The classrooms today are not only expanding to incorporate more technologies and digital tools but are also engaging in machine learning. Technology within classrooms has become all the more vivid in the past few years; laptops are replacing textbooks, and on smartphones, we can study just about everything.
Technology has become the most important aspect of distance education programs. Moreover, it enables teachers and students to digitally interconnect and exchange material and student work, all the time retaining a ‘human link’, which is important for the growth of young minds. Enhanced connections and customized experience, especially during this pandemic, is allowing educators to recognize opportunities to enhance the potential of a student. Hence, the classrooms in the present era are also engaging in machine learning.
Machine learning is artificial intelligence (AI) element, which allows machines or computers to learn from previous data and make smart decisions. The architecture for machine learning involves gathering and storing a rich collection of information and transforming it into a standardized knowledge base for varied uses. Educators can save time in their non-classroom by concentrating on machine learning.
Machine Learning in education is one of the key industries to drive investment, with countries like the U.S. and China expected to become the top players by 2030. Companies, like Google and IBM, are involved in creating more progressive and innovative school education programs.
The incorporation of machine learning in education aims to make the online learning sector top-notch. ML technologies analyze the content of online courses and help to ensure if the quality of the knowledge presented meets the applicable criteria. Users obtain data according to their particular preferences and expertise, and the overall learning experience increases dramatically.
This is the best application of machine learning; highly adaptable and takes care of individual needs. Students are able to guide their own learning through this education system. They can have their own speed and decide what to study, how to learn, etc. They can select topics of interest, preferred instructor, and program.
As the learning skills of a large number of students are expressed in online courses, grading becomes a challenge. ML technology makes the grading process spontaneous. There are some places where teachers cannot be replaced by computers but still can contribute to enhancing current approaches of grading and evaluation.
Researchers have recently investigated the potential of machine-learning techniques for assessing student engagement in the context of classroom research. They created a deep-neural-network-based architecture that can facilitate student engagement by analyzing video footage collected from classrooms – physical and virtual. Such advances have opened up immense possibilities for the use of ML in the education sector.