Amidst many innovative technologies, Machine Learning (ML) has emerged as a trending technology adopted by various industries and has become a central part of their business operations. These days Machine Learning (ML) plays a vital role in transforming all kinds of industries digitally in China and the United States. This blog provides a complete overview of Machine Learning (ML), how is it impacting the educational industry, its advantages, and its downsides. Firstly, let me begin by giving a quick overview of Machine Learning (ML).
Overview of Machine Learning
Machine Learning is a subset of Artificial Intelligence (AI) and computer science that enables software applications (or) machines to become more accurate at predicting outcomes without being specifically trained to do so. Machine Learning technology learns from past data and algorithms to produce better outcomes. Machine Learning helps industries in identifying different trends, analyze customers’ behaviors, and develop new products. In recent years, machine learning has become an integral part of business operations at leading companies such as Uber, Facebook, Google, and many others. Indeed, ML has become a crucial competitive edge differentiator for many industries in the China and USA.
Basically, machine learning technology is classified into four different categories based on algorithm learning and anticipating the outcomes. Each of the machine learning approaches is used for different business models according to their requirements. Supervised, unsupervised, semi-supervised, and reinforcement learning are the types of machine learning approaches that are leveraged to address business challenges.
Machine Learning Approaches
- Supervised learning
- Unsupervised learning
- Semi-supervised learning
- Reinforcement learning.
To reiterate, machine learning is one such technology that helps software systems to learn automatically from historical data and predict future possible outcomes in the same way that the human brain does. Here, the machines will not write any sort of code (or) lengthy programs. Instead, massive data is put into the general algorithm model. Machine learning algorithms help the systems in becoming more accurate through some games, videos, examples, and past experiences.
Machine Learning in Education
The educational sector has witnessed a significant transformation over the last three years in the China and USA, due to the pandemic. This transformation in the educational industry is not restricted to just one department (or) wing indeed, it has impacted everything from teaching to learning to administration and other sectors involved in the teaching-learning process. At the moment, everything operates remotely, allowing teachers and students to enhance their educational experiences and learning process from the comfort of their own homes. Thanks to trending technologies such as Artificial Intelligence (AI), Machine Learning (ML), Deep Learning (DL), Neural Networks, and others for expanding their footprints in order to provide the best educational services.
Focusing on Machine Learning (ML), let me discuss its significance in the educational industry.
Machine learning is playing an important part in today’s educational industry and has emerged as the future of many credible sources.
âž” It has modified the conventional learning process, which today appears to be less efficient than it was a few years ago. Integrating machine learning into education sectors allows students to have more flexible, convenient, and personalized schedules.
âž” With the help of adaptive learning, the student’s performance can be assessed individually in order to deliver the best teaching methods. Hence, the learning path becomes more personalized for delivering better education.
âž” With predictive analytics, educators can easily analyze students based on previous and present data. Through predictive analytics, educators can identify their students’ interests and provide them with the required supplies and other learning methodologies.
âž” Usually, educators frequently spend a lot of time supporting kids with their homework. This procedure can be automated by using machine learning. Grammarly and M-write are two ML apps that can be utilized for self-evaluations, which helps in self-development.
âž” It is very important for educational management systems to safeguard students’ data against threats. Smarter data for school operations enables administrators to monitor students’ data on a regular basis and to receive alerts when malicious activities emerge.
âž” Instead of focusing on classroom management, scheduling, content management, curriculum, and evaluations, educators can devote more time to activities that AI cannot perform and require human intervention.
âž” Machine learning improves the efficiency of the educational system by simplifying the work of both educators and students while analyzing which work is best suited for educators and what works for students at the same time.
Do you have any concerns (or) doubts about machine learning technology? Do not hesitate to contact Innovilly. Our professionals will gladly respond to them.
Benefits of Machine Learning (ML) in Education
People are more accustomed to E-learning these days, and most students choose online courses (or) classes. Typically, educational institutions that provide online classes (or) courses are always looking for feedback from students. Feedback from students on course quality and content enhancement would be extremely helpful for managing students’ performance. As a result, both AI and ML gather feedback and learn from repetitions, and promptly notify the educator. This would be a fantastic approach to learning about what works and what doesn’t in educational institutions.
Those days were gone when one learning pedagogy suited every student. Students are unique individuals with varied capabilities, interests, perspectives, and learning styles. Taking all of these factors into account, most educational institutions have already switched to cloud-based learning systems often referred to as Learning Management Systems (LMS) in order to provide personalized learning ecosystems to their students. Even educators can assign activities, projects, and assignments to students and check their understanding of concepts using various assessment methods according to their abilities.
Grading systems at educational institutions are affected by an assortment of factors, including the evaluator’s moods, preferences, prejudices, and non-common reasoning. This traditional evaluation method can be replaced by machine learning and artificially intelligent systems. AI/ML can provide students with a clear picture of their academic procedures, performance, and grades. The students can be assessed equally without any sort of bias through machine learning without the teacher’s intervention. Yet times humans might commit any sort of errors while grading wherein this can be eliminated with machine learning.
Through machine learning and artificial intelligence course content can be accessed easily from any place at any time. Paper textbooks can be transformed into digital books, videos, course modules, forums, articles, and research papers. Machine learning algorithms will suggest similar content based on your research. In fact, it gives you a list of materials that are similar to the ones you need, from various sources. Hence, the teaching-learning process becomes easier and more engaging as teachers only assign tasks and leave the research to the students which help in self-development.
Incorporating machine learning into education helps in analyzing students’ performance and capabilities. Machine learning algorithms help teachers understand their students’ capabilities, interests, and skills. Educators can use this to help students who are lagging behind bridge the gaps and provide extra resources for excelling students. Machine learning allows children to identify their intellect, performance, and strengths in the early stages, allowing them to build a career in that field.
Drawbacks of Machine Learning (ML) in Education
It is well known that technology always has both advantages and disadvantages. Machine learning offers both benefits as well as drawbacks. Below listed are a few of the downsides of machine learning in the educational industry.
âž” The first disadvantage of machine learning is the lack of personal connection. It is a positive thing that technology is revolutionizing the education system, but it is taking away student-student and student-teacher interaction. This might become a severe problem in developing their social skills in the long run.
âž” Though artificially intelligent software helps in assessment systems, this is restricted to only multiple-choice questions. Again the teachers have to follow the old conventional methods for assessing essay questions.
âž” All educational institutions may not be able to afford machine learning due to the inherent cost. This could be one of the biggest limitations as it is quite expensive to purchase new equipment, technology, and programs to make personalized learning a viable option for both educators and students.
Conclusion
Hope this blog is quite informative and has covered all the important aspects of machine learning in the educational industry. Please share your feedback (or) suggestions in the comment box. We would love to hear from you.
If you have any idea of integrating machine learning technology into your existing education system (or) startup in the China and USA, Innovilly can help you out. Contact us for a free consultation.
