Imagine you’re a teacher excited about using AI tools in the classroom to personalize learning, save time on routine tasks, and engage students. But when you tell your students about the new AI tool you’ll use in class, they respond with little enthusiasm. Some of them look worried and others even roll their eyes. What’s going on? This scenario illustrates one of the many challenges of using AI in a classroom. Students may have preconceived notions about artificial intelligence that can create roadblocks to successful implementation. As they say, knowledge is power. Understanding what are the challenges of using AI in a classroom can help teachers prepare for and address any issues that arise when using AI tools and create a smoother, more effective integration process. In this article, we’ll discuss the common obstacles educators might encounter and how to overcome them so you and your students can reap the benefits of this innovative technology.
EssayGrader’s grading software for teachers can help you achieve these goals by easing your workload, personalizing student feedback, and making using AI in education less intimidating for teachers and students.
What is AI in Education & Its Applications
AI is slowly making its way into education, and it may change how students learn, how teachers work, and how we structure our education system. Some educators and leaders look forward to these changes with great enthusiasm. Sal Kahn, founder of Khan Academy, went so far as to say in a TED talk that AI has the potential to probably have the biggest positive transformation that education has ever seen.
But others warn that AI will enable the spread of misinformation, facilitate cheating in school and college, kill whatever vestiges of individual privacy remain, and cause massive job loss. The challenge is to harness the positive potential while avoiding or mitigating the harm.
How Can AI Personalize Learning?
Artificial intelligence is a branch of computer science that focuses on creating software capable of mimicking behaviors and processes we would consider intelligent if exhibited by humans, including:
- Reasoning
- Learning
- Problem-solving
- Exercising creativity
AI systems can be applied to an extensive range of tasks, including language translation, image recognition, navigating autonomous vehicles, detecting and treating cancer, and, in the case of generative AI, producing content and knowledge rather than simply searching for and retrieving it.
Foundation Models in Generative AI
Foundation models in generative AI are systems trained on a large dataset to learn a broad base of knowledge that can then be adapted to a range of different, more specific purposes. This learning method is self-supervised, meaning the model learns by finding patterns and relationships in the data it is trained on.
Large Language Models (LLMs)
Large Language Models (LLMs) are foundation models trained on vast text data. For example, the training data for OpenAI’s GPT model consisted of:
- Web content
- Books
- Wikipedia articles
- News articles
- Social media posts
- Code snippets and more
OpenAI’s GPT-3 models underwent training on a staggering 300 billion tokens or word pieces, using more than 175 billion parameters to shape the model’s behavior, nearly 100 times more data than the company’s GPT-2 model had.
How LLMs Learn and Understand Language
By analyzing billions of sentences, LLM models develop a statistical understanding of language: how words and phrases are usually combined, what topics are typically discussed, and what tone or style is appropriate in different contexts. This allows them to generate human-like text and perform a wide range of tasks, such as:
- Writing articles
- Answering questions
- Analyzing unstructured data
Examples of LLMs and Their Applications
LLMs include:
- OpenAI’s GPT-4
- Google’s PaLM
- Meta’s LLaMA
These LLMs serve as foundations for AI applications. ChatGPT is built on GPT-3.5 and GPT-4, while Bard uses Google’s Pathways Language Model 2 (PaLM 2) as its foundation.
Some of the best-known applications are:
- ChatGPT 3.5: OpenAI released the free version of ChatGPT in November 2022. It was trained on data only up to 2021, and while it is very fast, it is prone to inaccuracies.
- ChatGPT 4.0: The newest version of ChatGPT is more powerful and accurate than ChatGPT 3.5 but also slower and requires a paid account. It also has extended capabilities through plug-ins that allow it to interface with website content, perform more sophisticated mathematical functions, and access other services. A new Code Interpreter feature allows ChatGPT to analyze data, create charts, solve math problems, edit files, and even develop hypotheses to explain data trends.
- Microsoft Bing Chat: An iteration of Microsoft’s Bing search engine enhanced with OpenAI’s ChatGPT technology. It can browse websites and offers source citations with its results.
- Google Bard: Google’s AI generates text, translates languages, writes different kinds of creative content, and writes and debugs code in more than 20 different programming languages. The tone and style of Bard’s replies can be finetuned to be simple, long, short, professional, or casual. Bard also leverages Google Lens to analyze images uploaded with prompts.
- Anthropic Claude 2: A chatbot that can generate text, summarize content, and perform other tasks, Claude 2 can analyze texts of roughly 75,000 words, about the length of The Great Gatsby, and generate responses of more than 3,000 words. The model was built using a set of principles that serve as a sort of “constitution” for AI systems to make them more helpful, honest, and harmless.
The Rapid Advancement of AI Systems
These AI systems have been improving remarkably, including in how well they perform on assessments of human knowledge. OpenAI’s GPT-3.5, released in March 2022, only managed to score in the 10th percentile on the bar exam, but GPT-4.0 introduced a year later, made a significant leap, scoring in the 90th percentile.
These feats are awe-inspiring because OpenAI did not specifically train the system to take these exams; the AI could come up with the correct answers independently. Similarly, Google’s medical AI model substantially improved its performance on a U.S. Medical Licensing Examination practice test, with its accuracy rate jumping to 85 percent in March 2021 from 33 percent in December 2020.
The Potential of AI in Various Fields
These two examples prompt one to ask: if AI continues to improve so rapidly, what will these systems be able to achieve in the next few years? New studies challenge the assumption that AI-generated responses are stale or sterile. In the case of Google’s AI model, physicians preferred the AI’s long-form answers to those written by their fellow doctors, and nonmedical study participants rated the AI answers as more helpful.
