If you have any problems related to the accessibility of any content (or if you want to request that a specific publication be accessible), please contact us at firstname.lastname@example.org.
Mobile Applications and Delivery of Bioinformatics Education in the Post-Secondary Introductory Biological Science Classroom
AdvisorCrowther, David T.
AltmetricsView Usage Statistics
The field of life science is facing a great challenge, in that the tools are beginning to outpace the user. Technology has rapidly been accelerating while the knowledge to use this new tech has been unable to keep pace. For example: as the recent push to get the faster, cheaper sequencing machine designed has inspired engineers to design contraptions that achieve the original idea but also more complexity, greater amounts of data, and the need for scientists to learn new techniques to understand it all. In this case, by generating large amounts of data in a short amount of time, the ability to interpret the produced numbers becomes increasingly important (Bender, 2015; Frankel & Reid, 2008). Additionally, acquiring access to the tools necessary to interpret data can prove a challenge. While many of these analytical algorithms can be found on the internet or through peer-sharing networks (in the case of specific programs written for the exact task at hand), these are somewhat restricted to the home or office, as they require the user to be at a desktop or laptop computer. This dissertation’s aim is to design a suite of mobile applications that would allow a scientist, a student, a casual researcher, or anyone with a set of data they wish to examine the ability to do so while out of the home or office, as well as test the use of this technology with students in a classroom setting. By integrating facets of informatics research such as math, life science, statistics, and computer science, the user will be able to manipulate and view their dataset from the coffee shop, the passenger seat, the airport, or even the hallway. The Application was designed in a modular format so that the developer can add new operations and techniques that also allows a flexibility in the program to bring in other developers’, researchers’, and students’ ideas, creating a crowdsourced, collaborative endeavor. The main thrust of this design is its integration into the undergraduate classroom. Bringing these analytical tools to the future researchers can open their minds to possibilities they may never have considered. By using this App in workshops, lessons, and units that currently exist within the undergraduate life science curriculum, the students received a hands-on experience they may not be privy to otherwise; whether this is due to availability of technology, access to the technology if it is available, or simply being more proficient in a tool they use daily. The App based on the probability behind sequence similarity (described within) combines both statistics and life science, making it ideal for integration into the class, while the App based on CRISPR techniques combines bioinformatics, biostatistics, and life science concepts, as well as introduces a current and very relevant topic that has potential to impact the world of science and public policy. In addition, secondary schools (high schools) can use this tool to bring in rudimentary concepts. Using their own mobile devices gave a more personal touch to the users’ data analysis and interpretation, and thus yielded a better understanding of the topics. Utilizing current programming tools, current mobile technologies, and scientific backgrounds in conjunction with a series of workshops designed both from a Constructivist combined with a Connectivist approach, it is shown students will not only learn the information and topics presented to them, but enjoy the act of doing so, and help foster a love of life-long learning. Methods included workshops designed to instruct in these Biological, Statistical, and Molecular Biological topics, which were then evaluated prior to and upon completion of these workshops. Using a pre- and post-test format, as well as a Likert-scale survey, students were evaluated on their prior knowledge, the knowledge gained throughout, and the attitudes of utilizing mobile technology. Results showed that there was a significant difference in the knowledge learned and retained through usage of the mobile applications vs traditional computing (desktop/laptop) methods, with the resultant statistical analysis showing a p<0.001, and the threshold at 0.05. Student attitudes also showed that they learned more, and desired not only the subject matter be incorporated, but also the mobile technology within their current and future coursework. Overall, this project cemented the tremendous potential utilizing mobile technology within the classroom poses, in addition showcasing how the future of learning could be more virtual than traditional. Considering the current state of affairs with the global Coronavirus pandemic, with an increasing amount of public and private schools going virtual/remote, the need for more, better, tailored, engaging, and connected scientific material for these types of learning scenarios is higher than ever before.