Artificial intelligence has made its presence known in nearly every industry imaginable and education is no exception. This cutting-edge technology initially proved controversial among teachers and administrators, but there’s no denying its appeal among students, who view AI as convenient and accessible.
At this point, whether students use AI is no longer the debate. Survey results overwhelmingly indicate that both high school and college students are making use of it, whether or not their teachers approve. That said, some educational professionals are warming up to the idea of AI in education, with many recognizing that when leveraged correctly, AI tools could actually prove beneficial.
Educational leaders must decide whether to allow AI in schools and address issues like bias and privacy that come with it. This discussion calls for a clear understanding of every application of AI in education, as valid concerns are accompanied by significant opportunities.
We will explore all this in detail below, while also revealing realistic strategies for navigating the new era of AI in education. Our goal is to reveal the answer to a growing question, “How can AI be used in education?”
Understanding AI in Education
Artificial intelligence represents a broad range of advanced technologies that can be integrated into several aspects of the educational experience. This is far more nuanced than skeptics realize. As some claim, AI is not a shortcut. It offers an accessible and personalized supplement to learning along with opportunities to expedite time-consuming and mundane tasks. So, when answering the question of “How can AI be applied in education?” understanding it as a whole is key.
Machine Learning in Education
As an important subset of AI, machine learning (ML) brings a wealth of potential to the tech-driven educational space. ML leverages data and advanced algorithms to help computers mimic the human process of learning without requiring explicit programming. Through this process, computers begin to ‘see’ patterns in data and use these insights to boost their performance.
The implications are exciting in education, where machine learning can influence adaptive learning solutions. ML algorithms utilize extensive student data, including details about their academic performance. This allows ML systems to adjust their approach to reflect students’ evolving needs.
ML will be especially valuable for the chatbot and the digital tutors of tomorrow. Already, AI-enabled chatbots offer targeted insights, developed according to specific student needs and preferences.
Furthermore, ML can uncover powerful insights about education’s greatest challenges, revealing, for example, why students drop out and which strategies prove most effective for keeping them enrolled.
Natural Language Processing (NLP) in Education
As another subset of AI, natural language processing (NLP) helps computer systems understand and use human language. This capability promotes many exciting applications across the spectrum of education.
One of the most significant applications? Gathering and analyzing student feedback, with sentiment analysis revealing how students collectively feel about various instructors, curricula, or policies.
NLP can also be a helpful tool for automated grading, especially when examining large volumes of essays. Written work can be graded according to predefined criteria, thereby reducing instructional workloads and also ensuring that students receive swift and targeted feedback.
Computer Vision in Education
Encouraging computer systems to interact with visual stimuli, computer vision helps machines perceive images or videos and automate tasks based on what these systems ‘see.’ While this technology is strongly associated with manufacturing, warehousing, and transportation, it also holds strong potential in education.
A number of educators rely on computer vision for automation, as this technology lends itself to productivity-oriented tasks. For instance, combined with facial recognition, computer vision can streamline attendance-taking processes.
Advocates also cite emotion analysis as an exciting opportunity, which can provide significant insights into students’ emotional states. These systems leverage deep neural networks, involving layers of nodes arranged in hierarchical systems. The powerful combination of computer vision and deep neural networks can help instructors determine how students feel and how they respond to various instructional strategies.
Examples of AI in Education
AI use cases abound, offering exciting advantages for students and instructors alike. Every application of AI in education comes with its own unique advantages and concerns, but the following are among the most promising:
Adaptive Learning Platforms
Adaptive learning platforms are all about personalization. Drawing on advanced AI technology, these customizable solutions assess students’ knowledge and experiences over time to reveal which instructional approaches will be most welcome and most effective. From test scores to time spent answering questions, many analytics can shape the platform-based learning experience. Examples include:
- Knewton
- Adaptemy
- Smart Sparrow
Intelligent Tutoring Systems
Some students rely on traditional tutors to provide extra insight beyond the confines of the classroom. At one time, tutors called for carefully scheduled, in-person sessions, but online availability extended access so that students could work with human tutors on a remote basis.
Now, intelligent systems promise to further expand the reach of tutoring, granting students supplemental instruction whenever or wherever they see fit. Insights from the Florida Artificial Intelligence Research Society indicate that students are highly receptive to AI tutoring, with key advantages including “personalized assistance, adapting to individual learning styles, and providing immediate feedback.”
Automated Essay Grading
It’s no secret that teachers spend long hours grading assignments. A survey from EdWeek’s Research Center reveals that this occupies at least five hours of the average teacher’s jam-packed week. This process can produce valuable feedback, but repetitive grading tasks may limit time spent working directly with students.
Automated solutions can expedite this process, leveraging NLP and other advanced technologies to streamline grading. This is especially useful for short-answer or multiple-choice exams, evaluations that call for repetitive grading tasks. AI-driven essay grading has already seen several significant improvements and is as effective as an overburdened teacher.
Chatbots for Student Support
Students often struggle to find timely answers to critical questions about class registration, campus services, or challenging coursework. Chatbots bridge the gap, connecting students with the resources they need or even answering questions outright so students don’t need to wait for human employees to take over. Examples of trusted educational chatbots include:
- AdmitHub. Designed to automate student queries, AdmitHub is an AI-powered chatbot that sends relevant messages to keep students in the loop about crucial developments. This powerful tool draws on behavioral science to help students complete necessary tasks such as registering for classes. One of this chatbot’s main goals is to boost student retention.
