How Big Data Will Transform Social Studies in the Future

In the era of big data, social studies classrooms are being transformed in different ways. For starters big data is blurring the lines between the social sciences, the humanities, and higher mathematics. By unlocking the deep data on civics, history, sociology, and other areas, the field of big data is enabling streamlined data processing and analytics in modern social studies classrooms. But before we dive deeper into that, let’s take a closer look at the growing field of big data itself.

What is Big Data?

Big data is a relatively new field of study surrounding the systematic collection, handling, and analysis of large data sets too complex for traditional data processing. Today, big data has become a crucial discipline for any industry, organization, enterprise, or classroom that handles large amounts of data. Through the proper application of big data principles, any type of information can be organized and analyzed to glean actionable insights and predict outcomes. Not surprisingly, big data also has applications in different areas of not just social studies but also business.

This is particularly true as the worldwide volume of data is projected to reach an annual 180 trillion gigabytes in 2025. In a nutshell, this is why big data experts have become highly in demand, which has resulted in big data evolving into a specialized academic concentration. This can be observed in how both online and traditional universities have developed training programs focused on data science and analytics. Through remote courses in database principles, data visualization, advanced analytics, and predictive modeling, Maryville University’s online master’s in business data analytics is helping meet the demand for operational, financial, management, and market research analysts across the private and public spheres. The same can be said of the University of Minnesota’s master’s degree in data science, in which students are also getting hands-on, industry-relevant training in the handling and predictive modeling of data.

In short, higher education institutions have already developed special academic programs aimed at advancing big data. In turn, this ensures that analytics and data science will play a more significant role in the evolution of not just social studies but many other concentrations where research, business, and education intersect.

 

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Big Data and Social Biases

Using data from decades of both Hollywood and Bollywood films, scientists have found that they can use artificial intelligence (AI) to track different social biases across these massive and extremely culturally influential enterprises. Through insights from an automated computer analysis model crafted by Carnegie Mellon University’s computer scientists, researchers analyzed 100 Bollywood and 100 top-grossing Hollywood films from the past seventy years. Faced with the subtitle data of 1,400 movies, they used AI-driven statistical language models to search for social and gender biases.

The result is an AI model that can analyze these factors in thousands of movies in a matter of just days. Apart from making the work of cultural critics and analysts easier, this method is also an efficient way of running a fine-tooth comb through film content. And this is just the tip of the iceberg. Theoretically, the same method could be used to analyze and look for different factors in practically any type of media. From films, music, and books to magazine articles, radio transcripts, online blogs, and social media content, there’s tons of data to be found in the world’s extensive volumes of art, media, and literature.

In the social studies classroom, this type of AI-enabled data tool can fast-track organizing and analyzing information from cultural products. Apart from history, this also enables faster research methodologies in data-rich subjects such as geography, sociology, and civics. Armed with such tools, social studies students can build key analysis and critical-thinking skills more efficiently—without getting bogged down by the data.

 

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Big Data in the Classroom

Big data seeks to simplify the increasingly large and interconnected sets of raw social data across the world’s industries, communities, and disciplines. In today’s virtual and hybrid classrooms, this means potentially streamlining the use of Webb’s Depth-of-Knowledge (DOK) model.

Through big-data-driven tools like the aforementioned AI model for film content analysis, teachers can more easily empower students through the latter levels of the DOK spectrum. While the first levels are all about recall and summarization, the last two levels revolve around strategic intentional thinking, extended thinking, and data analysis. And with big data tools in the mix, students can more quickly and efficiently arrive at sound conclusions and evaluations—however complex the data or the problem is at hand.

Currently, there are near-infinite ways for teachers to apply DOK alongside big data tools in the classroom. The world is plagued with problems such as world hunger, political conflicts, and other crises that can be mined for actionable data. Teachers can use global concerns as a focal point for students to use big data tools, particularly for analyzing this data to develop specific solutions. These solutions—along with the methods used to derive them—can be organized into a visual presentation. Apart from developing critical thinking skills, this can also introduce students to data visualization, a key component vital in data science.

This is just one of the many possible applications of big data in the classroom. As the Halo Ethnographic Bureau details, big data is empowering social researchers to handle increasingly large, varied, and complex data sets. And through the use of AI and machine learning tools, it’s also allowing social studies practitioners to record and follow phenomena with precision in real time. This brings us to how big data can be put to practical use in different social studies concentrations.

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Big Data in Social Studies

As illustrated by the aforementioned examples, the main benefit of big data is how it can streamline social studies research. This will allow social studies classes to cover so much more. In geography, the use of analytics on geospatial data can fast-track identifying patterns related to resource consumption, industrial land use, and habitation. For researchers in history, data-crunching tools can speed up analysis, events, technologies, artifacts, and other historical archives. In civics, data science will come in handy for analyzing large volumes of legal writings on laws, policies, civil obligations, and civil rights. And this is just the beginning. As big data has turned into a specialized academic field, it will continue to shape—and be shaped—by social studies curricula.

From cultural insights and virtual classroom applications to the evolution of social studies itself, big data is playing a larger role wherever social science data can be found. And given the rapid development in these and more big data use cases, this development is bound to continue in the next decades.


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Sociology graduate, amateur computer programmer, and ancient history buff Melina Casey believes that classrooms can benefit a lot from digital transformation. When she’s not chasing deadlines or reading French literature, she likes to relaxing walks outdoors with Mr. Burns, her 5-year old Miniature Pinscher.

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