Dr Ignatius Luke Chan, PhD, ACLP, Senior Lecturer at the London School of Business and Finance in Singapore, investigates the current technological revolution and changes in the research paradigm of global science
In the current global context, to a certain extent, we have definitely seen a shift in the direction of research over the past 10 years. From its humble beginnings in trial and error, research experiments led to the discovery of many other findings and inventions we see around us today.
In recent years, we have now seen a shift from the qualitative and quantitative realm of trial and error, and positing hypotheses with research questions to a more technologically advanced realm using big data, cloud computing, artificial intelligence (AI), and machine learning (ML).
In the past, the science field seemed to be very heavily focused on research methodologies such as interviews, analysis, case studies, and thematics, and these were used to test theories and to understand how behaviour, social constructs, and cultures work.
On the other hand, we had our natural science and engineering research, the focal point of which was empirical and experimental, and testing was done in a controlled environment, either with a controlled group or in a laboratory.
Research: A new technological revolution and paradigm
In the current day, we have noticed that research has now shifted into a new technological revolution and paradigm where not only do we deal with empirical and qualitative studies, but the use of technology, and design science research (DSR) to enhance design thinking and systems thinking and explore beyond the surface.
DSR has two unique focuses that are brought to the research table – that being the focus of problem-solving, where the primary goal is to solve a specific, practical problem by developing an artefact in the way of a software system, a method, or a framework, to answer or mitigate the problem at hand, and the other being knowledge contribution.
Aside from coming up with a methodology or framework to solve a practical problem, DSR aims to contribute to both the theoretical understanding of the problem
domain and the general knowledge of design principles regarding research.
The new research paradigm of global science now goes into AI and ML, while at the same time, exploring interdisciplinary collaboration across multiple platforms and industries. With the help of connectivity and collaboration through fostered relationships, global science is not looking into a system of self-decisionmaking, predictive alerts based on trends, and a worldwide collaboration on data and findings of research studies.
Technologies such as AI, ML, and data analytics
It is essential first to acknowledge that the future of education today is supported by a hybrid learning structure. A model where a piece is taken from each structure and built into a learning model for modern learners. This is where digitalisation and technologies such as AI, ML, and data analytics play a vital role.
It is no longer only about building skills in performing research but also transforming research by knowledge sharing and data optimisation with the aid of AI and ML.
Through collaboration and interdisciplinary learning practices, knowledge increases and, in doing so, pushes curiosity about other possible topics to be further explored. Participating in interdisciplinary collaboration brings the much-needed awareness to build meaningful connections across different disciplines and themes.
A call to push research collaboration boundaries
The cross of AI and ML in the healthcare industry proved useful; however, it is not entirely reliant. While it fills the gaps in knowledge and allows other researchers who may have been working on similar research to push the boundaries of collaboration to give back to the body of knowledge through interdisciplinary collaboration. With this data being shared with other researchers across the globe, it will help immensely with scientific progress.
In the past 15 years, we have seen a 10% increase in the number of published articles that are internationally collaborative. This shows the direction in which research has now taken, as opposed to 15 years prior.
Researchers are now looking more for collaborative research and, experiments and data-sharing to enhance their research in their fields. With the help of the advancement of technology, AI, ML, data-sharing, and even Cloud computing, it is safe to say that we are definitely witnessing a new technological revolution and significant shifts in the research paradigm of global science.
