Build, Understand, & Tune Interventions that Cumulate to Real Impact

匹兹堡大学获得了NSF改善本科生STEM教育：教育和人力资源设计与开发级别奖，以聚集一个高度跨学科的团队，研究一套教学、认知技能和社交/动机干预措施，这些干预措施已被证明在STEM入门课程的背景下大大改善了学习。这项研究具有重要意义，因为它将使我们了解哪些干预措施能够产生长期的积极结果，这些干预措施在课程内部和课程之间是负面的还是协同的，以及它们对哪些类型的学生或学生群体最有效。该项目团队包括四名以学科为基础的教育研究科学家(生物、化学、物理和心理学)，三名具有社会/动机、认知技能或主动STEM学习技术专长的学习科学家，以及一名擅长使用尖端统计技术进行大规模纵向数据分析的学习科学家。该项目代表了一种名为“干预科学”的新型研究的初始阶段。虽然干预措施在教育环境中相对常见，但很少有研究试图在一个单一的、跨学科的方法框架中全面评估不同的干预措施。该研究计划试图了解不同课堂“干预”(例如，“翻转”课堂、主动学习、同伴评估等)的相对影响。关于学生成功的指标(例如，下游课程的课程表现、参与本科生研究、概念性学习收益等)。控制组和试验组的构建将使用统计技术，将学生按概率分配到这些类别中。混淆的情况(例如，参加不同课程的学生经历不同的干预，或学生与其他课程的同龄人互动)将使用分层线性建模等技术进行处理。对教学、认知技能和社会/动机干预最有效的条件以及对谁的干预的知识，将为教师在课堂上实施有效干预的方式提供信息，并以这种方式对全国大量STEM学生的教育体验产生重大影响。

The University of Pittsburgh has received an NSF Improving Undergraduate STEM Education: Education and Human Resources Design and Development tier award to bring together a highly interdisciplinary team to study a suite of instructional, cognitive-skill, and social/motivational interventions that have been demonstrated to produce large improvements in learning in the context of introductory STEM courses. This research is significant because it will allow us to understand which interventions produce long-term positive outcomes, whether these interventions combine negatively or synergistically within and across courses, and the types of situations or groups of students for which they are most effective. The project team consists of four Discipline-Based Education Research scientists (biology, chemistry, physics, and psychology), three learning scientists with expertise in social/motivational, cognitive skills or active STEM learning techniques, and a learning scientist with expertise in large-scale longitudinal data analysis with cutting edge statistical techniques. This project represents the initial phase of a new type of study termed "Intervention Science." Although interventions are relatively commonplace in educational settings, very little research has sought to comprehensively evaluate different interventions in a single, interdisciplinary methodological framework. The research plan seeks to understand the relative influence of different classroom "interventions" (e.g. "flipped" classes, active learning, peer assessment, etc.) on indicators of student success (e.g. course performance in downstream courses, participation in undergraduate research, conceptual learning gains, etc.). Construction of control and experimental groups will be accomplished using statistical techniques that assign students probabilistically to such categories. Confounding circumstances (e.g. students enrolled in different courses experiencing different interventions, or students interacting with peers in other courses) will be handled using techniques such as hierarchical linear modeling. Knowledge of the conditions in which instructional, cognitive-skill, and social/motivational interventions are most effective, and on whom, will inform the way in which faculty members implement effective interventions in the classroom and, in that way, have a significant impact on the educational experience of large numbers of STEM students nationwide.