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Employment of big data in 2020, caused by the COVID-19 pandemic. Businesses large and small have long relied on data-driven decision-making in education and many other industries. The application of data science in education has helped companies understand trends in students’ behavior and their preferences. Let’s take a deeper dive into how big data can take the EdTech industry to the next level.
The amount of data being generated globally is astronomical and is exponentially increasing in size. In 2023, according to Statista, the amount of global data was 120 zettabytes, butexperts predict that this parameter will reach up to 175 zettabytes by 2025. The education sector is critical for economies globally, and they are ideally placed to take advantage of this influx of information.
When discussing big data in education, there are three primary areas we are considering. These areas are educational data mining, web dashboards, and big data analytics. The knowledge and insights gained from these areas provide several benefits to academic institutions, including:
Data collected can be analyzed in a variety of different ways. Specifically, students’ and faculty members’ data collection can lead to new insights that can improve the way schools work. Simply put, big data is changing the way schools educate their students. This has led to different learning models and concepts and it is possible using big data to obtain a much greater understanding of how to ensure students are successful.
Big data in education can be used to analyze student performance based on test results and assignments. These results can lead to the development of personalized education plans and goals.
By obtaining data from a variety of different channels, more information can be examined. This additional information can further enhance the teaching methods based on specific behaviors and patterns. In addition, by grouping individuals based on learning patterns and difficulties, additional required resources and changes can be allocated.
Added to this is the ability of big data grants to create customized groups of learners based on different needs and requirements. These clusters of students can be determined based on the complexity of the course itself or can be larger in focus and determined based on a variety of different courses bundled together.
Big data is changing online learning and helping to build unique, customized curriculums for students. Using big data in education, organizations can institutionalize the process of acquiring, sharing, and exchanging knowledge. This process leads to higher achievement as students have access to more information in a format that is designed for their requirements.
Data in the classroom can be used by teachers to improve reading materials and help students deal with specific problems and issues they might be experiencing. By building a customized knowledge experience with digital materials and course plans, educators and administrators can better facilitate communication.
The use of big data in higher education helps educational institutions and educators as well. Data analytics can be used to help identify student problem areas and through the use of customized training and better facilitate learning. Big data systems help to monitor student achievements and preferences, helping to improve student outcomes and overall academic performance.
Big data does more than just solve short-term problems—it can also help determine a student’s longer-term future. Not all students know or envision their eventual future role in society, but with big data recommendations, students can better understand potential future roles and sectors that match their personal abilities and preferences.
Big data also helps educators evaluate their own course content. It provides unbiased feedback on the structure and design of their course and also helps them understand how efficient their teaching methods are. Through this improved information, educators are better able to identify weaknesses in their students at earlier stages and better plan coursework to address these areas.
Big data can analyze the complexity and difficulty of a course and its materials against specific students. By correlating both the course content and the students’ capabilities, strengths, and weaknesses, big data is better able to determine the failure risk of the student. With this knowledge, educators can build personalized programs that ensure students obtain the knowledge they need in a fashion they can better digest.
In this section, we propose to find out what three main challenges organizations may face when considering introducing big data in education.
While there is a massive demand for experienced data experts, there simply is not enough supply. Unfortunately, this deficit has not yet been addressed by most top universities, as data science programs are still lacking. This, unfortunately, means that many schools will not have access to technology or its results and benefits, impacting millions of students globally.
The volume of structured and unstructured data often exceeds the processing power of currently accessible big data tools. This can cause significant issues and force systems to crash or slow down, leading to a negative experience and a reduced quality of the big data analysis.
Security protocols were not built for a big data world and need to be reworked to account for the volume of data that big data uses in its analysis. While academic data is not considered as sensitive as health or financial data, student data could be used to gain access to other systems, so security needs to be addressed in customer satisfaction.
Big data and education may be more connected in more ways than meet the eye, and these connections will only become stronger every year. If today, tools based on big data perform mainly analytical tasks, soon, they will most likely make a real revolution in the field of education, allowing each student to receive an individual pace of learning and use individual methods that are most comfortable for their perception. Below, we propose to consider particular areas of implementation of big data in education that are already intensively developing.
Personalized learning is based on the analysis of data obtained during the preliminary performance of a particular student. This approach allows educational institutions to formulate individual learning plans for each student, taking into account their individual cognitive characteristics. Such adaptation ultimately allows these institutions to maximize the success rate and also increase the average score.
Since the effectiveness of the learning process must be achieved immediately for both parties taking part in it—that is, both the student and the teacher—the latter must have advanced tools at hand that would help maximize their teaching potential. In particular, educators can use big data analytics for education to analyze possible learning patterns based on continuous monitoring of student progress and levels of engagement. Thus, with appropriate analytics, educational institutions can significantly improve their competitive advantage, because over time, thanks to big data, their approaches and methods will take the overall knowledge of the students to the next level.
