10 examples of how artificial intelligence is improving education
Artificial intelligence (AI) is quickly becoming a common tool for use in a wide number of industries, including business, finance, and medicine. Due to the many different types of AI platforms and applications available, the possibilities for their use are endless. For example, AI can be used to detect anomalies in bank transactions to help spot fraudulent activities. AI platforms can also be used as diagnostic tools, to help pharmaceutical companies with drug discovery, and to aid doctors in spotting tumors that might otherwise be missed. And that is just the beginning.
However, the education industry still has some way to go before it has harnessed the full potential of AI. Ideas include using AI to make education more engaging and personalized, improve accessibility, complement individual learning styles, and enhance the learning experience for both the teacher and the student. In addition to improving the learning experience for students, AI could be used to help teachers save time and resources by automating tasks such as checking answer sheets and other administrative tasks.
In this article, we will take a look at ten examples of AI technology that have the potential to revolutionize the education industry and explore some organizations that are using the technology to improve performance in education.
1. Personalized learning
One theory in pedagogy is that everyone has a different learning style. Some are more visual learners, some are more aural learners, while others are more kinesthetic learners, etc. While this theory has been hotly debated, it is generally agreed that people do tend to learn in different ways – whether that involves different work and study styles, learning at different paces, or finding some subjects and concepts easier than others. Given this, it makes sense to personalize the learning experience, doesn't it? But, if a school or teacher has to personalize lesson plans for every student, it would be impossible – there is simply not enough time. Enter – personalized learning using AI.
One of the strengths of AI is that it is capable of analyzing large amounts of data quickly and finding patterns, making it a perfect tool for developing personalized learning. AI can be used to devise individual lessons around a particular subject quickly. AI-based learning systems might also be able to give teachers detailed information about students’ learning styles, abilities, and progress and provide suggestions for how to customize their teaching methods to students’ individual needs. For example, suggesting more advanced work for some students and extra attention for others.
Additionally, AI could be used to predict results more accurately, thereby helping teachers understand whether their lesson planning will meet targets for learning.
It also helps with planning, scheduling, and producing lessons for students making the experience entirely unique and hugely rewarding. This could also free up time for teachers, which can then concentrate on high-value tasks, such as working with students.
For example, a number of universities have tested the use of chatbots for repetitive tasks that would normally be done by a professor or faculty member – such as providing answers to questions frequently asked by students. Both Staffordshire University in the U.K. and Georgia Tech have developed chatbots that offer 24/7 assistance to students.
2. Adaptive learning
Adaptive learning, or adaptive teaching, is an educational method in which AI is used to customize resources and learning activities to cater to the unique needs of each learner. This is especially useful in online learning.
This is done via rigorous analysis of a student's performance data, after which the pace and difficulty of the course material are adjusted by the AI algorithm in order to optimize the learning process.
This method not only optimizes learning but can also save time and resources by removing unnecessary repetition and focusing on the concepts or areas that a student might be struggling with. The teacher can provide support wherever the student needs and the student can learn at a pace they are comfortable with.
Many companies are incorporating adaptive learning to improve the way content is delivered. One popular example is Duolingo, a language-learning app that provides listening, reading, and speaking exercises for learning around 40 different languages. The app uses AI to help ensure that lessons are paced and leveled for each student according to their performance.
3. Automated grading
Grading assignments and exams are one of the most time-consuming tasks in education. With the help of machine learning algorithms, AI tools can evaluate essays, multiple-choice tests, and programming assignments with great accuracy and efficiency, thereby saving teachers a lot of time.
A computer doing these tasks not only saves time but also ensures consistency in scoring, potentially eliminating bias, including unconscious bias, teachers may have and reducing human error in the correction process. The AI tool can also provide personalized feedback to students and teachers. This can help students improve in problem areas and enables students to take ownership of their learning.
Although automated grading powered by AI has a lot of advantages, bias may exist, even in AI. This is because machine learning algorithms are trained on data, which itself may have underlying biases. Therefore, this is still a field requiring more research to make the technology bias-free.
For example, according to a 2021 article published in OxJournal, China has been using AI auto grading platforms with increasing volume, with around 1 in 4 schools in the country testing a machine learning auto grading platform that can also give suggestions on work done.
4. Intelligent tutoring systems
Intelligent tutoring systems (ITS) are computer systems powered by machine learning algorithms that provide personalized and adaptive lesson plans based on every student's learning needs and pace. Similar to previous AI tools, ITSs analyze student data to understand learning patterns which it then uses to provide customized suggestions, feedback, and exercises suiting the individual needs of each student.
ITSs are helpful to both students and teachers as it allows teachers to monitor students’ progress and modify their teaching approach to deliver their lessons effectively. ITSs can help students learn at their own pace while providing support when necessary and challenging them when they are ready to learn more advanced concepts.
A study by the U.S. Department of Education found that existing ITSs can improve student literacy by improving their reading comprehension and writing skills. However, implementation of the systems in a classroom remains a challenge. To overcome this, natural language processing techniques have been suggested for use in scoring student responses.
Despite the challenges faced by these systems, students have had some positive responses to the use of ITSs. Another study found that students find ITSs easy to use and learn, although not necessarily fun.
5. Smart content creation
Creating lesson plans is one of the greatest challenges for a teacher, as each student has unique requirements based on the way they learn and understand concepts. The term "smart content creation" describes the use of AI to automate and enhance the generation of educational content. The AI platforms can provide detailed insight by analyzing student data to create personalized and engaging educational material.
