Education Industry
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AI is Changing the Education Industry – Let’s Find Out How!

Existing and emerging technologies have played an essential role in the evolution of the education sector. With AI technology, the education industry is building robust, reactive platforms that can provide reliable information for performance, emotional state, and much more. With the development of artificial intelligence-empowered educational games, the overall educational process has been significantly enhanced. 

Integration of AI in education solves language processing, reasoning, planning, and cognitive modeling. It helps in organizing and building content to support business operations. Stallion Market Research has found that the global AI in the education market contributes to the rise of adaptive learning, the development of the IT sector, and the leverage of intelligent learning devices. 

Reports from Stallion Market Research estimated AI in the education market to be between USD 400 million to 500 million in 2017, with the growth anticipated at 45% CAGR from 2018 to 2024. The education market’s current opportunities include implementing collaborative learning models, trending AI services, and facilitating the course designs. 

The education market can be segmented into higher education and K-12, which can be further categorized into learner model, pedagogical model, and domain model. Here are more ways in which the tools and applications that implement AI shape and define the global education market.

Advantages of AI in Education

● Automation of Processes

AI may not truly replace humans in teaching and grading, but it has simplified and automated processes. Automation in the education industry adds value by enhancing speed and convenience to the teaching and assessment processes. Artificial intelligence allows students to learn at their own pace and attest to their progress. AI-enabled learning processes can assess students without bias, intervention, or assistance. 

It will ultimately increase the speed of grading papers, attesting examination papers, and other similar tasks. It can enable teachers to focus on in-class activities and student interaction instead of spending several months grading. Grading homework and tests can be a tedious task utilizing the significant time and resources of educational institutions. 

The time which could be invested in interacting with students, preparing for classes, or ensuring professional development is diverted towards grading. The research on AI in education from Stallion Market Research concludes that automating education and institutional processes will make the sector disciplined, flexible, and closely tailored to individual preferences and requirements.

● Simplify Administrative Tasks

I can simplify filing paperwork, check the validity and reliability of documents, and ensure complete and error-free maintenance. It can improvise IT processes to explore new efficiencies, such as determining and simplifying complex data to enable smooth operations across departments with data-driven forecasts. 

AI in the education sector can also assist without complaining about tedious data handling and administrative tasks. It ensures functions that are subject to human errors are performed without lethargy or other consequences with accuracy and efficiency. It controls several administrative expenses by intelligently deciding restocking only when necessary to avoid wastages caused by over-ordering. Artificial intelligence can simplify the segmentation and processing of paperwork across educational institutions.

● Smart Academic Content

AI in education can enhance the learning experience for students with new techniques to ensure academic success. Online learning can capture and record to read, listen, or watch over again. It provides clarity, preciseness, and accuracy. AI systems are using the traditional curriculum to create customized learning syllabus for specific subjects. 

Digital learning creates a new learning interface that helps students of all academic disciplines and grades. ‘Smart content’ includes video conferencing and lectures with engaging activities for a complete learning environment. It makes traditional textbook content more accessible and understandable with practical tests. 

Lecturers and teachers can bridge the learning gap by identifying pain points and addressing them quickly using AI. It also prompts students to learn on the go instead of scheduling appointments with their teachers. With immediate feedback, it helps them understand a concept and remember them correctly for the next time. Stallion Market Research has observed the maximum usage of AI in education, especially post-pandemic. COVID-19 has created a ‘new normal’ across the education sector, and artificial intelligence has quickly adopted it.

● Personalized Learning Experience

Artificial intelligence can customize in-class assignments with personalized recommendations to ensure the best possible assistance. Our research on AI in education indicates that instant feedback is essential for result-driven learning. AI-powered learning provides targeted and customized responses from teachers. Teachers can condense lessons into smart study guides and flashcards for easy understanding. 

Stallion Market Research concludes that students’ emotions influence their achievements – confidence, boredom, confusion, stress, and anxiety are all strong predictors of achievements. Mentoring systems need to support decision-making and reasoning, which AI can accomplish. Rich and multi-faceted instruction models powered by AI can determine real-time and appropriate guidance for student cognition, meta-cognition, and emotions. 

Collaborative learning enables students to share their experiences and perspectives to persuade others to understand their views and articulate their learning curve. AI-powered education provides one-to-one attention based on student interactions.

● Global Learning Adaptation

Education should be limitless, and AI in education can eliminate geographical boundaries. With the pandemic’s ‘new normal,’ AI has helped in adopting the drastic transitions by facilitating learning from anywhere worldwide at any time. AI-powered education enables students to be skilled with fundamental IT skills. 

It has created a platform for education for all with a broader range of courses. From recruiting to suggesting suitable methods to students, intelligent systems and AI-powered applications can help students get a tailored learning experience based on their requirements and goals. AI in education is gaining popularity with its tremendous potential to bridge the gap between teaching and learning. 

Stallion Market Research expects standard adaptive learning models to be designed from three dimensions: content, data, and algorithm. They integrate multiple technologies into AI-powered learning systems to focus on diagnosis and assessment of learning, adaptive recommendation, analysis, and knowledge acquirement. Let’s now find out all the technologies involved in creating intelligent AI-powered learning environments.

  • Generic algorithms merged with logistic regression optimize the path of learning to maximize efficiency. It helps understand students’ learning objectives and current learning status to adjust the syllabus in real-time based on their developments.
  • Graph theory implements intelligent adaptive learning. It comprehends students’ abilities and knowledge status through quiz testing, which is necessary for accurately defining students’ expertise and mastery.
  • Machine learning technology enables you to personalize recommendations with the most suitable content for students based on their preferences, learning habits, and style of learning. Depending on students’ learning status, objectives, and intelligence, AI applications can automatically suggest lessons with suitable difficulty levels.
  • The Bayesian network predicts students’ learning ability to determine the timing for the next stage of learning. Its data processing mechanism identifies the connection between students’ comprehension level and the course.
  • Deep learning and natural language processing is used to automate learning materials by analyzing student profiles. It generates labeled learning materials from a pool of resources to select customized content automatically.
  • Knowledge space theory and information entropy theory measures information based on metrology. It is leveraged to test critical concepts and gain insights into students’ learning status more efficiently and accurately.
  • Educational data mining and learning analytics measure and analyze learning processes and activities using students’ data, including learning time, duration, and performance. It helps in developing personalized learning with tailored incentives.

Future of AI in Education

Artificial intelligence has the power to balance the education sector and become a key differentiating factor for institutions that embrace it. The AI-powered education systems are not as empathetic as human beings and require human assistance for the best results. Though AI’s future in education will optimize and change the operations of the education sector, these systems may not completely replace teachers in classrooms. Including data science and artificial intelligence systems courses, curriculum, and technology infrastructure will help move towards AI-powered education systems.

The World Economic Forum has estimated that by 2022, the education sector will be powered by technologies such as machine learning and artificial intelligence. Stallion Market Research predicts that the education sector will focus on STEM (science, technology, engineering, and mathematics) and non-cognitive soft skills to match the ever-changing environment. Preparing students for the future workplace will require them to use AI to their advantage and solve problems with a team-player approach. Stallion Market Research can provide deeper insights into the education sector based on your requirements. Get in touch with us today!