Big data education is not only about increasing the level of knowledge of students and maximizing the efficiency of teachers. Smart solutions based on big data can also be used to impartially assess knowledge levels. This approach will eliminate the influence of the human factor on the processes associated with monitoring the level of proficiency in a particular discipline and also free up human resources for more non-trivial tasks.
Generally speaking, big data analytics in education can also be used to achieve certain business goals. With the help of these technologies, educational institutions can predict trends and improve the quality of decisions made. This may concern the number of applicants in the upcoming academic year, the demand for specific courses and faculties, and so on.
Finally, big data in education can be used to optimize learning environments. In particular, given the proliferation of consumer data protection standards in the digital space such as GDPR, educational institutions can use big data together with machine learning and/or artificial intelligence to eliminate the misuse of students’ personal information and generally provide better security around the perimeter of their network infrastructures.
If we talk about further prospects for the development of big data in education, it would be reasonable to consider the possibilities of combining this technological concept with other advanced ones. Below, we invite you to learn about four such technologies that, when used together with big data, can make a significant impact on the international field of education.
Artificial intelligence and machine learning, when used in conjunction with big data, can take on the role of both improving the quality of this data and extracting valuable insights that may not be obvious to even the best specialists. Thanks to these capabilities, this bundle of technologies can be used in adaptive learning systems, chatbots for student support, smart solutions for assessing student knowledge, as well as in all kinds of predictive solutions.
Elements of gamification, introduced into digital platforms and individual learning tools, can increase the level of student engagement and also make a positive impact on their academic performance. As for big data applications, it can be used to analyze the behavioral patterns of individual students when interacting with these integrated platforms. Thus, these digital solutions will be able to adapt the learning plan and approach according to individual student characteristics.
Virtual and augmented reality technologies can be used in digital learning platforms to provide the most immersive learning experience. When used in conjunction with big data, such solutions will be able to visualize abstract concepts and provide students with the most accurate and relevant information.
Finally, another promising technology that can be effectively used together with big data in education is the Internet of Things. Solutions that combine these two technologies are able to exchange data without human intervention, thereby eliminating the need for human resources and opening up new opportunities for teaching students the best global practices.
Now, it’s time to check a few special cases of using big data in digital learning solutions.
Knowre is a big data based application aimed at providing a personalized approach to improving student achievement. Educational institutions around the world use this solution to automatically identify and fix student knowledge gaps. First, this software collects analytics on a specific student, identifying their strengths and weaknesses and areas in which this student needs additional training, and then processes the resulting analytics to generate recommendations for teachers. Thus, with its help, teachers receive a personalized guide to improving academic performance for each student.
The Naviance software solution is a great companion for applicants and their parents. In particular, they can use this big data software to prepare for college or before applying for a desired job position. With the help of Naviance, students receive an objective assessment of their level of academic performance and, based on this, the generated lists of possible universities/vacancies where this level will be sufficient for successful admission or employment.
This big data software is intended for school administrators and school districts. It provides a centralized repository of data on students’ educational plans, their level of academic performance and social behavior, and activities that bring together students and their parents, teachers, and other personnel from educational institutions. Panorama Education users can request data on individual students, which can be extremely useful for end-to-end monitoring of those who need a special pedagogical approach.
Udemy is one of the most famous online learning platforms for students of different skill levels. Here, you can find both short courses to gain basic knowledge in certain disciplines and long ones that repeat programs from the best offline educational institutions in the world. As for big data, this technology is applied here to determine student engagement rates in a course. These metrics can be used by course creators (that is, teachers) for further improvement of their educational approaches and methods.
Apex Learning radically transforms the way students are assessed in middle and high schools. For example, with the help of this big data solution, teachers and students can constantly monitor their progress instead of relying on test results. This allows both sides of the educational process to take timely measures to eliminate gaps in knowledge and, thereby, prevent unsatisfactory performance indicators.
This solution is used by many universities to collect data about students and receive their feedback about the educational process as a whole. In addition, this software provides analytics and reporting based on big data, which allows these institutions to continuously improve the level of education and overall satisfaction of their students.
The value of big data in education is growing with the development of the technology itself. However, tangible results from employing data science in education are highly dependent on the maturity level and technology adoption of a school or university. When implemented right, cutting-edge technologies enhance data-driven decision making in education that fuels further growth of the educational establishment.
If you want to get more insights on the topic, check out our article about the essential trends in EdTech, our latest case study on the development of an e-learning platform called MindTap or get in touch with our team for a tailored consultation.
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