Big data on what individuals search for online can offer powerful new opportunities for education researchers to understand shifts in student learning experiences and teaching practices. We use the Covid-19 pandemic as a case study. Using time series regression analysis, we find (statistically significant evidence) that in the months following Covid in the United States, students and parents searched online much more often for fundamental concepts, like “How to multiply fractions?” Moreover, we find that this increased Googling of basic concepts strongly correlates with later student learning loss. This suggests that if researchers had been observing this increased searching in real time, they may have been able to see that students and parents were experiencing heightened confusion over basic concepts, likely due to disrupted teaching practices in school. Importantly, we find similar results for numerous countries around the world, highlighting the pandemic’s universal impact on learning. Lastly, we test whether the amount of Googling in different US states and different countries was related to the length of time schools remained closed or to the socioeconomic differences among these different places. Overall, this case vividly highlights the need for education researchers to embrace big data’s growing value and grapple with its significant implications for assessment methodologies. Despite its limitations, Internet search data can serve as a novel, cost-free early-monitoring system to track the effects of educational policies, the role of innovative technologies, and the success of curriculum adaptations.

Authors:
Gregory Eirich, Columbia University, United States

About the Presenter(s)
Gregory Eirich is currently the Director of the Quantitative Methods in the Social Sciences (QMSS) MA Program and a Senior Lecturer in Sociology at Columbia University, New York City, USA.

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