on 01 May, 2019 by Gaurav Belani, SEO & Content Marketing Analyst
While the world goes smart at an astonishing pace, turning phones into personal health monitors and TVs into voice-controlled streaming devices; educational institutions cannot afford to remain archaic stone buildings with rigid curriculums and one-dimensional grading systems. Artificial intelligence and big data are helping schools, colleges and universities become more sophisticated and better capable of helping more students attain a better quality of education. One that will better enable them to attain their highest potential and become valuable members of society.
From delivering highly engaging lectures that are better understood by students, to performing more intuitive aptitude assessments to propel students into the right courses for higher education, AI and big data are helping change the very course of formal education and bringing it closer to the goal it was originally intended for – to inform young minds and enable them to make the best use of that information.
So let’s take a look at all the ways AI and big data solve the biggest problems students and institutions face.
1. Improved Effectiveness of Learning through Personalized Program
One of the major players in a conventional classroom setting is student diversity. Some students are naturally good at grasping mathematical concepts while others struggle with it. Just one monotonous teaching curriculum isn’t enough. Effective data analysis of individual test scores over the sessions can help teachers understand the underlying strengths and inherent challenges of each student.
Educational institutions are constantly generating critical data such as student surveys, credits analysis, data from participation in various school activities and a host of other resources. Tests that are taken online are a goldmine of data, presenting valuable insights into how long students take to answer a question, which ones they like to attempt first and many others.
Careful analysis of all this data can help educators develop personalized teaching plans that play up the strengths and mitigate the weaknesses of each student, sizably improving the effectiveness of teaching. Further, AI can help develop such personalized teaching programs adjusted to individual student needs. Already, companies like ‘Carnegie Learning’ and ‘Content Technologies’ are working on creating intelligent instruction design and creating a firm ground for such technologies.
2. Reduce Dropouts
More than 48% of first-time college students in America dropped out of college in 2016. This means that a staggering 2 million students starting college each year will drop out before earning a diploma. School and college dropouts are a huge problem in America and the rest of the world. The problem is multi-faceted and needs immediate solutions. Fortunately, AI and machine learning solutions have a substantial ability to tackle many of the reasons that lead to dropouts.
One of the big reasons so many students drop out of courses they worked so hard to get into is that they were just not prepared for the academic pressures they face in college. Another reason is courses unfit for their aptitude, something we will discuss in the next point.
Big data analysis done to determine the level of preparedness of a student before enrolling in a college and investing their time, money and effort into it can profoundly improve student outcomes. It can even help students prepare for the upcoming curriculum.
3. Performing Better Skills Assessment
Often, students find that a course they thought was their ultimate goal isn’t really a good fit for them. Preliminary ambitions are driven by an outside view of their chosen field often become a burden when young students are faced with the reality of the subject. Often, good grades in math and physics make students and teachers think of engineering as a good option. However, when faced with the nuances of an engineering degree, students don’t quite find it to be what they expected.
Once again, data analysis and AI can help these students perform a better assessment of their interests and aptitude. Data analysis of their grades, performance and participation throughout their school life and not just the final entrance exams can better indicate their inclination and determine courses more suitable for them. This in turn immensely helps students pick the right course.
4. Better Grading
Relying on monotone standardized tests is no longer the right way to assess a student’s capabilities. That is something educators, parents and authorities are beginning to truly understand now. As a result, developing a better, more efficient system is imperative, one that can objectively measure a student’s performance. A student’s participation in class, analytical thinking, curious questioning, consistency in class attendance and many other aspects can be made legitimate performance criteria to measure their performance and grade them accordingly.
5. Improve Student Performance
In the same vein as above, all the data collected to these ends can also help find out which areas a student is struggling with, in subjects that they otherwise show an aptitude for. For instance, if a student is showing great critical thinking and analytical skills in class, but still scoring poorly in tests, maybe they need help with writing their papers or expressing their thoughts on writing. Working on those particular aspects then help improve the overall performance of the student and prevent them from falling into the discouragement trap of low grades on paper.
Education is one of the most sensitive matters of society that is struggling with enough problems of its own. Yet, imparting quality education and giving every student a level playing field is of the utmost importance if we are to obliterate the biggest of our challenges. The above points are a good indicator of how we can begin leveraging big data and AI to improve the lives of studentsand deliver better education to our future generations.