Discussion: “Big data” includes large, complex, diverse, and unstructured collections of data sets that cannot be easily parsed with common tools. These massive data sets are gathered by a range of technologies, including mobile devices. As data sets grow in size, so too must our ability and capacity to capture, store, analyze, search, visualize, and share information in its ever-increasing volume, variety, velocity, and complexity. Remember that generative AI works on LLMs (Large Language Models) that train themselves on every piece of writing available, so imagine what happens when the training ground shifts from words to images, and our AIs begin to learn from countless video feeds?
523 Inspiration: How big is big data to education? Along with its younger siblings—data mining, data visualization, machine learning, artificial intelligence, and learning analytics—big data is one of the most influential frontiers in education. One of the most compelling aspects of big data is its reach: this bird’s eye view of information is increasingly (re)shaping knowledge and knowledge production, technology and application development, education as a field of practice and research, and how public and private sectors seek to improve education as well as address its problems and challenges, both locally and internationally.
Big Data stood out to me because of its growing role in how learning can be understood and supported. I am particularly interested in this frontier because I am also exploring learning analytics in ETEC 543, which has begun to help me think more critically about what educational data can and cannot tell us. Large datasets can reveal patterns that may not be visible at the individual classroom level, but those patterns still require context and interpretation. I think the challenge for educators will be finding ways to use data to inform decisions without reducing complex learners and learning experiences to numbers alone. Data can provide valuable information, but professional judgment is still needed to understand what those patterns mean in a specific learning context.
Harnessing the power of big data is such a double edged sword in education. The potential benefits are massive and undeniable when you consider how it might allow districts and researchers to pinpoint methods and materials that truly do lead to better learning outcomes. However, the privacy concerns raised by this level of data tracking are serious and should not be handwaved away in the name of better outcomes.
From a mobile technology perspective I think the “big” part of data could still apply in the context of a classroom where there might only be 20-30 students but who each could have hundreds or even thousands of individual data points associated with their progress and understanding. A handheld app that distills this dizzying amount of data down to individual, actionable and context aware prompts and suggestions for a classroom teacher would be an immensely useful tool for realtime instruction – and it wouldn’t anchor the educator to a laptop halfway across the room like so many platforms currently do.
Big Data is an area I want to understand much better. As a teacher, I develop a deep understanding of the learners in my classroom, while a school may begin to identify patterns across hundreds of students. Big Data makes me wonder what becomes visible when we scale that perspective to thousands or even millions of learners. Could we use data across schools, regions or even nationally to better understand patterns in curriculum, interventions, achievement, resource allocation or educational inequities that no individual educator could see?
I see enormous potential in that bird’s-eye view, but I also think keeping humans in the loop is essential. I am interested in how Big Data could expand what we are able to notice and question across an education system while keeping human judgement central to interpretation and educational decision-making.