Gannon University, located in the USA, uses data analytics to identify students at risk of dropping out. They implement this methodology even before students get admitted to the university, helping them improve student retention. Nowadays, higher education institutions are investing more in data analytics to track students at risk of dropping out, placing greater emphasis on first-generation and underprivileged students. The global market for big data analytics in education was valued at USD 13.58 billion in 2020 and is projected to reach USD 57.14 billion by 2030, with an impressive compound annual growth rate of 15.3%.
Data analytics has become a major tool across several industries, including higher education. It is crucial that educational institutions should leverage the power of data to gain valuable insights into students' performance and take them forward.
Personalized Learning
In this modern era, personalized learning has become the key, and many educational institutions have been following this to unleash the maximum potential of students. To comprehend the student's performance or to take them to the next level in education, institutions make use of data to get crucial insights into the students' behavioral patterns so that they can customize several learning paths to meet every student's requirements. Understanding them comprehensively and taking the customized steps will nurture a more effective and interactive experience, which will help the student community succeed in the future. Personalized learning plays a vital role in enabling students to make their own decisions about their learning for enhanced motivation and results.
For instance, Arizona State University has adopted adaptive learning platforms such as Knewton and Smart Sparrow. These platforms utilize algorithms to personalize students' learning practices, considering their strengths, weaknesses and learning manners.
Rick C. Levin, CEO, Coursera said that "Data analytics in online learning will create new pathways for people of all backgrounds to find a fulfilling career"
Early Intervention and Support
Assessing the student's performance in terms of data analytics can help them know whether they are pursuing well in their academics or going through the risk of academic failure. More importantly, their unsatisfactory performance can be identified well in advance, and with the help of several signs such as attendance, grades, and participation, educational institutions can take the necessary steps to improve students' performance from the struggling stage. Institutions can offer assistance to students in the form of advanced tutoring from the base level and counseling if required so that the students are likely to succeed. Consequently, the institutions can enhance the retention rates of students, contributing to their maximum potential.
Many schools in the USA implemented Multi-Tiered Systems of Support (MTSS) to offer early intervention and support to students. For example, St. Paul Public Schools in Minnesota leverages MTSS to find students requiring additional support and delivers targeted interventions.
Continuous Improvement
Data analytics remains the key from both angles. One from the educational provider's point of view, they can use the comprehensive data to assess the student's performance and what steps can be taken to mold the students to the next level. Similarly, the students will benefit in their academics as they are being observed by the educational providers to propel. Besides, institutes can harness this tool for continuous improvement and quality assurance. The process starts by taking and examining data on students' results, their level of satisfaction and learning experience so that they can comprehend the areas where students need to be improved and take the appropriate measures accordingly.
The University of Central Florida uses a learning platform called Student Data Mart, which incorporates information from several sources comprising of student information system, course evaluations and more to offer educators crucial insights into student performance and used for continuous improvement.
Enhanced Decision Making
Arriving at the right decision is the key to success. Data analytics makes the process way easier by collecting and examining several sorts of data from all sources in the form of trends related to enrollment, demographics of students, and course evaluation so that the concerned person can secure key information about the efficiency of academic programs and all support services. By adopting data analytics as the key strategy, the approach will allow educational institutions to make accurate decisions concerning allocating resources, how the curriculum can be developed, and tactical planning, eventually improving the overall learner journey and positive outcomes.
Georgia State University has secured recognition for its advanced utilization of data analytics to enhance student outcomes, mainly in retention and graduation rates. They adopted GPS Advising, a predictive analytics system to find students facing challenges and, with this framework, examine the necessary information of students to provide adequate support.
All in all, data analytics has become part and parcel of this complex educational landscape to improve student performance. It also benefits the educational providers in transforming teaching and administrative practices. To succeed in this modern education, it is significant that the educational providers have to enable personalized learning methodology, predictive analytics, taking early intervention to improve student results, leading to high retention rates. Also, the decision-making process, with the help of data analytics, will lead to quality education and continuous improvement. It will make the institutions quick to react to the requirements of students. Hence, data analytics cannot be avoidable and should be leveraged to the maximum to get positive outcomes.
