Seeing Scientifically: Scaffolding Observation of Complex Visual Phenomena

“科学地观看”项目将研究一种支持博物馆游客体验的新方式，使他们能够对活体显微标本进行真实的科学观察。通过采用当前生物研究中现有的计算成像技术，该项目旨在鼓励和支持参观者进行科学观察，即提出富有成效的问题，解释图像丰富的信息，并从视觉证据中做出推断，这些证据日益成为当前生物研究的特征。脚手架（例如，视觉提示或支持学习的信息）将由一个虚拟向导和提示系统组成，该系统对访问者所看到的内容作出反应。脚手架提示将被覆盖在一个实时的、高密度的活体样本图像上，参观者正在用研究级显微镜进行调查。项目研究将提供早期知识，帮助非正式学习者在真实的科学观察实践中，利用科学家自己使用的设备和技术看到的复杂、动态的视觉证据，培养他们。项目研究和资源将通过出版物、会议演讲和通过nsf支持的非正规科学网站和其他相关网站的资源共享，广泛传播给学习科学研究人员、非正式科学从业者和其他感兴趣的受众。作为加强非正式环境学习总体战略的一部分，推进非正式STEM学习（AISL）项目为各种环境中使用的创新资源提供资金。这包括提供多种途径，扩大STEM学习经验的获取和参与，推进非正式环境中STEM学习的创新研究和评估，以及发展参与者对深度学习的理解。该项目将以创新的显微镜展览为原型，为参观者提供对活体标本及其生物过程的科学观察。最重要的假设是，对实时视觉现象的科学观察可以让学习者深入了解现代科学的内容、工具和实践，而现代科学越来越依赖于基于图像的数据。通过三轮迭代的原型开发和评估，该项目将产生以下相关问题的早期发现：(1)在无中介展览中有哪些有前途的脚手架观察活标本的方法；(2)如何将计算成像技术整合到显微镜展览中，以吸引和支撑学习者提出富有成效的问题，解释他们所看到的，并从复杂的动态图像中做出基于证据的推断。收集和分析数据的方法是，对参观者进行“有声思考”访谈，了解他们对所观察到的生物现象的兴趣和描述；对访问者提问的类型和答案、相关特征、推理和脚手架的使用进行编码；并对羁押时间、提问、回答、推论和脚手架使用情况进行统计比较。项目的研究结果将促成更严格的研究，将脚手架和计算成像技术结合起来，有效地支持在图像丰富的科学领域进行科学观测。

The Seeing Scientifically project will research a new way of supporting museum visitor experiences so they can have authentic scientific observation of live microscopic specimens. By adapting existing computational imaging techniques from current biological research, the project aims to encourage and support visitors in observing scientifically, that is, in asking productive questions, interpreting image-rich information, and making inferences from visual evidence that increasingly characterizes current biological research. The scaffolding (e.g., visual cues or information supporting learning) will consist of a system of virtual guides and prompts that are responsive to what visitors see. The scaffolding prompts will be overlaid on a real time, high-density image of a live sample that the visitor is investigating with a research grade microscope. Project research will contribute early knowledge on ways to scaffold informal learners in the practice of authentic scientific observation with the complex, dynamic visual evidence that scientists themselves see using the equipment and techniques they use. Project research and resources will be widely disseminated to learning science researchers, informal science practitioners, and other interested audiences through publications, conference presentations and sharing of resources via the NSF-supported informalscience.org website and other relevant websites.As part of its overall strategy to enhance learning in informal environments, the Advancing Informal STEM Learning (AISL) program funds innovative resources for use in a variety of settings. This includes providing multiple pathways for broadening access to and engagement in STEM learning experiences, advancing innovative research on and assessment of STEM learning in informal environments, and developing understandings of deeper learning by participants. The project will prototype an innovative microscope exhibit that scaffolds visitors in scientific observation of live specimens and their biological processes. The overarching hypothesis is that scientific observation of real-time visual phenomena can deeply engage learners with the content, tools and practices of modern science, which increasingly rely on image-based data. Through three rounds of iterative prototype development and evaluation, the project will generate early findings for the following related questions: (1) what are promising ways of scaffolding observation of live specimens at an unmediated exhibit; (2) How can computational imaging techniques be integrated into a microscope exhibit to engage and scaffold learners to ask productive questions, interpret what they see, and make evidence-based inferences from complex, dynamic images. Data will be collected and analyzed by coding think-aloud interviews with visitors concerning their interest in and description of the biological phenomenon observed; coding of think aloud transcripts of visitor questions types and answers, relevant features noted, inferences and scaffold use; and statistical comparison of holding time, questions asked, answers, inferences, and scaffold use. Project findings will seed more rigorous research on the combination of scaffolding and computational imaging techniques effective for supporting scientific observation in image-rich areas of science.