AIMS: Analyzing Images to Learn Mathematics and Statistics

这个改进本科STEM教育（IUSE）项目是基于学生从事真正的生物学研究的知识，无论是通过课堂外的经验，还是通过课堂上的开放性探究活动，都能学到更多，更有动力。项目团队正在制作学习材料，为生物学入门课的学生提供真实的研究经验。生物学课程的挑战之一是许多学生对数学和统计学不感兴趣和不舒服。正在创建、评估和传播的学习材料允许有意义的假设形成、数据收集和最重要的分析，通过对迷人生物现象的图像分析来吸引学生的兴趣。摄影图像能迅速捕捉人们的兴趣，并能传递大量的信息。这个项目是利用这些现象来创造引人入胜的教育材料，向生物学学生教授定量和分析技能。通过图像分析，学生们可以观察和测量真实的生物现象，这些图像或视频本身就很有趣。向他们展示一个有形的研究框架和背景信息，要求他们提出假设，然后要求他们从一组图像/视频中收集第一手数据。通过这些图像，学生们参与到科学的过程中，首先是在表面上听到有趣的研究项目和检查吸收的摄影图像；但在数据收集和随后的分析过程中，会更深入。图像分析辅助教学的能力在数学、地球工程和计算机科学的教学文献中已经有了基础，但在生物学中却很少使用。作为学习材料基础的研究项目包括生态学、行为科学、神经科学、进化以及分子和细胞过程。项目评估包括教学前和教学后的评估，以检查学生的学习成果，以及直接询问学生对生物科学的态度。在雷德福大学测试的学习模块随后将在广泛的合作机构进行测试，包括弗吉尼亚理工大学、瓦萨学院和罗阿诺克学院。正在产生的知识是将这些认知技能整合到全国传统生物学课程中的一种手段。

This Improving Undergraduate STEM Education (IUSE) project is based on the knowledge that students engaged in real biological research, either via experiences outside of the class, or open-inquiry activities in the class, learn more and are better motivated. The project team is generating learning materials that provide authentic research experiences for students in introductory biology classes. One of the challenges in biology curricula is the disinterest and discomfort many students have with mathematics and statistics. The learning materials being created, assessed, and disseminated allow meaningful hypothesis formation, data collection, and most importantly analyses, that capture student interest via image analysis of fascinating biological phenomena. Photographic images can quickly capture people's interest, and can transmit a great deal of information. This project is capitalizing on these phenomena to create engaging educational materials to teach quantitative and analytical skills to biology students. Students are presented with inherently interesting sets of still images or videos from which they can observe and measure real biological phenomena, via image analysis. They are presented with a tangible research framework and given background information, asked to develop hypotheses, and then asked to collect data from a set of images/videos, firsthand. Through these images, students are engaged in the process of science, first superficially as they hear interesting research projects and examine absorbing photographic images; but then more deeply during data collection and subsequent analyses. The power of image analysis to aid instruction already has a foundation in the pedagogical literature for mathematics, geo-engineering, and computer science, but has been more rarely used in biology. The research projects being used as the foundation of the learning materials include ecology, behavioral science, neuroscience, evolution, and molecular and cellular processes. Project evaluation includes pre- and post-instruction assessment to examine student learning gains, as well as direct queries concerning students' attitudes to the biological sciences. Learning modules tested at Radford University are then being tested at a broad range of partner institutions, including Virginia Tech, Vassar College, and Roanoke College. The knowledge being generated is a means for these cognitive skills to be integrated into traditional biology curricula nationwide.