Doane DIVAS: Digital Imaging and Vision Applications in Science

数字成像和视觉在科学中的应用（DIVAS）项目将通过创建一个教学和程序化的计算材料“入口”，使自然科学专业的学生能够参与真实的计算问题，从而对促进国家的繁荣和福利具有重要意义和重要性。DIVAS最终将增加经过计算培训的熟练科学家进入劳动力市场的数量，解决这些工人的严重短缺问题。DIVAS的目标是开发，使用和测试教学实践和课程创新，这将吸引和培训STEM本科生进行与图像处理相关的计算和计算。范围将是评估的做法和创新，在传统的课堂环境中，在非正式的培训“靴子营地”，并在本科研究设置对学生的自我效能感，计算能力，以及预期和实际的职业道路的影响。该项目小组将使用一个既定的工具来评估计算自我效能，并将开发一个新的工具来评估各种教育环境中的计算能力。自我效能，计算技能和职业选择的增长将在每次学生从事DIVAS创新进行评估。这一合作项目将建立和加强与主要学术机构和组织的伙伴关系，并将优先考虑在更广泛的DIVAS网络中采用的做法和创新。DIVAS将测试在传统学习环境、非正式培训环境和专业环境中进行的教育干预的有效性。

The Digital Imaging and Vision Applications in Science (DIVAS) project will have strong significance and importance toward advancing the prosperity and welfare of the country by creating a pedagogical and programmatic 'onramp' of computational materials that empower natural science majors to engage in authentic computational problems. DIVAS will ultimately increase the number of skilled computationally trained scientists entering the workforce, addressing the critical shortage of these workers. DIVAS' goal is to develop, use, and test instructional practices and curricular innovations that will engage and train STEM undergraduates in computation and computing related to image processing. The scope will be to assess practices and innovations in the traditional classroom environment, in informal training 'boot camps', and in undergraduate research settings for their impact on student self-efficacy, computational competency, and intended and actual career paths. The project team will use an established instrument for assessing self-efficacy in computation and will develop a new tool to assess computational competency across a wide range of educational settings. Growth in self-efficacy, computational skills, and career choice will be assessed each time a student engages in a DIVAS innovation. This collaborative project will establish and strengthen partnerships with key academic institutions and organizations and will prioritize practices and innovations for adoption within a broader DIVAS network. DIVAS will test the effectiveness of educational interventions occurring in the traditional learning environment, in informal training environments, and in professional settings.