摘要
计算机模拟情境摆脱了实验室研究和现场研究的不足,满足了复杂问题解决的复杂性、动态性和模糊性等特征,受到研究者们的青睐。近年来,各种模拟情境在复杂问题解决研究中得到运用,其内部逻辑结构主要有线性结构方程和有限状态自动化,线性结构方程适用于等距数据,而有限状态自动化适用于称名数据。当前,对复杂问题解决的测量注重结果,而相对忽视过程。未来的模拟情境可以从问题特征、任务逻辑和测量方式来提高信度和效度。
Computer simulations, free from both the narrow straits of the laboratory and the field study, satisfied the characteristics of complex problem solving, such as complexity, dynamic, and intranpancy. An increasing number ofresearchers have used computer simulations or micro-worlds as research methods to explore the behaviors in complex problem solving situation. Currently, two formal frameworks, linear structural equations （LSE） and finite state automata （FSA）, have been widely used in the simulations. Based on the requirement of the systems, two measurement approaches, result-orientation and process-orientation, were developed. However, most research emphasized the results and ignored the process. Fi- nally, the paper proposed possible solutions to improve the quality of computer simulations, including the character of the problem, the logic of task, and the measurement.
出处
《应用心理学》
CSSCI
2014年第2期171-179,共9页
Chinese Journal of Applied Psychology
基金
国家自然青年科学项目(71101128)
国家自然科学项目(71071137)
教育部社科青年项目(10YJC630075)
关键词
复杂问题解决
计算机模拟
线性结构方程
有限状态自动化
complex problem solving, computer-simulation, linear equation system, finite state automata
