Small Data is as Important as Big Data in K-12 Sector
When we entered the new millennium over a decade ago, our obsession with big data began. Individuals and companies, alike, came to realise the importance of collecting, maintaining and analysing data sets. From waking up in the morning and analysing sleeping patterns to weather forecasts, big data analytics have pervaded all aspects of our mundane and not-so-mundane life. The education sector, too, has adopted it enthusiastically. Even before a teacher enters the classroom, their performance in their classroom can now be predicted basis their qualification, past tenure and the huge sets of data already in the repository of people in a similar post.
However, in the age of personalisation, in respect to both teaching and learning, insights on just trends and patterns might not be helpful enough to yield good learning outcomes. Educators are now increasingly taking the help of small data and delving deeper into students’ behaviour — their social interactions and emotional needs – to find out what goes on in a classroom. Research finds that very often a student’s emotional well being is proportional to their academic performance, and hence, the use of small data alongside big data becomes imperatives. Only when links between big data and small data have been established that we would be able to crack student success.
Let’s begin by discussing big data.
Big Data in the Education Sector
Large sets of data, to be analysed using computer algorithms, is called big data. The analysis yields patterns and connections in the functioning of human behaviour. With the help of software, we can find out the progress of students’ learning, and thereby try to bridge the learning gaps, and thus enabling the efficacy of learning. Though the predictions may or may not come true, it nonetheless helps schools to prepare the course of action.
It is difficult for a teacher to give individual academic assistance – personalised lesson plans, personalised assessments – to all students. The analysis of the big data can facilitate adaptive learning, thus improving the learning outcomes. The analysis also gives teachers particular data points while pointing out learning gaps in students to their parents. Besides academics, big data analytics also helps schools to manage their logistics and resources. Three Vs – volume, velocity and variety — help in understanding the vastness of big data.
However, now boiling down to a much smaller scale, let’s move to small data.
Small Data in the Education Sector
While big data includes an array of data regarding students’ demographic background, their performance, and their pattern of learning progress, small data deals with seemingly irrelevant subjects like their emotional and social aspects, their interests, their relationship with peers and teachers, etc. Unlike big data, there is no one or right way to collect small data, and hence, the challenges in collecting small data are many. Teachers should try to include more group activities in the classroom to help increase interaction in the classroom. Moreover, increased focus on formative assessments can help teachers understand the gaps in student’s learning. This mode of continuous assessment and continuous feedback could also lay a strong foundation of teacher’s relationship with students.
Teachers should be given more independence over the manner in which they want to plan their lessons and assessments. This would enhance social capital and build trust within a classroom ecosystem. Likewise, students should also be nudged to reflect on their own learning. A student’s own voice can be help teachers uncover those small gaps in learning.
Though the practice of collecting and analysing small data has not seen the light of success, the ensuing revolution in education sector has propelled policymakers to pay the much-needed heed to this aspect of data mining. It is essential to understand that only small clues can uncover big trends, which otherwise don’t call for much immediate action. For instance, if administrators get on to analyse details like how much time students are outside the classroom, without just getting into the parameter of absent and present, we could understand why sometimes the increase in attendance fails to bring about a positive change in the performance of the students. This kind of miniscule analysis though difficult, is important to bring about positive learning outcomes.
