One of the critical goals of teaching chemistry is to enable learners to gain conceptual understanding. Traditional instruction has often been associated with rote memorisation, resulting in learners failing to explain observed chemical phenomena, make predictions based on acquired concepts, advance convincing arguments, and engage in meaningful problem-solving and critical thinking. Therefore, the study aimed to describe the conceptual understanding of the learners taught Reaction Kinetics using computer simulations supported by the Predict-Observe-Explain strategy. The study was guided by Holme, Luxford, and Brandriet’s five categories of conceptual understanding—transfer, translation, problem-solving, prediction, and depth as the conceptual framework. This was a descriptive study in which a case study research approach was used. Five purposively sampled grade 12 learners participated in the study, representing the range of cognitive abilities from a secondary school class of 53 learners. Semi-structured interviews were used to collect data. The responses of the five participants were analysed using the qualitative content analysis. The findings were that most of the learners’ responses were in the sound understanding sub-category, some were in the partial understanding sub-category, and a few were in the no understanding sub-category, which made us conclude that computer simulations supported by the Predict-Observe-Explain strategy assisted the learners in conceptual understanding. The learners gained an understanding of most concepts, although their responses in the partial understanding sub-category showed difficulties related to depth, transfer, and translation. These findings are expected to assist chemistry teachers, teacher educators, and curriculum planners in improving learners’ conceptual understanding of chemistry.

化学教学的关键目标之一是使学习者获得概念理解。传统教学常常与死记硬背联系在一起，导致学习者无法解释观察到的化学现象，无法根据获得的概念做出预测，无法提出令人信服的论点，也无法进行有意义的问题解决和批判性思维。因此，该研究旨在使用预测-观察-解释策略支持的计算机模拟来描述学习者对反应动力学的概念理解。该研究以 Holme、Luxford 和 Brandriet 的概念理解五类——迁移、翻译、问题解决、预测和深度为概念框架。这是一项使用案例研究方法的描述性研究。特意抽取的 5 名 12 年级学生参与了这项研究，代表了中学班级 53 名学生的认知能力范围。使用半结构化访谈来收集数据。使用定性内容分析对五名参与者的回答进行了分析。结果发现，大多数学习者的回答属于正确理解子类别，一些属于部分理解子类别，少数属于不理解子类别，这使我们得出结论，计算机模拟支持预测-观察-解释策略帮助学习者进行概念理解。学习者获得了对大多数概念的理解，尽管他们在部分理解子类别中的反应表现出与深度、迁移和翻译相关的困难。 这些发现有望帮助化学教师、教师教育工作者和课程规划者提高学习者对化学的概念理解。