Development of a Play-Learning Model in Science Museum

Abstract

In this study, a science museum teaching-learning model was developed with emphasis on play. In order to do this, the models of factor-centered museum education and process-centered museum education were reviewed and characteristics of science museum education were considered. The model developed in this study is called 'Play-Learning Model in Science Museum', and 'play' is defined as activities to achieve the mission in accordance with methods and rules set by individuals or small groups including scaffolding and play is divided into competition, simulation, and chance. 'Play-Learning Model in Science Museum' emphasizes learning using the articles on exhibition, scaffolding and interaction in small groups, and play. The model consists of four steps: 'Preparation', 'Exploring the exhibits', 'Experience', and 'Summary of learning content'. In the 'Preparation' step, the students form related knowledge and are ready to play. The 'Exploring the exhibits' step is the core step of this model, and entails the students solving problems in the mission by interacting with members of the small group. When they cannot find resolution, they get help. In the 'Experience' step, hands-on activities related to the prior step are included. In the 'Summary of learning content' step, the students summarize what they learned while playing. As science museum education is implemented in a variety of forms, continuous research about the science museum learning model and development of various programs are needed.

AI-Integrated Science Teaching Through Facilitating Epistemic Discourse in the Classroom

“…-What would be "good" data collection in terms of science (and in the training of AI agents)? Teachers also can have students experience the "messy" process of data collection and processing by using statistical and analytic tools such as spreadsheets in the classroom (e.g., Hardy et al, 2022;Son & Jeong, 2020). For example, teachers can engage students in at least a single 1-hour lesson in the authentic process of collecting and processing data, which resembles a crucial aspect of the way AI learns from data.…”