Student knowledge integration in learning mechanical wave propagation

• Main Authors: Li Xie, Qiaoyi Liu, Hui Lu, Qingyong Wang, Jing Han, XiuMei Feng, Lei Bao
• Format: Article
• Language: English
• Published: American Physical Society 2021-09-01
• Series: Physical Review Physics Education Research
• Online Access: http://doi.org/10.1103/PhysRevPhysEducRes.17.020122

A deep understanding of mechanical waves is crucial for students to succeed in studying many advanced physics topics. Studies in existing literature have revealed that students often have widespread difficulties and misconceptions on wave propagation. This research develops and applies a conceptual framework model to examine students’ understanding of mechanical wave propagation from the knowledge integration perspective. Based on the existing literature and interview results, the conceptual framework model of wave propagation was developed and used to guide the development of a multiple-choice test that targets the assessment of knowledge integration in students’ understanding of wave propagation. The assessment was given to first-year college students enrolled in a calculus-based introductory physics course at a medium-ranking Chinese university. The results suggested that after traditional instruction the majority of the students only achieved intermediate level knowledge integration with fragmented knowledge structures and lacked a deep conceptual understanding of wave propagation. The conceptual framework and assessment outcomes were then used to inform the development of new instruction, which made explicit emphasis on teaching the central idea of the conceptual framework and making connections to the central idea within students’ knowledge structures. The effectiveness of the instruction was evaluated with the same pool of college students separated into an experimental group and a control group. Pre-post testing results suggested that the new instruction significantly improved students’ performance on questions that require an integrated knowledge structure, indicating advancement in knowledge integration and deep understanding.