Grounded within current reform recommendations and built upon Giere’s views (1986, 1999) on model-based science, we propose an alternative approach to science education which we refer to as the Evidence-Explanation (EE) Continuum. The approach addresses conceptual, epistemological, and social domains of knowledge, and places emphasis on the epistemological conversations about data acquisitions and transformations in the sciences. The steps of data transformation, which we refer to as data-texts, we argue, unfold the processes of using evidence during knowledge building and reveal the dynamics of scientific practices. Data-texts involve (a) obtaining observations/measurements to become data; (b) selecting and interpreting data to become evidence; (c) using evidence to ascertain patterns and develop models; and (d) utilizing the patterns and models to propose and refine explanations. Throughout the transformations of the EE continuum, there are stages of transition that foster the engagement of learners in negotiations of meaning and collective construction of knowledge. A focus on the EE continuum facilitates the emergence of further insights, both by questioning the nature of the data and its multiple possibilities for change and representations and by reflecting on the nature of the explanations. The shift of emphasis to the epistemics of science holds implications for the design of learning environments that support learners in developing contemporary understandings of the nature and processes of scientific practices.

基于当前的改革建议，并基于Giere关于基于模型的科学的观点（1986，1999），我们提出了另一种科学教育方法，我们称之为证据解释（EE）连续体。该方法处理知识的概念，认识论和社会领域，并重点关注关于科学中数据获取和转换的认识论对话。数据转换的步骤，我们称为数据文本，我们认为，在知识构建过程中展开使用证据的过程，并揭示科学实践的动态。数据文本涉及（a）获得观测/测量结果以成为数据；（b）选择和解释数据以作为证据；（c）使用证据确定模式并开发模型；（d）利用模式和模型来提出和完善解释。在EE连续体的整个转换过程中，有一些过渡阶段可以促进学习者参与意义的谈判和知识的集体建构。通过质疑数据的性质及其更改和表示的多种可能性，以及反思解释的性质，着重于EE连续体将促进更多见解的出现。