- IoT and AI-enabled devices are driving the creation of advanced learning programs
- AI-based CampusLogic, helps colleges assist students in calculating their institutional costs
- Global market for AI-enabled solutions in education is projected to reach USD $3.68 billion by 2023
Things such as extended learning beyond classrooms, real-time assessment and feedback, automated creation of personalized learning plans, and supporting teachers on time consuming tasks, are now possible courtesy of AI-based systems and applications.
AI technologies are being utilized more and more these days to analyze the growing number of data points for evaluating the performance and the changing needs of students. AI is playing an increasingly valuable role in accelerating effectiveness and efficiencies in many areas of the educational administrative processes.
Individualized learning is priority one for educators. AI-based solutions for education are rapidly accelerating the individualized learning mission. There are applications that use AI technology that enables teachers to develop academic syllabus online so that students can access it at any time. AI technology is also being used to identify gaps in knowledge and recommend subjects that the student should choose, all based upon the results of the aptitude test taken. AI solutions can now combine cognitive and learning science with practical instruction and research, so that students can better understand what they’re learning in a much more personal way.
Real-time assessment and feedback
IoT and AI-enabled devices are driving the creation of advanced learning programs that improve the learning processes. These solutions and services help teachers and parents understand their student’s performance, in addition to improving students’ experience and knowledge level. Intel’s solution is an excellent example of this. Intel is using multi-modal sensing to gather data on three primary inputs that can better predict engagement during a class session. These inputs – appearance, interaction, and time-to-action – enable educators to monitor each student’s progress, and in turn address their immediate learning needs.
There are now AI tools that are being used in the creation of virtual classrooms. While the pandemic has made this capability essential to educators everywhere, there are numerous other applications for this solution, such as personalized learning for students with special needs. Whatever the need is, these AI tools can keep students learning remotely with self-paced lessons that have the ability to embed video, links, and articles.
Automating administrative tasks
Educators spend an inordinate amount of time grading tests, checking homework, and following up on assignments. By using AI to automate these tasks, teachers can reallocate their time and resources to focus more on each student. One application leverages AI to make it easier to file paperwork, check the validity and authenticity of documents, and ensure the completion of paperwork at a faster pace. There is one AI-enabled solution from CampusLogic, that helps colleges assist their students in calculating how much their institutional costs will be. This way student knows that they’ll be able to afford their tuition and other expenses.
An Opportunity for Builders of Connected Systems
According to a recent study conducted by MarketsandMarkets, the global marketplace for AI-enabled solutions in education is projected to reach USD $3.68 billion by 2023. They predict that AI technologies such as deep learning, machine learning, and NLP will be applied to education and training solutions that will improve performance and the learning experience. For those design engineers and systems builders that support solutions and applications for the education space, this new level of market adoption presents enormous opportunity.
As planning, designing and executing upon AI-based initiatives for education are increasing, there are key technology considerations that educators are having to take into account. Specifically, successful AI-enabled deployments are very much dependent on the right IT infrastructures, data, and IoT devices for capturing instances.