Recently, AlphaGo, an artificially intelligent (AI) computer system built by Google, was able to beat world champion Lee Sedol at a complex strategy game called Go. AlphaGo’s victory startled not only artificial intelligence experts, who believed such an event was like 10 to 15 years away, but also educators, who perturbed that today’s high-value human skills will expeditiously be sidelined by advancing automation, possibly even by 2020.
Recent advances in technology have made it possible for education providers to take advantage of their increasingly large data sets. They’re now able to extract insights which can be used to improve teaching and learning outcomes and develop sophisticated predictive models for the future.
The term ‘learning analytics’ refers to the collection, quantification, analysis and reporting of data about learners’ growth and the context in which learning takes place. Learning analysis solutions can ordinarily accept data from a crowd of sources and systems, together with an institution’s core Student Management System.
MEASURE, MONITOR, AND RESPOND
Data Analytics allows an educator to quantify, monitor, and respond, in real time to a student’s learning of the material. Analytics, showing how students learn can help teachers adapt their teaching process and address student needs prior the final grade is delivered. This is a principle development for teachers because it will brace the ability to address any unplanned biases we might have towards the engagement or accomplishment of our students.
PERSONALIZE THE LEARNING EXPERIENCE.
Make courses fascinating for
students with multiple levels of knowledge. Introductory courses can often have
students with different levels of fundamental comprehension. Using data science
to analyze where each student is struggling or shining can allow you to offer
different starting content for each student within the same course. This will refine
student interest in the subject, and specify to whom and when specific learning
content should be delivered.
DESIGN A NEW COURSE
A key challenge for colleges and universities, is to quickly realize what industry needs and to deliver a module to meet those demands. Data science and machine learning can be used to acknowledge market and employment shifts and to categorize introductory courses and elementary learning principles around transpiring ideas in the business world.
This use of large datasets to guide business decisions is important for the world of education and is applicable to every industry wanting to take advantage of the technological trends driving economic and social change. Now, with real-time data, and lots of it, we can speed up the information gathering process, easily adapt our approach and respond, to the individual needs of our students.