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

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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.