The New Skill Gap: Prioritising & Normalising Domain Expertise
Many institutions are moving from one end of the spectrum of specialisation to the other of multiple disciplines and skills where students in their quest to gain knowledge of multiple skills fail to develop a deep understanding of any particular domain.
Today, higher education institutes are expected to impart marketable skills to their students that prepare them for the dynamic real world. As students continue to graduate and companies continue to hire new talent, the norm persists. However, over the years, the skill gap between existing talent and demand has widened. There have been predictable and unpredictable changes in the student demographics, cultural environment and entrepreneurial mindsets. But with every higher education institution claiming to teach multiple skills, the question remains why a widened gap exists?
The education sector is filled with buzzwords today - skill-based learning, liberal arts, interdisciplinary education and so on. Many institutions are moving from one end of the spectrum of specialisation to the other of multiple disciplines and skills where students in their quest to gain knowledge of multiple skills fail to develop a deep understanding of any particular domain. This leads to a lack of domain competency and gives rise to a new skill gap in the professional industry and society.
Problem-solving or innovation requires a deep understanding of a domain along with the context of its application. This confluence of the domain and the context of application leads to developing deep domain expertise. For instance, consider the inherently interdisciplinary domain of “Data Science”. Data Science intersects with other domains, such as psychology, economics, e-commerce, healthcare etc. Building expertise in Data Science will essentially require a good understanding of the context. Expert Data Scientists enable effective and profitable e-commerce with increased customer satisfaction. On the other hand, it has become imperative for Psychologists to deepen their expertise by plunging in the domain of data science, analyzing big data to better understand shifts or patterns for example in public health or behaviour to predict health and well-being issues and help people better manage their well-being and societal interactions.
Industry and society, today, needs leaders who can envision the bigger picture. Without domain expertise, they may be excellent at a piece of the puzzle but will not know how this piece is helping solve the puzzle. With domain knowledge, a data scientist could do specific feature engineering that’s relevant to the context of any problem and gain an edge over others. She may have the ability to demonstrate that she knows the industry inside out, she talks the language and she can help the business to achieve its target by helping find the right business problem to solve. In comparison, a data scientist with limited domain expertise will be functional with current computational skills that will need to be upgraded frequently.
Without domain expertise, a student or a professional limits his understanding of a problem or a business, cannot define long-term success and ends up limiting his own value. Therefore, it is important for universities to look at this side of the picture and enable their students with a deep domain understanding along with the context of multiple disciplines where their expertise can be applied. This will not be a tactical but a strategic change in how education is imparted in our colleges. However, this change will enable the students to meet the growing industry demands of innovation and leadership.
Such education for building domain expertise is a challenge indeed. But that is the true calling of a University. A University is a global community of knowledge creators – in pursuit of deep domain expertise and new knowledge emerging from the confluence and intersection of different domains – to build a knowledge society for sustainable progress.
Disclaimer: The views expressed in the article above are those of the authors' and do not necessarily represent or reflect the views of this publishing house
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