Gavarkovs Adam G, Kusurkar Rashmi A, Kulasegaram Kulamakan, Brydges Ryan
Faculty of Medicine, University of British Columbia, City Square East Tower, 555 W 12th Ave, Suite 200, Vancouver, BC, V5Z 3X7, Canada.
Research in Education, Amsterdam UMC Location Vrije Universiteit Amsterdam, De Boelelaan 1118, Amsterdam, The Netherlands.
Adv Health Sci Educ Theory Pract. 2025 Apr;30(2):557-570. doi: 10.1007/s10459-024-10365-9. Epub 2024 Aug 28.
To design effective instruction, educators need to know what design strategies are generally effective and why these strategies work, based on the mechanisms through which they operate. Experimental comparison studies, which compare one instructional design against another, can generate much needed evidence in support of effective design strategies. However, experimental comparison studies are often not equipped to generate evidence regarding the mechanisms through which strategies operate. Therefore, simply conducting experimental comparison studies may not provide educators with all the information they need to design more effective instruction. To generate evidence for the what and the why of design strategies, we advocate for researchers to conduct experimental comparison studies that include mediation or moderation analyses, which can illuminate the mechanisms through which design strategies operate. The purpose of this article is to provide a conceptual overview of mediation and moderation analyses for researchers who conduct experimental comparison studies in instructional design. While these statistical techniques add complexity to study design and analysis, they hold great promise for providing educators with more powerful information upon which to base their instructional design decisions. Using two real-world examples from our own work, we describe the structure of mediation and moderation analyses, emphasizing the need to control for confounding even in the context of experimental studies. We also discuss the importance of using learning theories to help identify mediating or moderating variables to test.
为了设计有效的教学，教育工作者需要了解哪些设计策略通常是有效的，以及基于这些策略的运作机制，它们为何有效。实验比较研究将一种教学设计与另一种进行比较，可以产生支持有效设计策略所需的大量证据。然而，实验比较研究往往无法产生关于策略运作机制的证据。因此，仅仅进行实验比较研究可能无法为教育工作者提供他们设计更有效教学所需的所有信息。为了产生关于设计策略的“是什么”和“为什么”的证据，我们主张研究人员进行包括中介或调节分析的实验比较研究，这可以阐明设计策略的运作机制。本文的目的是为在教学设计中进行实验比较研究的研究人员提供中介和调节分析的概念性概述。虽然这些统计技术增加了研究设计和分析的复杂性，但它们有望为教育工作者提供更有力的信息，以便他们做出教学设计决策。我们使用来自我们自己工作的两个实际例子，描述了中介和调节分析的结构，强调即使在实验研究的背景下也需要控制混杂因素。我们还讨论了使用学习理论来帮助识别要测试的中介或调节变量的重要性。
