Data has become an increasingly important resource. Business organisations are using data-driven insights to not just understand their customers and improve services but also to increase efficiency of their processes and enhance overall performance.
However, there is more to data than its application in businesses. It can be stored, categorised, analysed and used to predict future trends across various sectors, including education. Not only can data help improve the education sector, it can also make learning a social-emotional concept.
While the pandemic forced the education system move online, e-learning is currently limited to a few digital platforms. While teachers and learners have adjusted to this model, the former lack a few key insights such as attendance, student’s individual performance, strengths and weaknesses and so on. Including data science in education can help both the teachers and the students.
Learning analytics will allow educators to gather the learners’ performance data to leverage lesson outcomes. Apart from the attention aspect, it will also help in setting test and exam benchmarks. With the use of effective tools such as multi-source knowledge mapping and predictive analysis, it is possible to design a system that caters to individual learning needs and a more comprehensive evaluation.
Traditionally, instructors have relied on assessments and periodic tests to judge the students’ progress. This often resulted in late identification of struggling individuals. However, with the use of data science, the data of every student is stored, filtered, and correlated to specific metrics such as learning success. Teachers not only get to know attendance details but also interest areas, learning pace, difficult topics and, ultimately, attentiveness of each student.
As patterns emerge, instructors can make changes to help struggling learners. Early warning signs can help teachers reach out to students and offer interventions. Further, data analytics makes it possible to track every student’s activity to understand where they are most and least engaged. Based on this, teachers can create personalised learning plans to move away from one-size-fits-all paradigm. A feedback system is thus created to help instructors to discover solutions to the most common problems in online learning.
With the strong and growing demand for social-emotional learning, the education system must prioritise the development and assessment of social-emotional competencies. A data-informed approach will help educators invest in strategies that help reach this end.
The use of data science in education can help make learning better and more effective and improve the quality and impact of the teaching methodology.
The writer is the CEO and Founder, IntelliPaat.
