架的关键假设。研究1和2旨在测试框架的注意力成分。研究3和4旨在测试框架的集成部分。所有四项研究都将使用相同的材​​料和相似参与者样本，这使研究人员可以在所有研究的数据收集结束时进行大规模的调解分析。该分析将有助于对关注整合框架的各个组成部分之间的相互关系的完善和澄清。本奖反映了NSF的法定任务，并通过评估基金会的知识分子和更广泛的影响来审查标准。