Fostering Scientific Modelling in Chemistry Degree Courses

本研究旨在通过两项干预研究，调查化学专业学生的视觉模型理解与他们在大学一年级末的学习成绩（特定领域知识，考试成绩）之间的因果关系。要做到这一点，本项目区分一个图标和符号数学模型的理解。标志性模型具有结构性的描绘特征，其指的是参考对象（例如，原子轨道的视觉显示），而符号数学模型不显示这种相似性（例如，化学计量或物理化学方程式）。干预措施的目标是支持图标以及符号数学模型的理解，这两者都是化学特定的研究要求根据ALSTER框架模型。我们认为，培养图标模型理解将导致更深入的理解物质的结构，而在同一时间，培养符号数学模型理解将增加从不同方面定量感知化学方程式的能力。首先，一个基于实验室的实验，使用控制设计与两个干预组将调查促进图标和符号数学模型理解的有效性。除了模型的理解，学习成绩和结果，从标准化的特定领域的知识测试在有机和物理化学将被用作因变量。第二，训练将在一学期内的一门课程中，在生态有效的环境中进行实地实验。两个训练组也将作为对方的等待控制组。关于方法，两次培训都将基于工作示例方法。为了做到这一点，在培训过程中，工作示例的步骤将逐渐消失，以便学生在相关的特定领域背景下开发自己的解释。关于研究性能和基于有机和物理化学的基本概念和第一个资助阶段的关系分析，我们预计，培训图标和符号数学模型的理解将有利于两个化学子学科。我们以应用为导向的目标是开发和评估支持图标和符号数学模型理解的方法，这些方法可以立即整合到大学教学中，从而保证学习成功的可持续和持久增长。

This project aims at investigating causal relationships between the visual model comprehension of chemistry students and their study performance (domain-specific knowledge, exam scores) at the end of the first university year by means of two intervention studies. To do so, the present project distinguishes between an iconic and a symbolic-mathematical model comprehension. Iconic models have a structural depicting character that refers to a reference object (e.g., the visual display of an atomic orbital), while symbolic-mathematical models do not show this similarity (e.g., a stoichiometric or physical-chemical equation). The goal of the interventions is to support iconic as well as symbolic-mathematical model comprehension, both of which are chemistry-specific study requirements according to the ALSTER framework model. We suppose that fostering iconic model comprehension will lead to a deeper comprehension of the structure of matter, while at the same time, fostering symbolic-mathematical model comprehension will increase the ability to perceive chemical equations quantitatively considering different aspects. First, a laboratory-based experiment using a control design with two intervention groups will investigate the effectiveness of fostering iconic and symbolic-mathematical model comprehension. Besides model comprehension, study performance and results from standardized domain-specific knowledge tests in organic and physical chemistry will be used as dependent variables. Second, the trainings will be conducted under ecologically valid circumstances in a field experiment during a course within a semester. Both trainings groups will also serve as waiting control groups for each other. Regarding the method, both trainings will be based on a worked-examples approach. To do so, the steps of the worked examples will be gradually faded over the course of the training, so that students are triggered to develop their own explanations, also in related domain-specific contexts. Regarding study performance and based on the basic concepts of organic and physical chemistry and on the relational analyses of the first funding phase, we expect that training iconic and symbolic-mathematical model comprehension will be beneficial for both chemical sub disciplines. Our application-oriented goal is the development and evaluation of methods to support iconic and symbolic-mathematical model comprehension, which can be integrated into university-based teaching right away and thus bear the promise of a sustainable and long-lasting increase of study success.