作者：马晶晶,刘清堂*,余舒凡,刘金典,李小娟,王春华

出版刊物：British Journal of Educational Technology

出版时间：2025年

内容摘要：

This research employs the fuzzy- set qualitative comparative analysis (fsQCA) method to investigate the configurations of multiple factors influencing scientific concept learning, including augmented reality (AR) technology, the concept map (CM) strategy and individual differences (eg, prior knowledge, experience and attitudes). A quasi- experiment was conducted with 194 seventh- grade students divided into four groups: AR and CM (N = 52), AR and non- CM (N = 51), non- AR and CM (N = 40), non- AR and non- CM (N = 51). These students participated in a science lesson on ‘The structure of peach blossom’. This study represents students' science learning outcomes by measuring their academic performance and cognitive load. The fsQCA results reveal that: (1) factors influencing students' academic performance and cognitive load are interdependent, and a single factor cannot constitute a necessary condition for learning outcomes; (2) multiple pathways can lead to the same learning outcome, challenging the notion of a singular best path derived from traditional analysis methods; (3) the configurations of good and poor learning outcomes exhibit asymmetry. For example, high prior knowledge exists in both configurations leading to good and poor learning outcomes, depending on how other conditions are combined.

本研究采用模糊集定性比较分析方法，探究增强现实技术、概念图策略及个体差异（如先备知识、经验与态度）对科学概念学习的影响机制。通过对194名七年级学生开展的准实验研究，将被试分为四组：AR结合概念图组、AR无概念图组、非AR概念图组及非AR无概念图组，所有学生均参与以“桃花结构”为主题的科学课程学习。研究通过学业表现与认知负荷两项指标衡量学生的学习成效，fsQCA分析结果显示：（1）影响学业表现与认知负荷的因素具有相互依赖性，单一因素无法构成学习成效的必要条件；（2）存在多条等效路径能够达成相同学习结果，对传统分析方法所认定的“最优单一路径”形成挑战；（3）优良与不良学习结果的影响组态呈现非对称特征。例如，高先备知识既可能出现在促进优良学习成效的组态中，也可能存在于导致不良结果的组态中，其具体作用取决于与其他条件的组合方式。