On Artificial Intelligence and Ethics
The Tango of AI and Big Data
Transforming the Art Museum in the 21st Century.
Embedding AI in everything. Why we can't do without it now
When it Comes to AI, the Fun Part is Over
Beaumont Vance, Director of the Analytics Center of Excellence, TD Ameritrade
Applications of Big Data and Predictive Modeling
Somesh Nigam, Ph.D., SVP and Chief Data Officer, Blue Cross and Blue Shield of Louisiana
Grow and Supercharge with Artificial Intelligence
Deep Varma, VP of Engineering, Trulia
Technology Megatrends that Will Shape the Future and Your Business
Jag Randhawa, Technology Executive & Author, CAMICO

Transforming Learning Process using machine learning

No one can doubt that Artificial Intelligence (AI) is now making machines smarter. Machine learning, a subset of AI, which is present in every aspect of human life including education. Artificial Intelligence in Education (AIED) caters to the needs of learners and makes learning fun and interactive. Adaptive learning has transformed from pedagogy through the computer to mediated personalized learning solutions.
The Necessity of Machine Learning
Machine learning provides a personalized learning environment. With a customized learning environment, students can learn at their own pace and make the fundamentals clear which makes the related topics easier to digest. However, if the basics are not clear, then the students can develop a learning gap over the years. Machine learning can identify, address, and eliminate such learning gaps at an early stage.
Personalized Learning
There are two types of learners – sequential learners and global learners. Sequential learners learn through a linear path while global learners learn with long jumps and gain knowledge in a seemingly random fashion. Adaptive learning benefits global learners, but it doesn’t mean that sequential learners cannot benefit from it. However, one cannot skip certain concepts. Students can learn multiple concepts together. For example, one can learn trigonometry and algebra together. Adaptive learning maximizes learning in a short period, and it is ideal for fast learners because they get bored when they are not challenged enough. Adaptive learning allows students to learn at their own pace as a personalized path is carved for all types of learners.
Optimal Learning Tool
Once the AI integrated system learns about the performance of students, it teaches itself by using clustering algorithms to categorize the students according to their learning capacity, style, needs, and preferences. Lighting, sound, and time affect students' learning the process as well. Some students may read better in the morning while others can grasp better in the afternoon. Based on their habits and preferences, AI can recommend best schedules and tools to learners. AI can make students aware of their learning habits, and encouraging a self-learning practice.