Using artificial intelligence in education is not a new concept. AI has been used in the classroom for years to help make learning more interactive and engaging. Yet, with recent advancements in technology, AI has become even more prominent. To find out how you can use this innovative technology effectively within your educational institution, continue reading.
Assignment Grading and Student Feedback
Grading student assignments can be tedious and time-consuming, especially for educators who teach many classes. Luckily, AI can take up some of this burden by grading essays and providing feedback on students’ work.
AI-powered software can take in all the information, analyze it, and then give feedback on what needs to be improved. This is especially helpful for teachers who want to have a more effective way of grading assignments without doing tedious work themselves.
AI also has an advantage when dealing with diversity in writing styles. They are not biased like humans. One of the software you can use to grade quantitative vs qualitative research assignments is a robo-grader.
AI software derives metrics from manually fed data. This includes essays already marked and graded by an instructor. Thus, it’s essential first to have a clear rubric that makes sense. AI also offers consistency and an ability to provide better feedback.
Modern learning lays a great emphasis on personalized content. This allows all students to focus on their strengths and interests while preparing them for the future world of work.
AI can help assess a student’s understanding as well. It is difficult to do when you have many different types of learners with diverse needs in your classroom. AI can also monitor progress by providing feedback at certain intervals.
For instance, by asking a question, like what a synthesis essay is, and allowing the learners to type their answers, an instructor may determine who does not know the meaning.
AI can also help create customized content for an individual student’s needs and preferences using natural language processing systems. This means AI may learn what topics a learner has already mastered and then focus on sending more challenging material as needed.
Interactive and Engaging Learning
AI makes it possible to attain high engagement levels through interactive learning activities. This can come in the form of gamification. Gamification incorporates game design elements into lesson plans to make them more appealing. Gamified lessons may include
- a progress meter;
- points or badges for achieving specific goals within the lesson plan;
- rewards at the end of successful objectives.
High student engagement is also possible through storytelling techniques. Personal narratives or stories can teach a specific topic. This technique is helpful in teaching complex concepts like how to write a cause and effect essay because it stimulates different parts of the brain than traditional lectures do.
Kahoot is an example of a gamified learning environment where students can compete against each other in a timed quiz. Since its launch in 2013, Kahoot has been used by teachers and students in over 190 countries, helping to engage students with exploring topics.
Big data is the most talked-about topic regarding AI’s impact on education. Data is collected, analyzed, and interpreted by artificial intelligence algorithms. Students can then receive more personalized lessons tailored to their strengths and weaknesses.
With AI, blind decision-making by institutions and educators is a thing of the past. Data analytics can improve decision-making in education through predictive analysis and pattern recognition. This allows for better prediction over time about how students will perform on tests or other assignments.
Chatbots have a broad set of applications. They are beneficial for students with learning disabilities or those without tech skills to navigate learning platforms. TutorBot is an example of a chatbot capable of responding to student queries.
Learners come with different traits. These are useful when customizing the educational experience. The curriculum is tailored to each individual. For instance, learners are grouped by academic levels and interests to make the learning process more engaging.
Adaptive Learning Systems
Adaptive systems allow for a personalized experience. Learners receive content relevant to their needs, goals, and skill sets. Some examples include the following:
- Course Hero’s adaptive math system;
- Stanford University’s intelligent tutoring system.
Video lectures use speech recognition software and cloud-based video storage. This makes it easier for educators to deliver age-appropriate content.
In the next few years, AI will be commonplace in classrooms. It’s a technology that is here to stay and has undisputed benefits for all learners. Educators should learn more about integrating this tech into their curricula. Then, they will find new ways of engaging students and increasing their achievement rates.
With so many teachers embracing AI today, it’s only a matter of time before it becomes an integral part of every school curriculum out there. Yet, institutions need to address challenges like the scalability of technology and funding for implementation.