10 big data trends affecting education
The days of overhead projectors and chalkboards are being replaced now by smartphones and iPads. Apps, mobile technology and the Cloud are shaping modern education. Big data is increasingly becoming associated with education. There are 10 big data trends affecting education and in particular, educational technology.
Big data is affecting everything from learning spaces to teacher accountability as the world becomes more data-driven. According to educational experts, big data will transform education in the future. In order to better engage students and improve teaching strategies, educational institutions are already collecting data on students, including test scores and aptitudes.
The process of collecting and analyzing the students’ work in a digital manner in the data-driven classroom has become an integral component in tracking and reporting student performance. In addition, since social interactions have moved increasingly from in-person to online, big data can trace in detail student-to-student interaction. By integrating all these data sources, it is possible to measure more complex collaborative and problem-solving skills.
Here are 10 big data trends affecting education:
1. Tracking Student Performance – One of the top trends in using big data trends in education is identifying students at risk and tracking their achievement. This way, students at risk can be offered special support before their educational gap becomes more significant.
2. Big Data and Analytics – Among the benefits of analytics and big data in education are included increasing operational efficiency for a university or a district. In particular higher education institutions can leverage data analytics to forecast budgets, manage operational costs and revenues, grow investment portfolios and set market competitive tuition rates.
3. Optimizing Campus Operations – Big data can help improving student success and increasing campus efficiency. Administrative analytics integrate budgeting, personnel and procurement data and streamline essential business functions.
4. Advancing Recruitment and Marketing Efforts – Analytics can help improving alumni relations and recruitment by analyzing an educational institution’s market position.
5. Garnering Statewide Insights – Statewide longitudinal data systems can help enhance the ability of state level decision makes to accurately collect analyze and manage data from individual student records by connecting data from each stage of education.
6. Building Tomorrow’s Workforce – Data from individual institutions and statewide longitudinal data systems can be used to better prepare students for the workforce.
7. Alternative Credentialing – Big data in education has led to significant discussions about alternative institutions and learning pathways that offer education programs embodying alternative credentialing and providing a variety of learning options.
8. Experimentation in Learning Spaces and New Teaching Models – The traditional education model evolves through experimentation in learning spaces and new teaching models in response to digital culture and technology. From a passive and instructor focused model, the education system becomes active and student centered.
9. Student-driven Personalized Learning That Is Student-Driven – Personalized learning offers different learning methods that are learner-driven. Students are not only consumers but also active creators of content.
10. Assessing Complex Skills – Unlike conventional assessments in higher education, big data analytics provide tools for assessments of students’ performance on more authentic tasks, such as free-form text answers and engineering design problems. By measuring these tasks the precision and relevance of the results can allow the tailoring of instruction to specific needs of the students and provide individualized feedback.