Improving Student Outcomes with Big Data and Real-time Analytics

Big Data is Here. What can it do for Education?

The way that students learn and teachers teach will be revolutionized when big data is deployed massively in the educational space. To catalyze this trend, the US Department of Education (DOE), along with other organizations, has put up $200 million in fostering the use of big data analytics in education. Let's take a look at various aspects of education that big data is poised to improve.

Analytics on student success parameters

What factors contribute to the learner's success? Insights can be garnered through the use of big data analytics. Factors like attendance, frequency of contact with teachers, time taken to complete a given task, can all make a difference. If a student does better when his or her attendance rate is good, the correlation should be emphasized. If a particular student's performance improves if there is increased interaction with the teachers then the student can be assigned more tasks which require help from the teachers in an interactive way. A student's performance also differs based on the peer group they associate with. All of these data offer opportunities for interventions that can benefit student outcomes.

Tweaking course content

The digital textbooks and course outlines which are often used by students can be improved when students use of these tools are monitored in real time. Different students will have various issues with particular content, which can be detected by an algorithm. Which course content is more or less difficult to understand can be assessed and useful feedback provided in terms of course design enhancements. Additionally, information like how often a text is read, the number of questions asked on a certain topic, the time required to read the text, how many links are clicked for more information is useful to authors. If this information is provided, authors can work to tailor the textbooks and content to better suit the learning needs of students.

Individualized learning

How each student learns at an individualized level can be better understood with the help of big data analytics. The final grade of a course can be based on what the student learns in the course rather than on high-stakes assessments or exams. This could take the education system towards being more process-oriented rather than the results-oriented approach pervasive right now.

When a student joins a new school the teachers often find themselves at a disadvantage as they are not aware of the weak points of the students. Big data can make the interchange of data among the student's previous school and the current school possible so that the student can properly be guided by the teacher.

Sometimes there are exceptionally talented students who are actually confined to the common syllabus along with their peers. Big data can expose this and provide an opportunity to give more advanced course content to those gifted students.

Big data in reducing drop out rates

Would you be surprised to learn that big data analytics can be used to reduce the drop-out rates in the educational space? Drop outs are costly in so many ways. Yes, there are exceptional stories like those of Bill Gates, Larry Ellison and the like, who made it big despite their educational struggles. But they represent a very small portion of the drop outs, with the vast majority of them often finding it very hard to make a good living. If in their college life their academic activities had been closely monitored, given instant feedback and tutored based on their individual skills then they might have been positioned to suuceed. This is the realm of big data analytics.

Use cases where big data is deployed

Khan Academy is a widely known education technology service provider that is has been a leader in the use of big data to help teachers help their students. Sal Khan explains that he wants “to really arm the teachers with as much data as possible really data that, in almost any other field, is expected, if you're in finance or marketing or manufacturing.”

Georgia State University has put big data to use. After realizing that too many student were collecting credit but not getting closer to graduation, they decided to take action. They bough in a vendor with expertise in big data and set up a system that track, “the thousands of decisions that students make every day and predict the likelihood of their academic success on that basis.” Using 10 years’ worth of data on every student, grade and course at Georgia State to develop and calibrate the model, they set up a model.

“Every night, the system checks more than 800 variables relating to the institution’s 30,000 undergraduates to flag up those who, according to the model, are heading for trouble. The data include which courses students have signed up for, and their attendance records and grades [and] … automatically sends the student and their adviser an email or text asking them to meet to discuss the issue. In its first year, the system prompted more than 50,000 such meetings.

The results were immediate. “We saw fewer students dropping out and improved graduation rates within the next year,” says Becker. The average time to graduation for Georgia State students has fallen by half a semester, saving those who graduated in 2016 $15 million (£12 million) in tuition fees compared with the class of 2012. And every 1 per cent increase in student retention generates an additional $3 million return on investment for the university.”

Another example where big data is used in education is the University of Tasmania. This university has over 26,000 students and the university has deployed a learning management systems (LMS) to know how exactly a student is using the facility to learn. When the student logs in, how much time is spent on a particular page, and overall progress of the student is ascertained through this system.

Conclusion

A few closing points.

There is already a growing trend where big data is being deployed in the educational space. There are concerns regarding privacy of learners and teachers, and this is a very important consideration as we continue to move in this direction, and privacy controls and rights must be incorporated into the implementation of these tools.

We have focused on how big data can benefit student learning in this article, but imagine if the same technology is applied for teachers to enhance their performance? With the rapid development of analytics technologies, we are likely to see benefits on both sides of the student-teacher relationship in the years to come.

Lastly, for those interested in learning more about big data, Intellipaat's big data training is a great option, the leading e-learning institute on analytics training.