The Challenge of Developing Systems Thinkers: How Misconceptions About Complex Causality Contribute to Fundamental Problems in Scientific Learning

培养系统思考者的挑战：对复杂因果关系的误解如何导致科学学习中的基本问题

• 批准号: 9725502
• 负责人: Tina Grotzer
• 金额: $ 83.77万
• 依托单位: Harvard University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 1998
• 资助国家: 美国
• 起止时间: 1998-07-01 至 2003-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=9725502&HistoricalAwards=false
• 关键词: Challenge; Developing; Systems; Thinkers; How

9725502 Grotzer Learning to understand and analyze the systems concepts present in many different scientific phenomena entails interpreting a variety of types of complex causal relationships. Yet students tend to hold preconceptions and misconceptions about causality that hinder learning and systematically generate misconceptions in science content. There are different levels of increasingly sophisticated forms of complex causality. At each level, learners face new cognitive challenges where mismatches between students' causal models and scientific causal models arise and imperil scientific understandings. Despite the fundamental importance of complex causal models, few materials exist to help teachers support student learning about complex causal forms. A taxonomy of increasingly complex causal models that represent different sets of science understandings will be generated. Students' understandings of the different models and the inherent protoconcepts will be probed using computer and paper-based assessments, interviews, and observations. Mismatches between students' and scientific models will be investigated to identify and examine points of difficulty. Researchers and teachers will then work together to develop and assess intervention materials designed to help students beyond these points of difficulty. The resulting program, tentatively titled "The Understandings of Consequence Program," will be constructivist in nature. It will invite explicit student reflection upon causal models as situated in science content and how they map onto different scientific phenomenon. Methods will be developed for modeling and talking about specific concepts of difficulty. The program will be designed to be infused into existing science programs as well as provide direction for the development of future programs. In the third and final year of the project, the program will be tested with a set of teachers who were not involved in the research and development process. This will suggest what addition al supports may be needed for the broader dissemination of the program as well as provide a means of testing its effectiveness outside the development context. The effectiveness of the program will be evaluated through use of qualitative, conceptual methods as well as standardized assessments. The analysis will combine quantitative and qualitative methods. The program will then be offered for broad dissemination. By focusing on a set of misunderstandings and preconceptions that systematically generate other misunderstandings, the resulting materials and methods should fundamentally impact science learning. It will contribute of halting a pattern of systematically generated misconceptions-enabling conceptual changes that equip learners to grasp complex causal concepts and systematically contribute to deep understanding in science learning instead. ***

学习理解和分析存在于许多不同科学现象中的系统概念，需要解释各种类型的复杂因果关系。然而，学生往往对因果关系持有先入为主的观念和误解，这阻碍了学习，并系统地产生了对科学内容的误解。复杂的因果关系有不同层次的日益复杂的形式。在每一个层次上，学习者都面临着新的认知挑战，学生的因果模型和科学的因果模型之间出现了不匹配，危及科学的理解。尽管复杂因果模型具有根本的重要性，但很少有材料可以帮助教师支持学生学习复杂的因果形式。一个日益复杂的因果模型的分类将产生，代表不同的科学理解集。学生对不同模型和固有原型概念的理解将通过计算机和基于纸张的评估、访谈和观察来探讨。学生模型与科学模型之间的不匹配将被调查，以识别和检查难点。然后，研究人员和教师将共同开发和评估旨在帮助学生克服这些困难的干预材料。由此产生的程序，暂定名为“结果的理解程序”，本质上将是建构主义的。它将邀请学生对科学内容中的因果模型以及它们如何映射到不同的科学现象进行明确的反思。方法将开发建模和讨论具体的难度概念。该计划将被设计为融入现有的科学计划，并为未来计划的发展提供方向。在项目的第三年，也是最后一年，该项目将由一组没有参与研究和开发过程的教师进行测试。这将表明，为了更广泛地传播该方案，可能需要哪些额外的支持，并提供在开发环境之外测试其有效性的方法。该计划的有效性将通过使用定性、概念性方法以及标准化评估来评估。分析将采用定量和定性相结合的方法。然后将提供该方案以供广泛传播。通过关注系统地产生其他误解的一系列误解和先入为主的观念，由此产生的材料和方法应该从根本上影响科学学习。它将有助于阻止系统地产生误解的模式——使概念改变，使学习者能够掌握复杂的因果概念，并系统地促进科学学习中的深刻理解。＊＊＊