AI in Education
- Updated On 19/02/2020
- Author : HBB | Guest Author
- Topic : Technology
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The state of AI in Education
AI is already being used in education for a wide range of tasks that include, but are not limited to, creation of personalized content, automatic grading and feedback, and designing of courses that are comprehensible. Major industry players like Elemental Path and Volley Labs have already infused the power of AI into their teaching programs. There are several companies, such as Content Technologies and Carnegie Learning, currently developing intelligent instruction design and digital platforms that use AI to provide learning, testing and feedback to students that gives them the challenges they are ready for, identifies gaps in knowledge, and redirects to new topics when appropriate. Other examples include Cram101 which uses AI to make textbook contents more lucid and easier to navigate with summaries of the chapters, flashcards, and practical tests. It’s also being used to aid students in performing their tasks. For example, IBM’s Watson Analytics is able to answer natural language questions about info included in its database, while Google’s G Suite for Education app uses natural language processing to write complex formulas at the request of students and teachers. Moreover, it also includes tools that assist in making content more reachable. Tools such as Presentation Translator, a free plug-in for PowerPoint, creates subtitles in real time for what the teacher is saying.
Trends of AI in Education
Amongst the numerous roles AI’s playing in shaping education, the top trend I find is automation of administrative tasks. Checking homework, grading papers, looking through illness records and absence sheets, and preparing report cards are just some examples of the tasks where educators spend most of their time – tasks that an AI can perform with almost no errors in just a few minutes. Educators spend a lot of their valuable time on these tedious tasks. Firms are now offering AI in education solutions that can automate these and many other admin tasks. This leaves teachers with more time to plan lessons and conduct one-on-one interactions with students. Moreover, professors will have more time with their students rather than spending long hours grading them. AI is also institutions to minimize the time required to complete difficult tasks such processing of paperwork. In China, semi-sentient robots are already being used to automate the grading process, reducing the workload for teachers. Their smart artificial minds can understand the general logic and meaning of an essay and generate an almost human-like judgment about its quality. At least 60,000 schools have already implemented them with reportedly great outcomes. While AI may not ever be able to truly replace human grading, it’s getting close.
Challenges of AI Adoption in Education
A lot of effort is being put into infusing AI with education and to make this infusion resourceful for both instructors and students, however, like other new technologies, its adoption won’t be simple. One of the biggest challenges to adopt AI is preparing teachers for AI-powered education and preparing AI to understand education. Teaching and learning requirements may be substantially re-ordered and the dynamics of learning versus teaching in an AI-based system of education will be very different. This will surge requirements for modified teaching degrees and certificates in this new environment. Given the eventual widespread use of AI in the classroom, teacher training is therefore a critical aspect. To be able to use AI-enabled technologies effectively, teachers will also need assimilate new competencies, clear understanding of how AI-enabled systems can facilitate learning and possess research and data analytical skills, so that they can interpret data provided by AI-enabled systems. Teachers can gain these skills at a data science bootcamp or other available courses. Furthermore, for AI to understand education systems requires real-time data processing in the form of real-time feedback, quicker interventions, and individualized instruction by teachers. These are the challenges that will be faced early on and need to be tackled.
Benefits of AI in Education
For educational content to be accessible and clear for students, learning content must be customized for each student. Students come from different backgrounds and possess different set of skills and abilities. A single type of unified content won’t be effective. With the introduction of AI, teachers can perform much better by offering personalized recommendations to each pupil. AI customizes in-class assignments as well as final exams, ensuring that students get the best possible assistance. Through AI-powered apps, students get targeted and customized responses from their teachers. Over the course of a student’s educational career, they output an enormous amount of data in the form of papers, exams, and classroom participation that rarely carries over to the next term. With these new tools, however, student data can be stored an analyzed over time to see what material they engage with more successfully and what educational deficits they may have hidden in their past work that might be inhibiting their future potential. AI has also helped digitize textbooks and create customizable “smart” content for students of all age ranges, helping them with memorizing and learning. One example is D2L, the maker of Brightspace Insights, a suite of analytical tools for educators. Brightspace captures, aggregates, and analyzes data streamed from several different sources, including learning apps, online resources, publishers, and other learning management systems to build a complete model of individual student learning behavior. Over time, this can teach the teacher exactly what a student needs to succeed.
The future of AI in education
The student of the future will be getting an AI-based educational experience where they will be exposed to an immersive, digital education heretofore unimaginable. AI will change where students learn, who teaches them, and how they acquire basic skills. It has the potential to radically change just about everything. Educational programs powered by AI are already helping students to learn basic skills, but as these programs grow and as developers learn more, they will likely offer students a much wider range of services. On the other hand, as AI gets more sophisticated, it might offer services that were never thought of before, such as reading a student’s expression that indicates they are struggling to grasp a subject and modifying the lesson to respond to that. While there are things that human tutors can offer that machines can’t, the future could see more students being tutored by digital tutors. Some of these programs already exist and teach students fundamental content, but aren’t ideal for helping students learn complex concepts, something that real-world teachers can do. Yet that shouldn’t rule out the possibility of AI tutors being able to do these things in the future. With the speedy pace of technological progression, advanced tutoring systems may not be a dream.
Rahim Rasool is an Associate Data Scientist at Data Science Dojo (DSD) where he helps create learning material for DSD’s data science bootcamp. He holds a bachelor’s in electrical engineering. He possesses great interest in machine learning, astronomy and history.
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