Big Data in Education
As we already know, in the world of big data, bigger means better. Indeed, the more data points we have about anything or any situation, the more reliable the insights or predictions emerged from our analysis are. From the reading assignment and our class discussion, we all agree that the era of big data which empowers many ongoing waves of digital transformation including artificial intelligence, data science, and Internet of Things has been underway and inevitably changed every aspects of our life and society.
Many scientists and scholars across disciplines such as computer science, physics, economics, mathematics, and bioinformatics have been researching big data for years and making many promising applications which can be found in the news very frequently. For example, the article “The Complete Beginner's Guide To Big Data In 2017” will give you a glimpse of how scientists are using big data to not only make our daily lives easier and more convenient but also make us live longer and healthier by remedying diseases, predicting and responding to natural disasters, and preventing crimes. However, when it comes to education, the discussion regarding the impact and practical application of big data remains scant.
It seems to me that education is always “laggard” in terms of new technology adoption. By the way, if you have never learned about the “Technology Adoption Life Cycle” which is a sociological model categorizing technology adopters into groups based on demographic and psychological characteristics, here is a quick overview. Unlike other scientific disciplines, education has faced many unique challenges when getting into big data. The article “Big Data Analysis in Higher Education: Promises and Pitfalls” pointed out some of these challenges, such as privacy and security concerns when collecting data, lack of computational infrastructure and human resources required for analyzing massive sets of data effectively, and so on.
Source: wikipedia
Speaking of the applications of big data in education, analyzing extensive data generated from learning software (e.g MOOCs or learning management systems) and standardized tests to better understand learners’ performance and improve student learning has become more and more common in the recent years. Although big data provides educators unprecedented opportunities to understand different learning styles, individualize learning experience, and potentially enhance learning outcomes, its benefits and pitfalls are still debatable. For instance, in the article “Big data was supposed to fix education. It didn’t. It’s time for small data,” the author argued that while the big data is increasingly utilized by educators and policymakers around the world to reform their education systems, they sometimes forget the fact that big data is only able to reveal correlation, not causality among factors in education. That will cause serious problem if possible causative relationship and many other details that make difference in schools are not scrutinized.
While researching this topic, I have come across some interesting resources that I would like to share with you. The Big Data and Education: The MOOC course produced by Teachers College and published on EdX is an example. Even though the course has ended, you can still access the course lectures and other resources for your own learning. In case you don’t have EdX account, you can view the lectures on the Columbia site. In this course, you will find various techniques and methods used for analyzing big data in education which are called educational data mining or learning analytics. Happy learning!
