How is AI Revolutionizing Education in American Classrooms?

AI is making its presence felt everywhere, and education is no different. It is changing the educational ecosystem and provides significant advantages. In education, AI is being used by making use of technologies like Machine Learning, Natural Language Processing and Computer Vision. 

In this blog, we will discuss in detail the use of AI in American classrooms and the impact it is having. So, let’s get started.

To begin with let’s have a look at some of the statistics about use of AI in American classrooms.

“92% of US state agencies are seeing increased interest in AI usage in classrooms.”(Source:Statista)

“53% of US high schoolers are using AI on a regular basis.” (Source:Statista)

“60% of K12 teachers in the US say that their school permits the use of generative AI.”(Source:Statista)

“Over 65% of college students in the US have used AI tools for assignments or studying.”(Source:Intelligent.com)

“41% of educators in higher education believe AI will be essential in the future of teaching.”(Source:EDUCAUSE)

Current Application of AI in American Classrooms

Application of AI in American classrooms are several and also impactful. Let’s have a look at some of the major applications of the same. 

1.  Adaptive Learning Systems

Arizona State University uses Ed-Tech platforms to offer personalized curricula as per each student’s learning needs. This leads to better performance and higher engagement of students. This is needed as each student is unique and cannot be treated in the same manner.

2. Virtual Reality(VR) & Augmented Reality(AR)

AR & VR is being used in various domains including Metaverse and gaming. However, it can also be used for teaching purposes. This technology provides an immersive experience to students and enables them to understand the concepts better. 

AR & VR can especially be useful for teaching the subjects of Science and Mathematics.

3.   Automated Grading & Feedback

AI can fully take over the task of grading students in multiple-choice tests and assignments. This frees up time for teachers to interact more with students. One such automated tool is called Gradescope, which provides consistent, meaningful, and automated feedback.

It also provides detailed analytics of students' performance, which includes per-question statistics. As a result, teachers can identify common areas of difficulty and address them.

4.  Streamlined Administrative Work

AI can streamline administrative work in educational institutions, which enhances efficiency and allows leaders to focus on more important areas. AI can take over routine processes like scheduling, attendance and data management. 

AI-driven tools can quickly analyze students' performance and provide insights which can be used for taking major decisions. 

Chatbots can be used to answer routine queries from parents and students. AI can also be used to allot budget and resources based on previous trends.

5.  Emotional & Social Learning 

AI technology-based applications are trying to help students with special needs, like those with Autism and other learning disorders. AI can assist such students in developing better social and linguistic skills. 

This application of AI in education can be achieved using human-computer interaction and robots.

Challenges of Using AI in American Classrooms

Although AI is very useful for teaching and administrative purposes, there are some challenges which need to be addressed for its complete adoption.

Privacy & Data Security

When it comes to protecting student information, adoption of AI-powered learning causes significant Data privacy concerns. With the increasing use of EdTech tools, there arises questions regarding type and volume of data stored. 

There are also questions about who can access this data and how to protect it from hackers. Parents and students should be informed about data usage and consent processes. Educational institutes should partner with reputable vendors that give priority to data security.  

Dependence on Technology

With the use of AI for educational purposes, there is always a risk of students and teachers becoming too much dependent on technology.

As a result of such a situation, there will be a decreased ability to think critically and solve problems without making use of technology. Developing this ability requires the use of traditional learning processes.

Algorithm Bias

Algorithm bias can creep into educational institutions as AI systems are trained on historical data, which can be biased. It may happen that someone who is not a native English speaker may get his/her work flagged as AI-generated by the evaluation algorithm. 

With the increasing use of AI in American Classrooms, it becomes difficult to eliminate biases due to historical data and previous outcomes.

Monetary Constraints

Making use of AI technologies for education requires investment in terms of money and human resources. Not all educational institutes have the resources to make use of AI-powered learning in education.

Making use of EdTech requires infrastructure, maintenance, and investment from students to buy new gadgets.

Reduced Human Interaction

AI technology cannot completely replace the human-to-human connection, which takes place in traditional learning methods. This emotional connection is also vital for overall growth and education.

This reduction in interaction between students and teachers and between students themselves is also an area of concern.

Case Studies of Use of AI in American Classrooms

Let’s have a look at some of the Use Cases of AI in American classrooms. This will help in getting a clear picture of how EdTech is revolutionizing education in the USA.

Case Study 1: Stanford University

Stanford University was facing the issue of not being able to provide personalized learning to students of courses with high enrollment. Traditional teaching was failing in this case and there was lower engagement, high drop out rates of students.

Stanford University introduced AI-based adaptive learning platforms in several courses. These platforms made use of machine learning to customize content for each student. 

As a result of use of AI-based platforms, there was a substantial increase in student learning outcomes. There was a reduction in drop out rates and increase in student satisfaction. 

Case Study 2: Massachusetts Institute of Technology (MIT)

MIT faced the issue of student retention and academic success across its diverse and large student body. Traditional methods were not sufficient to address individual needs of students.

MIT developed a predictive analytics system based on AI, that makes use of historical data on attendance, student performance and other academic parameters. This system makes use of Machine Learning algorithms to detect potential academic challenges.

As a result of the use of this AI-based system, there was improvement in student retention rates and academic success. Faculty members receive timely insights from AI systems that allow them to make important decisions. 

Case Study 3: Santa Monica College, USA

Students belonging to Santa Monica College were facing difficulties in choosing careers as per their interests and job market. Existing counsellors were not able to match the needs of a large student body. 

Santa Monica College introduced a sophisticated AI-based career counselling platform that collected data on students’ performances and personal interests and analyzed them. 

This AI platform also analyzed labor-market data in real time and predicted future career trends. This improved students’ satisfaction, and they made more correct career choices. 

Case Study 4: Juilliard School, USA

Students of the Juilliard School in the USA, especially those in the music department, needed to improve their performances and refine their techniques and expressions. Traditional feedback methods were limited by the availability of instructors who could provide detailed feedback. 

Juilliard School introduced an AI powered tool called Music Mentor that was designed to evaluate students' performances. This tool made use of advanced algorithms to provide the results. It was capable of analyzing dynamics, tempo, pitch and expressions and providing real-time feedback to students. 

As a result, students are able to receive detailed as well as immediate feedback. This leads to quicker adjustments to their performances and better technical proficiency. This AI tool was supplementing instructor-led training.

Case Study 5: Ivy Tech Community College, Indiana

Ivy Tech Community College was facing issues of student retention and low success rates. Many students faced the risk of failing courses early in the semester mostly because of non-academic challenges.

The institute implemented an AI-powered pilot program to identify students who were at the risk of failing in the first semester. This system analyzed data from various course sections and found out areas where students were facing difficulties. 

This helped in targeted interventions and support for students in both academic and non-academic areas.

By the end of the semester, there was a significant reduction in failure rates among targeted students. 

To Conclude…

We have seen the different ways in which AI tools are revolutionizing education in American classrooms. It is also helping in automated grading, feedback and administrative work along with education.

However, there are some challenges which need to be addressed for large-scale adoption of AI in American Classrooms. This includes data privacy, affordability and reduced human interaction.

These challenges would surely be addressed in the near future and adoption of AI in American classrooms is only going to increase.

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