This is then used to create customized environments depending on various learning outcomes. The students can then choose the lesson plan that aligns with their requirements. AI can help to generate interactive quizzes, simulations, and experiments, via chatbots, augmented or virtual reality, which can then be used in the customized environment to enhance the learning experience.
The biggest and most successful demonstration of this is Coursera. It uses AI to curate multiple educational and professional courses that can help the learner. Teachers can also suggest appropriate courses based on a student’s learning performance, pace, and individual requirements.
6. Learning analytics
Combing through large amounts of student data is a tedious task but can provide valuable insights into a student's learning and performance. Using automated analytics makes it easier to analyze large amounts of student data, and this can be sped up using AI. It makes the challenging and time-consuming task of data analysis easier.
Teachers can use the data to track student performance and engagement as well as to make timely interventions and provide additional support to students who require it. Similarly, students can also use it to track their performance and learning and use it to ask for additional help if they need it. The University of Michigan has a dashboard called My Learning Analytics that allows students to visualize and track their grade distribution, assignment planning, and resources.
However, there are also potential issues with the implementation of learning analytics in the education sector. A study published in 2022 highlights ethical and privacy issues, data collection, and data analysis as potentially challenging implementation problems for learning analytics. While the latter of the two concerns can also be solved with the use of AI, there are still significant ethical concerns that will have to be dealt with.
7. Virtual assistants
Many administrative tasks, such as lesson planning and organizing schedules, can be automated thanks to the power of AI. Virtual assistants take on laborious, repetitive activities, freeing up teachers' valuable time to focus on essential duties like giving lectures and interacting with students.
Additionally, virtual assistants can provide customized feedback to students, monitor their progress, and provide additional resources based on a student's individual needs. Using AI-powered virtual assistants can help teachers streamline administrative work and focus on making the learning experience engaging for students.
A study in SpringerOpen even found a correlation between students who used virtual assistants, such as chatbots, and their academic performance. They found that students who interacted with chatbots outperformed those who interacted with the course teacher in terms of academic performance. The study was conducted on 68 undergraduate students in Ghana and made a positive case for the use of AI tools, such as virtual assistants, in the education sector.
8. Natural language processing
Natural language processing (NLP) is a field of AI that deals with making computer systems that can understand and interpret human languages. NLP has many different applications, such as text generation, chatbots, and information extraction, among many others. One of the most popular uses of NLP is in large language models, such as ChatGPT, developed by OpenAI.
ChatGPT may be used by students to help with homework, prepare for an exam, or simply satisfy their curiosity while learning. Teachers can also use ChatGPT to prepare lesson plans and check assignments for grammar and information. As the popularity of the software has risen, more and more students are using this resource. And although it may seem like there are no downsides to this technology, many people think otherwise.
Students should not see ChatGPT as their answer to all the homework questions, and similarly, teachers should not see ChatGPT as the absolute of human knowledge. As mentioned in this study, it should be viewed more as an assistive technology that responds to societal values and needs. Other concerns also exist, such as the existence of bias, the knowledge not being current, plagiarism, its use as an aid in cheating, etc.
There are other technologies that use NLP, such as automated essay grading systems, which have been covered earlier in the article. Future developments with the use of NLP technologies should address the various concerns with the technology when being used in the education sector.
9. Predictive modeling
Similar to learning analytics, AI-powered predictive modeling deals with analyzing large amounts of data, which is then used to predict various outcomes, such as student performance. This information is valuable to teachers, parents, institutions, governments, and students as they can greatly help with the learning experience and setting benchmarks. This can help teachers offer timely guidance to students based on the student's predicted performance and on their previous test or exam results.
Data-driven analysis is an important tool to have in education as it can improve individual student performance and give them additional support when needed, overall enriching their learning experience. It is also of value to governments for use in planning educational goals. A study on community college students used predictive modeling to identify at-risk students based on several key variables. This helped them to drive interventions to help these students.
10. Augmented and virtual reality
Immersive technologies, such as augmented reality (AR) and virtual reality (VR), have become increasingly popular over the past few years. AR is an immersive technology that overlays computer-generated content onto real-world objects, thus enhancing a user's perception of reality. On the other hand, VR is a simulated virtual environment that the user can experience as if it were real. These technologies are used for gaming and metaverse but have huge potential in the education sector.
Students can use immersive technologies to interact with the learning material to improve their understanding of complex concepts and overall enrich the learning experience. VR, in particular, has many promising applications, such as creating labs where students can conduct chemistry experiments or virtually dissect animals. AR can be used to study stars and galaxies up close, allowing students to engage with physical things and giving them more hands-on and experiential learning.
An article published by the Information Technology and Innovation Foundation (ITIF) explained that AR/VR technologies can reduce the learning curve for students. They also mention that AR/VR technologies can help teachers enhance STEM courses, medical simulations, arts and humanities materials, and technical education. AR/VR technologies are already being used in several institutions, such as Arizona State University (ASU), which has collaborated with Dreamscape Immersive to create Dreamscape Learn. ASU students even created a time travel experience using this technology.
And there you have it – 10 of the most promising examples of AI improving the education sector. While AI provides numerous advantages for both teachers and students, it's crucial to keep in mind that it also has certain disadvantages.
One limitation of AI is that it cannot replace human interaction and empathy, which are essential in the teaching and learning process. Additionally, as was already discussed in the article, biases can be perpetuated by AI algorithms. And finally, there are always concerns about data privacy and security when it comes to AI. As a result, it is crucial to integrate AI into education, but doing so requires careful consideration of both its potential advantages and drawbacks.
The use of AI in education holds a lot of potentials and could even revolutionize the way future generations of students learn.