- Ivy.ai. Placing a greater emphasis on customization, Ivy.ai offers many forms of support. This tool can be used to enhance admission and enrollment processes or to improve access to campus resources. Ivy.ai is also favored for its seamless integration, which allows it to play a significant role in learning management systems (LMS) and other essential platforms.
Virtual Reality (VR) and Augmented Reality (AR) in Education
In an effort to make learning experiences more immersive, cutting-edge classrooms have leveraged the power of virtual reality (VR) and augmented reality (AR). This is already extensively utilized at the college level, especially for online courses that call for active experiences.
The convergence of VR, AR, and AI can ensure that immersive learning is as dynamic and relevant as possible. Yes, engaging students is important, but these experiences should be carefully developed based on which skills require extra attention and how specific students learn best.
Benefits of AI in Education
AI can produce unique benefits for students, teachers, and administrators. Different situations require different AI applications, but overall, using advanced technology can lead to greater efficiency, personalized learning, and higher satisfaction for students and instructors. We’ve highlighted a few of the most promising implications below:
Enhanced Learning Experiences for Students
Students already show enthusiasm for the integration of AI into everyday learning strategies and solutions. Others are interested in AI but may require extra instruction or support before they can fully leverage cutting-edge opportunities. Potential benefits include:
- Personalized Learning Paths. Teachers recognize that one-size-fits-all strategies do not accommodate diverse student bodies. Unfortunately, many struggle to live up to the promise of differentiated instruction. AI can address this by adjusting content and teaching styles based on specific student qualities and challenges.
- Real-Time Feedback and Support. Even when instructors have good intentions, they often struggle to respond promptly to student inquiries. This can be frustrating for busy students, who may struggle to convey their learning concerns accurately if forced to wait for too long. Real-time insights can keep their study sessions on track, and with AI solutions, answers are only a click away.
- Gamification and Engagement. AI tools can support gamification efforts, which aim to make learning more exciting while boosting student engagement. AI can be built into interactive learning activities, using intriguing challenges or simulations to bring a more active element to instruction. Meanwhile, AI analysis reveals which learning strategies students find most compelling and can lean on these solutions to keep students feeling excited and motivated.
Increased Efficiency and Productivity for Educators
Busy instructors only have so much time to dedicate to repetitive tasks. Many welcome the opportunity to streamline time-consuming activities such as grading papers or sending reminders. AI solutions can provide a significant productivity boost, thereby freeing up instructors to focus on interacting with students in a more meaningful manner.
Improved Accessibility and Inclusion
Accessibility and inclusion have long represented huge challenges in traditional education. While we have come a long way in recent years, AI tools promise to provide yet another boost. These tools are especially valuable for vision and hearing-impaired students, as they can convert text to speech or provide real-time captioning.
AI may even revolutionize learning for students with ADHD. These well-meaning students often struggle to sit through traditional assignments or lectures. Specialized cues help them stay on track, while adaptive systems adjust their approach to drive maximum engagement.
How Educational Leaders Can Prepare and Embrace AI
Educational professionals have previously expressed skepticism about AI tools, but sentiments are beginning to shift. At this point, it’s not a matter of whether AI will enter education, but rather how. Educational leaders will see far more positive outcomes if they embrace AI and actively plan for its expanded role in future classrooms.
Invest in Professional Development
Professional development courses introduce instructors to AI and its many benefits while revealing how AI can be leveraged in various settings or situations. This can help staff members feel less intimidated and more excited about their AI journey.
Opportunities for professional development could include workshops, continuing education, or mentorship. Additionally, AI systems can be incorporated into seemingly unrelated training initiatives, as simply navigating these tools will help teachers feel more comfortable using similar solutions in other contexts.
Develop a Comprehensive AI Strategy
A purpose-driven approach to AI can encourage both teachers and students to make the most of AI’s powerful capabilities while overcoming its downsides. This should include clear objectives, revealing why AI is valued and what schools want to accomplish by leveraging advanced educational systems. Strict policies must be adopted to account for concerns regarding privacy and transparency.
Foster Collaboration and Innovation
Educational professionals have strong opinions about AI and they want to make their perspectives known. They should receive ample opportunities to share feedback about potential or existing AI systems. If this becomes a collaborative effort, teachers may feel empowered to share suggestions that can enhance AI solutions and streamline classroom adoption.
Address Ethical Considerations
AI presents significant ethical concerns that should not be ignored. Mitigation strategies should be purposefully built into AI solutions. For example, the potential for bias can be addressed by carefully evaluating AI tools and simply understanding how and why bias occurs.
Teachers should be willing to discuss ethical concerns with students and should welcome student insights into potential situations involving bias. This is a skill like any other, and students need to be taught to think critically about the information that AI systems present.
Embrace Educational Opportunities With Marymount
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Embrace administrative opportunities by pursuing your online master’s in education administration and supervision, which places a strong emphasis on ethics and integrity as they relate to modern education.
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Sources
https://leadershipblog.act.org/2023/12/students-ai-research.html
https://journals.flvc.org/FLAIRS/article/view/135314
https://www.edweek.org/teaching-learning/how-teachers-spend-their-time-a-breakdown/2022/04
https://hechingerreport.org/proof-points-ai-essay-grading/
https://training.safetyculture.com/blog/adaptive-learning-platforms/
