Promote Scientific Knowledge Construction Of Complex Systems With Agent-based Modeling

There are many complex systems in the natural world,such as ecosystem,chemical reaction system,etc.These are composed of several autonomous agents.The complexity lies in that it is difficult to infer the changing pattern in the system level even if we have already understanded the agent's behavior rules.This emergence nature goes against the reductionism that modern science relies on for a long time,and therefore provides a new perspective for understanding the world that are worth introducing into science education.In fact,a lot of content in the middle school science curriculum is related to complex system(CS).However,teachers tend to introduce the macro law of the systems while put little effort into the micro level,leading to structural deficiencies in students' knowledge of complex systems.Agent-based Modeling(ABM)is a computer modeling method of CS.It is used by foreign researchers to cope with the teaching challenge of complex systems.In most cases recently,however,students directly used the ABM models made by teachers,instead of building the models on their own,so ABM was unable to works as a cognitive tool of complex systems.Therefore,the research goal is to design a Learning environment for Learning Complex Systems through Agent-based Modeling(LCSTABM),and use it as an intermediary to study the process of students' knowledge construction of CS.The research questions are as follows:Question 1: What content in science curriculum of our country is related to complex systems? Are they suitable for students to learn by ABM?Question 2: What is the learning environment for constructing scientific knowledge of CS through ABM?Question 3: Using the learning environment designed by this research,what changes have taken place in students' understanding of scientific knowledge of CS?How did that happen?For the first question,we summarized the content topics of CS based on existing research,and then analyzed the content of these topics in textbooks,and evaluated the teaching difficulties and content deficiencies according to the knowledge framework of complex systems.The ABM tool--Starlogo NOVA(SLN)was used to model these CSs,representing the corresponding scientific knowledge of complex systems.It is found that the number of population changes,natural selection,epidemiology and chemical reaction could be represented by the corresponding SLN model,which is suitable for students to learn in the way of ABM.The second question was on the basis of the first one.We selected three topics as the learning content: the use of antibiotics,epidemics and the hare in the farm.We designed the prototype of the learning environment,test and optimize it for teaching.Finally,the SLN toolkit is developed as a learning tool for students.The learning task consisted of four phases — "analysis and prediction ? modeling and verification ?expansion and exploration?summary and generalization",and the student work sheet is designed for each phase.To answer the third question,an empirical study was carried out among students in grades 7 and 8 in a junior high school in S city.The continuous comparison method was used to collect and analyze student cases.It was found that,students' predictions at the macro level of complex systems were often one-sided before learning.Although the micro-level information has been prompted,it was difficult for students to explain the mechanism in the micro level.After invention,students could integrate micro information into the knowledge structure,developed more and more comprehensive understanding at the macro level,and could form relatively complex cross-layer reasoning and explanations.The learning process of students showed that the process of constructing models could prompt students to analyze CS from the perspective of the agent.In the process of simulation,the running of the computer model born the complex reasoning work,so that students could quickly obtain the changes of the system under the different conditions,and consider the changes presented in the model to explain.In short,students construct scientific knowledge of CS by modeling and simulation of human-computer interaction.This study proves that it is feasible for students to learn science knowledge of CS through ABM,which can be applied to science teaching in the future.More science topics of CS should be developed as the research is carried on further,and the interdisciplinary courses of computer programming and scientific inquiry will be designed.