An Overview of Big Data in Education (by UNESCO Bangkok)

30.01.2015

With no precise definition in place, the term big datausually refers to any data that is too large to be handled effectively by the traditional database software. The common 3 V’s of big data are volume, referring to the amount of information, velocity, referring to the speed of data, and variety, referring to the various type of data (Mayer-Schonberger & Cukier, 2013). Big data has been opening new horizons and making a difference in many sectors of our society. Our participation in big data, whether through generating or using it, is quickly becoming a norm, frequently without our realizing. Every click on a given device affects how the Internet responds to and guides us, ranging from the price ranges for airline tickets, to Tweeter’s feeding of posts, to Google’s location services and search engines, to receiving a reminder from an e-learning course detected from the user’s inactivity. With time, we have realized the seemingly endless potential of big data in our lives that could bring about innovation, and provide an array of tools and services for our daily use.

Also known as learning analytics, the potential of big data has created a great hope to transform education. Big data tracks interaction and direct feedback between learners and teachers, continuous monitoring of progress and attendance, more opportunities for personalized learning and guided pathways to the students’ interests. The users generate all kinds of data, and from those choices, they can be taken from one activity to the next. It is the learning analytics factor of big data that can guide the students and teachers to better understand the trajectory of the learner’s progress, to adapt to the learner’s understanding of a subject, analyze his/her social relationship and network, as well as evaluate not only the quantity, but also the quality of the learner’s input. At the macro level, the analysis of this data can contribute to sound policy development by providing access to numerous factors from the environments, approaches, and pedagogies that bring about actual results.

One of the most promising outlooks that big data implies is its richness that may enable us to understand how people learn and how learning occurs online. With online courses available to almost all students in the world, platforms and tools such as MOOCs can simultaneously analyze the students’ behavioral and learning patterns. In effect, at Harvard Graduate School of Education, MOOCs are being used to explore big data from their MOOCs to optimize the online learning environment. Given that the MOOCs technology is still at the early stage, it is much anticipated how the big data will be collected and used to help enhance online learning experiences.

Nevertheless, as with many of technology-driven projects and innovations, there are also challenges to consider. Firstly, big data, as the name tells, is enormous. Without a critical eye and analytical ability, data remains as data and can easily become another form of information waste. It is when in the right hands of a critical analyst that this data can speak to the benefit of our development. Additionally, as any data, big or small, it has flaws, and cannot provide a 360 degree view of our classrooms, teachers and learners.

Secondly, one of the biggest concerns for the data-driven future is the increasing transparency, potentially violating privacy and security of the users. In education, the information that big data generates can be very useful for teachers, school leaders and students, but can also be sensitive and private. Knowing how each student performs, what they like or dislike can be valuable, and yet should not always be shared. It is thus paramount to remember and protect the privacy of the individual.

Thirdly, big data should not become the panacea to understanding how to teach or learn, as in the end, it is our teachers who navigate through and lead our students toward meaningful educational transformations. It is them who can best assess the students’ needs and interests. It is them who have the ability to go beyond that data and reflect on the why’s and the how’s.

Fourthly, much of data input is simply not existent in many parts of the world today. Even within a country, there are patches of little to no information available, as some communities may not have access to devices due to various socio-economic or geographical reasons, and thus cannot access the data or participate in producing it.

Lastly, it is important to be aware of the common hype that new technologies and innovations receive once they are discovered or gain momentum. Too often, the successes and predictions are exaggerated, while companies and organizations dive into using the latest innovation with the hope of eliminating the existing challenges, not always realizing the costs and the time necessary to witness the actual impact and results.

With this evident and rapid advent of big data, the UN has been responding and getting involved in developing and analyzing this tool for the social benefit, recognizing the value and potential of big data. The UN Global Pulse initiative (2009) was created to leverage the discoveries and innovation within data, its collection and analysis for decision-making and understanding for development and livelihood improvement. The most recent publication, “A World That Counts: Mobilising the Data Revolution for Sustainable Development”, developed by the Data Revolution Group, identifies a few global challenges: invisibility and inequality, addressing the evident gap between the data-poor and data-rich communities.

Consequently, some questions to consider are: with the rapidly increasing data-driven information predicting the next steps or choices for us, how will that affect our freedom and decision-making? No matter what data we analyze, it will always have its flaws and blind spots. It is crucial to remember that big data is not always the right data for every context. And it certainly cannot provide a complete view of everything and everyone. The interpretation bias should always be taken into account, while finding ways to utilize it to benefit a specific context. In conclusion, it is important to realize the immense powers of big data, but not become controlled or misled by it. Projects involving big data can also be extremely costly and time-consuming. However, the smart marriage of education and technology can provide a foundation for a stronger link between how we learn and what we learn, and consequently, help our societies continue the quest for sustainable development and lifelong learning.

References:

Mayer-Schonberger, V. & Cukier, K. (2013). Big Data: A Revolution that Will Transform how We Live, Work and Think. New York: Houghton Mifflin Harcourt Publishing Company. Retrieved from www.google.co.th/books.

UNESCO-IITE. (2012). Policy Brief. Learning Analytics. Retrieved from iite.unesco.org/files/policy_briefs/pdf/en/learning_analytics.pdf.