Learning Analytics, Educational Data Mining, Adaptive Learning

Many in the higher education community are intrigued by the value of leveraging institutional analytics to improve student success, and have been for a while. “Institutional Analytics in Higher Education,” a 2016 EDUCAUSE ECAR report, asserts that the aspiration to use analytics to make a difference for students goes back at least a decade.

Could the right combination of software and process reform dramatically improve persistence and completion rates for students — especially students from minority groups or low-income backgrounds? Many institutions are still not quite at the point of investing the resources needed to realize the potential of analytics for student success. That said, the current academic year has seen pioneering projects and early successes draw the media spotlight.

Machine learning is the science of getting computers to act without being explicitly programmed.

Educators today are open to try new technology in education. As witnessed, integration of technology makes learning and teaching efficient on both ends. Thus, there is rising likability of machine learning in the education. A part of Artificial Intelligence, machine learning is on rising scale of adoption. Other than education, we are so much around this technology that we may not even know. The recommendations from e-commerce that are so much similar to our preferences is all Artificial Intelligence that is working. Machine learning is so pervasive today that you probably use it dozens of times a day without knowing it. Many researchers also think it is the best way to make progress towards human-level AI. It is all about innovation and improving the life of the millennial and beyond. If you have heard about automated card driving, you already know how machine learning can improve the life of the people.

In education, it does have its own impacts. In this post find out how machine learning is improving the education. Pointers mentioned below indicate the use of machine learning in education along with platforms that are using this technology.

The assistant vice president for analytics at Excelsior College explains the value of training and the importance of diverse skills.


EDTECH: HOW SHOULD COLLEGES EVALUATE WHETHER THEY NEED A CDO OR EQUIVALENT?

 DANIELS: I don’t think every college has the need or capacity. I’m thinking of the small, liberal arts college that has a fairly small population. They already have a lot of face-to-face time with students. They should look at basic statistics to inform decisions on some level, such as keeping track of their student success rate and whether certain programs are doing better than others. But they don’t necessarily need an elaborate process like I’ve described. In terms of whether colleges should hire an analytics expert, they need to look at the top strategic challenges they are facing. Is it something that analytics could inform and drive decisions on? You have to sit on a large amount of data to have that level of program. Colleges probably have someone with an institutional research capacity doing analytics on some level, but it’s hard for me to say where the tipping point would be.

A growing number of universities are using big data to improve student success but there are ethical issues that arises with the exploitation of
student data.

Glancing around school classrooms in 2016, it’s easy to miss just how far technology has transformed learning over the last decade. The desks, whiteboards and rows of chairs are the same, but so much else has changed that can’t be seen.

A third of Britain’s schools are asking students to bring their own tablets and laptops into the classroom now, coding has been on the national curriculum for three years, and more and more education is happening outside school through apps and digital services.

But these changes are just the start. Artificial intelligence (AI) is the next giant leap in learning and, according to those working in the field of education and technology, we haven’t seen anything yet.