Big Data in Education - Learners Behaviour and Student Performance

With over 2 decade worth of experience delivering data projects, as well as advising organisations on their data strategy and usage of data, there is one common factor across all use cases across all industries and that is Big Data. Without the use of Big Data, you can only go so far in becoming a truly data driven organisation.

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Datasets that satisfy at least three (volume, velocity, and variety) of the five V’s (veracity and value) can be characterised as Big Data. These datasets have diverse information that arrives in ever increasing volumes and ever higher velocity. This diverse information can arrive in the form of structured or unstructured data. With technological advancement, businesses are inundated with big data on a day-to-day basis. ?

The value of big data lies in the use cases that it drives or the power it gives the functional area within an organisation. Organisations use big data to

1)???? increase productivity.

2)???? drive efficiency.

3)???? smart and fact-based decision making.

4)???? drive new and growth opportunities.

?A good article to understand the depths of Big Data can be found here.

?Use of Big Data

?Big data is a big deal for industries. The onslaught of IoT and other connected devices has created a massive uptick in the amount of information organisations collect, manage, and analyse. Along with big data comes the potential to unlock big insights – for every industry, large to small.

?One of the most common use cases of Big Data that has touched almost the entire population of the world who has access to search engines is to get personalised ads. Online channels have utilised your search behaviour by collecting, analysing, and personalising what you want to see in your Facebook and Google feed all with the intent of increasing revenue and growth. However, the use of Big Data in education could be used to improve students lives, their learning journey and academic performance.

?Use of Big Data in Education

?Pandemic forced schools and colleges to move from traditional classroom learning to online learning. World Economic Forum reported that the Covid-19 pandemic has changed education forever where as in UK proportion of parents reporting that their kids were provided with online learning between April and June 2020 rose from 44% to 51% for primary students, and 59% to 65% for secondary students.

?As a result of technological advancements, education institutions generate large amounts of exponentially increasing Big Data via use of online learning management systems or student records with multitude of data depicting student behaviours. Regardless of any conceptualisation, the increasing amount of data generated in the higher education sector provides opportunities for extracting valuable, actionable insights, like other sectors.

?Educators armed with data-driven insight can make a significant impact on school systems, students, and curriculums. By analysing big data, they can identify at-risk students, make sure students are making adequate progress, and can implement a better system for evaluation and support of teachers and principals.

?Big Data application using Learners and Performance use case:

?·??????? Personalised Learning Path – With the help of Big Data one can improve learning management of a student. Analysing what content engaged students longer and the time they took on task submission, research, tests, and exams will help to plan or customise the curricula efficiently and effectively. It can also create a personalised learning path for students utilising their strongest engagement areas.

·??????? Identify areas of performance improvement – Analysing the data near real time helps to react to areas of student performance improvement quickly and clubbing the academia data with the attendance data shows areas of support that may extend beyond learning.

·??????? Better understanding of strengths and weaknesses of individual students – Overlapping various external data sources to students learning data helps to hone down on students strengths and weaknesses. Analysis of the weaknesses will allow early detection of students at risk, there by giving teachers ample time to change course.

·??????? Improve college-dropouts – A great article by The Washington Post showed how Georgia State University examined more than 10 years of transcripts from 140,000 students. GSU identified 800 risk factors that make it more likely a student will flunk out. It found, for instance, that only 1 in 4 political science majors who earned a C in his first class graduated on time. This helped GSU to put in place measures that reduced the dropout rate by 32%.

·??????? Early detection of student wellbeing – Imagine a student who is a regular at gym classes, that data will be available from swiping into gym classes. Overlapping this with the academia data, and attendance data paints a student behaviour. Any divergence from the usual behaviour early on will assist the institution to intervene at the right time.

?With all the benefits that Big Data brings, Institutions still has a long way to go.

?How does Big Data work?

?Before making sure one has the right foundations to get real time learning predictions, personalised learning plan and performance of students, it is crucial to implement the foundations to make Big Data work.

?Foundations for use of Big Data

·??????? Set a big data strategy – this should help you understand how you collect, store, manage and share your data assets both internal and external. Ascertain both current and future roadmap and lay a high-level plan to incorporate Big Data in decision making processes.

·??????? Identify data sources – Create use cases to drive the strategy and identify the various sources that should contribute to those use cases. Streaming data, social media, publicly available data, and any other sources that can have an impact on those use cases.

·??????? Collect, store, manage and access Big Data – Create a data architecture that is scalable, accessible, and consumable globally or cross functionally dependent on the institution to embed and analyse the Big Data use cases near real-time.

·??????? Analyse Big Data – Analyse the data to cater for relevant data pertaining to use case in action. Prepare to differentiate between noisy and irrelevant data points and create paths to visualise the analysis.

·??????? Fact based or Smart Decision Making - Change or Embed business processes to incorporate the above visualised or analysed data to feed back into business as usual to help with smarter decision making.

?To conclude, with ever increasing use of technology the amount of data available presents immense opportunities, from personalised learning paths to early intervention of at-risk students both from academic and emotional perspective, however, plan to lay the foundation. Institutions must handle larger volumes of data and determine which data represents signals compared to noise. Deciding what makes the data relevant becomes a key factor. Furthermore, the nature and format of the data can require special handling before it is acted upon. ?

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