Student Research Guide WQ25: Evolution of Computation in Scientific Research

The effect of the evolution of computation on scientists and scientific research

 This is a student created research guide for English 102 & Library 201 Learning community

This guide will examine the transformative effect of computing on scientific methodologies and the scientific research community as a whole.

The research thesis will analyze the profound shifts that computing has caused in the analysis, collection, and utilization of information. Further, it will show how these developments have changed to scientific landscape by promoting interdisciplinary efforts in solving complex research problems.

• What role does computation play in the increased ability to process information at a faster and more efficient way?
• How has computation changed the way that research models are structured?
• How has the integration of computation changed training for researchers?
• How has the collaboration between 'wet' and 'dry' sciences changed the scientific landscape and moved research forward and provided challenges?
• How has the digitization of scientific research provided sustainability and ethical concerns to researchers?

The integration of computation technologies in scientific research has changed the methodologies, educational requirements, and ethical considerations of STEM disciplines. As this technology continues to evolve researchers across various fields of the scientific landscape must adapt to and more computational and interdisciplinary approach to research. This research paper examines how the profound influence of computational tools, including machine learning, artificial intelligence, and high- performance computing has affected the modern research process. To investigate this topic, a comprehensive review of academic journals, government agencies, and industry reports were found in SVC databases, Google Scholar, the Pew Research Center, and government and university websites. Thirteen sources were complied with and annotated. The findings indicate that computational tools have significantly improved research efficiency and capabilities. However, they have introduced new challenges, such as a need for standardized computational training among researchers, concerns with research integrity, and ethical and sustainability concerns. The results indicate that modern researchers and scientists need to be equipped with the skills and knowledge necessary to function ethically and efficiently in a computational research environment.

Computation has been a corner stone in research across many disciplines, including biology, physics, mathematics. It plays a role in data management, algorithmic development, and problem solving, enabling researchers to process vast amounts of information efficiently. Its transformational effects have allowed many fields to advance in ways that were previously impossible and significantly altered research paradigms. As an essential component of modern scientific inquiry, computation continues to drive innovation and discovery across all fields.

The video provides a comprehensive overview of machine learning and how it works. The video explains how machine learning works by first demonstrating how to judge a data set with human input and then replicating that on its own. This resource provides insight on the topic by displaying how computation can rapidly and effectively analyze large and complex data sets as well as how its reliance on human judgement can pose a problem. 

Source citation:

Kessel, Patrick V. “Methods 101: What is Machine Learning, and How Does it Work?” Youtube, uploaded by Pew Research Center, 4 June 2020, Methods 101: What is machine learning, and how does it work? - YouTube.