ABSTRACT

Background: A key aspect of STEM learning is the use of visual representations for problem solving. To successfully use visuals, students need to make sense of how they show concepts and to fluently perceive domain-relevan information in them. Adding support for sense making and perceptual fluency to problem-solving activities enhances students’ learning of content knowledge. However, students need different types of representational-competency supports, depending on their prior knowledge. This suggests that adaptively assigning students to sense-makingand perceptual-fluency support might be more effective than assigning all students to the same sequence of these supports.

Method: We tested this hypothesis in an experiment with 44 undergraduate students in a chemistry course. Students were randomly assigned to a ten-week sequence of problem-solving activities that either provided a fixed sequence of sense-making support and perceptual-fluency support or adaptively assigned these supports based on students’ problem-solving interactions.

Findings: Results show that adaptive representational-competency supports reduced students’ confusion and mistakes during problem solving while increasing their learning of content knowledge.

Contribution: Our study is the first to show that adaptive support for representational competencies can significantly enhance learning of content knowledge. Given the pervasiveness of visuals, our results may inform general STEM instruction.

摘要

背景：STEM学习的一个关键方面是使用视觉表示来解决问题。为了成功地使用视觉效果，学生需要弄清楚他们如何展示概念并流利地感知其中的领域相关信息。在解决问题的活动中增加对理解力和感知流利性的支持，可以增强学生对内容知识的学习。但是，根据他们的先验知识，学生需要不同类型的表征能力支持。这表明适应性地给学生分配感官和感知流利性支持可能比将所有学生分配给这些支持的相同顺序更有效。

方法：我们在一个化学课程的44名大学生的实验中检验了该假设。学生被随机分配到为期十周的问题解决活动序列，这些活动要么提供固定顺序的感性支持和感知流利性支持，要么根据学生的问题解决交互作用自适应地分配这些支持。

研究结果：结果表明，自适应表示能力有助于减少学生在解决问题过程中的困惑和错误，同时增加他们对内容知识的学习。

贡献：我们的研究首次表明，对代表性能力的自适应支持可以显着增强内容知识的学习。考虑到视觉效果的普遍性，我们的结果可能会为一般STEM指导提供参考。