Engaged Student Learning: Development of active learning bioinformatics education apps for mobile technology

生物数据的计算机数据库，如人类基因组计划的DNA序列，正在经历前所未有的增长。因此，私营和公共部门非常需要高质量的教育资源来培训学生如何使用计算机分析生物大数据，这是一个被称为生物信息学的专业领域。帮助教授困难的计算机算法概念的新教育方法对全国各地的学院和大学尤为重要。该项目的目的是通过开发智能手机和其他移动技术的主动学习生物信息学教育应用程序来增强学生的学习。这些移动应用程序将允许教师很容易地将主动学习（AL）方法纳入他们的生物信息学入门课程，这将提高学生对生物信息学算法和编程概念的理解。该软件旨在为学生和教师在课堂上解决问题时提供即时反馈，允许学生之间随时分享问题和答案。在整个项目过程中，大约150-200名学生将接触到这些应用程序。生物信息学（计算生物学）在整个生物科学中变得越来越重要。多年来，序列比对、基因组组装、分子结构预测等算法在生物学研究中得到了广泛应用。然而，由下一代测序和其他高通量技术产生的生物数据的指数增长使得生物信息学工具和软件开发比以往任何时候都更加必要。事实上，缺乏在生物信息学方面受过高度训练的学生正在成为研究的一个重大瓶颈。因此，越来越需要高质量的教育资源来培养生物学家在生物信息学理论和应用方面的能力。生物信息学本身不仅是一门令人兴奋和不断发展的STEM学科，而且有可能成为女性进入计算机科学的重要入口。该项目的目标是通过开发移动技术的主动学习生物信息学教育应用程序来增强学生的学习。拟议的移动应用程序将允许教师在他们的生物信息学入门课程中很容易地结合主动学习（AL）方法，这将提高学生对生物信息学算法和编程概念的理解。该软件旨在为学生和老师在课堂上解决问题时提供即时反馈，允许学生之间随时分享问题和答案，并在课堂内外产生几乎无穷无尽的练习问题。

Computer databases of biological data, such as the DNA sequence from the human genome project, are experiencing unprecedented growth. Thus, there is a significant need in the private and public sectors for high-quality educational resources to train students how to use computers to analyze biological big data, an area of expertise known as bioinformatics. New educational approaches that help teach difficult computer algorithm concepts would be especially important for colleges and universities across the country. The purpose of this project is to enhance student learning through the development of active learning bioinformatics education apps for smartphones and other mobile technology. These mobile apps will allow instructors to readily incorporate active learning (AL) approaches in their introductory bioinformatics classes, which will improve student comprehension of bioinformatics algorithms and programming concepts. The software will be designed to provide instant feedback to both students and teachers during in-class problem solving, allow ready sharing of problems and answers among students. Over the course of the project, approximately 150-200 students will be exposed to the apps.Bioinformatics (computational biology) has become increasingly important across the biological sciences. Algorithms for sequence alignment, genome assembly, molecular structure prediction and others have been used widely in biological research for years. However, the exponential growth of biological data generated by next-generation sequencing and other high-throughput technologies has made bioinformatics tools and software development more necessary than ever. Indeed, the lack of students highly trained in bioinformatics is becoming a significant bottleneck to research. Thus, there is a growing need for high-quality educational resources to train biologists in bioinformatics theory and application. Bioinformatics is not only an exciting and growing STEM discipline in its own right but it also has the potential to be a significant entryway for women into computer science. The goal of this project is to enhance student learning through the development of active learning bioinformatics education apps for mobile technology. The proposed mobile apps will allow instructors to readily incorporate active learning (AL) approaches in their introductory bioinformatics classes, which will improve student comprehension of bioinformatics algorithms and programming concepts. The software will be designed to provide instant feedback to both students and teachers during in-class problem solving, allow ready sharing of problems and answers among students, and generate virtually endless problems for practice inside and outside of the classroom.