The importance of integrating data literacy into the academic curriculum

Do we still need data literacy in the age of AI? Yes, because it provides the foundational knowledge required to navigate data and leverage the capabilities of AI effectively. The World Economic Forum’s The Future of Jobs Report 2023 finds that the job market for data-related roles is experiencing significant growth, with more than 75% of companies planning to adopt big data, cloud computing, and AI technologies in the next five years. Digital platforms, apps, e-commerce, and digital trade rank among the technologies most likely to be adopted, as most businesses plan to incorporate them into their operations.

Gap in application

Yet alarmingly, NASSCOM also reports a 51% gap between the demand and supply for AI/ML Big Data Analytics tech talent in India. While there is a keen interest in AI and cybersecurity, students often lack hands-on experience and practical knowledge. Bridging this gap between theoretical understanding and practical application is crucial and educators have to raise awareness of the data literacy skills gap. Here’s what they can do to prepare students for careers that will rely on data skills:

Integrating data literacy into the education system requires a multi-faceted approach that goes beyond traditional teaching methods. One effective strategy is to incorporate real-world data into lesson plans, allowing students to work with authentic data sets and gain practical experience in data analysis. For example, students could analyse data on climate change to understand its impact on the environment, or examine data on social media usage to explore trends in online behaviour.

Seamless integration

Another effective approach is to integrate data literacy seamlessly into existing subjects such as Maths, Science, and Social Studies for students to grasp the relevance of data analysis across various contexts. For example, in Science, students could analyse data on population growth to understand the impact of human activity on the environment. In medical education, students can leverage patient data to prepare dashboards outlining a patient’s case, thereby enhancing their practical understanding of data utilisation in their field. This enables students to derive insights from data and conduct meaningful analyses.

Educational institutions must forge the right industry partnerships to better align students’ learning with employers’ needs to benefit both the business community and the education sector. Many companies offer online tools and certification programmes that can help facilitate structured learning pathways for students by offering a range of resources, including free software, and online training to equip students with the necessary skills for roles such as business analyst, data architect, data engineer and so on. The success of such programmes can be measured not only by the number of students enrolled but also by their subsequent employment rates as well as their qualification and certification outcomes. Additionally, success can be gauged by the extent to which graduates contribute meaningfully to the workforce and how acquiring new-age skills enhances their professional profiles.

These initiatives, implemented across numerous universities and colleges globally including institutions in India such as IITs, IIMs, and National Institutes of Technology (NITs), underscore the commitment to preparing students for the data-driven world. Through strategic partnerships and robust academic programmes of tech companies, educational institutions can effectively bridge the gap between classroom learning and industry requirements

Constant learning

Educators must recognise that data literacy is not merely a skill that’s nice to have but a necessity in preparing students for the future. By analysing student performance data, educators can identify areas for improvement and allocate resources effectively to address gaps in learning and empower students with the skills needed to progress into new roles emerging in an increasingly digital-first, data-driven world.

AI, and now generative AI, is rapidly taking over the way we work, giving more power to data than ever. The Data Literacy: The Upskilling Evolution report confirms that over 58% of employees believe that data literacy is crucial to stay relevant. The ability to work effectively with data from Gen AI cannot be acquired in a day. So what it means to be data literate is constantly changing and evolving with each technology innovation. But by making learning a deliberate and ongoing process, students must be equipped with the data skills needed to build a pipeline of talent for the data-driven world of work we find ourselves in.

The writer is the Senior Academic Programme Manager, Qlik- Asia Pacific