Another study found that participants preferred a medical chatbot’s responses over a physician's ones and rated them significantly higher for quality and empathy. What will happen when empathetic AI is used in education?
The Growing Reasoning Capabilities of AI
Other studies have examined these models' reasoning capabilities. Microsoft researchers suggest that newer systems exhibit more general intelligence than previous AI models and are coming strikingly close to human-level performance.
While some observers question those conclusions, the AI systems display an increasing ability to generate coherent and contextually appropriate responses, make connections between different pieces of information, and engage in reasoning processes such as:
- Inference
- Education
- Analogy
How is AI Being Used in Education?
In May 2023, the U.S. Department of Education released a report titled Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations. The department had conducted listening sessions in 2022 with more than 700 people, including educators and parents, to gauge their views on AI.
The report noted that constituents believe that action is required now to get ahead of the expected increase of AI in education technology. They want to roll up their sleeves and start working together. People expressed anxiety about future potential risks with AI but also felt that AI may enable achieving educational priorities in better ways, at scale, and with lower costs.
AI could serve in several teaching and learning roles:
Instructional assistants
AI’s ability to conduct human-like conversations opens up possibilities for adaptive tutoring or instructional assistants that can help explain complex concepts to students. AI-based feedback systems can offer constructive critiques on student writing, which can help students fine-tune their writing skills.
Some research also suggests particular kinds of prompts can help children generate more fruitful questions about learning. AI models might also support customized learning for students with disabilities and provide translation for English language learners.
Teaching assistants
AI might tackle administrative tasks that keep teachers from investing more time with their peers or students. Early uses include automated routine tasks such as:
- Drafting lesson plans
- Creating differentiated materials
- Designing worksheets
- Developing quizzes
- Exploring ways of explaining complicated academic materials
AI can also provide educators with recommendations to meet student needs and help teachers reflect, plan, and improve their practice.
Parent assistants
Parents can use AI to generate letters requesting individualized education plan (IEP) services or to ask that a child be evaluated for gifted and talented programs. For parents choosing a school for their child, AI could:
- Serve as an administrative assistant
- Mapping out school options within driving distance of home
- Generating application timelines
- Compiling contact information and the likes
Generative AI can create bedtime stories with evolving plots tailored to a child’s interests.
Administrator assistants
Using generative AI, school administrators can draft various communications, including:
- Materials for parents
- Newsletters
- Other community-engagement documents
AI systems can also help with the complex tasks of organizing class or bus schedules and analyze complex data to identify patterns or needs. ChatGPT can perform sophisticated sentiment analysis useful for measuring school climate and other survey data.
How Will AI Change Grading?
One prominent example of AI's impact on education administration is the automation of grading tasks. Higher education institutions can benefit from AI solutions in grading and administrative tasks, such as reducing biases in testing systems and improving enrollment and admissions processes.
Educators spend considerable time grading homework and tests, a process that can be both time-consuming and labor-intensive. AI solutions can swiftly and accurately assess assignments, offering rapid grading and insightful recommendations to address learning gaps.
AI's Grading and Evaluating Student Work
Indeed, AI's role extends beyond simply grading exams based on predefined answer keys. These sophisticated systems can assess objective questions and analyze and evaluate more subjective assessments, such as essays.
By leveraging natural language processing and machine learning algorithms, AI can analyze written responses’ content, structure, and coherence, providing valuable insights into students’ comprehension and critical thinking skills.
The Growing Adoption of AI in Education
Though the potential is great, most teachers have yet to use these tools. A Morning Consult and EdChoice poll found that while 60 percent say they’ve heard about ChatGPT, only 14 percent have used it in their free time, and just 13 percent have used it at school. Most teachers and students will likely engage with generative AI not through the platforms but through AI capabilities embedded in software.
Instructional providers such as Khan Academy, Varsity Tutors, and DuoLingo are experimenting with GPT-4-powered tutors trained on datasets specific to these organizations to provide individualized learning support with additional guardrails to help protect students and enhance teachers' experiences.
AI-Powered Tools for Teachers and Students
Google’s Project Tailwind is experimenting with an AI notebook to analyze student notes, develop study questions, or provide tutoring support through a chat interface. These features could soon be available on Google Classroom, potentially reaching over half of all U.S. classrooms.
Brisk Teaching is one of the first companies to build a portfolio of AI services designed specifically for teachers:
- Differentiating content
- Drafting lesson plans
- Providing student feedback
- Serving as an AI assistant to streamline workflow
Ensuring Sound Instructional Practice
Curriculum and instruction materials providers might also include AI assistants for instant help and tutoring tailored to the companies’ products. One example is the edX Xpert, a ChatGPT-based learning assistant on the edX platform. It offers immediate, customized academic and customer support for online learners worldwide.
AI on Education Policy and Leadership
Regardless of the ways AI is used in classrooms, the fundamental task of policymakers and education leaders is to ensure that the technology is serving sound instructional practice. As Vicki Phillips, CEO of the National Center on Education and the Economy, wrote, “We should not only think about how technology can assist teachers and learners in improving what they’re doing now, but what it means for ensuring that new ways of teaching and learning flourish alongside the applications of AI.”
Opportunities and Challenges of AI in Higher Education
AI technologies are an increasingly viable way for institutions to save money and improve efficiency and workflows. The potential for AI to address more complex and higher-stakes tasks is growing. The Educause Horizon Report 2023 teaching and learning edition emphasizes this when reflecting on the growth of AI. Along with increased popularity, attitudes toward AI in higher education have gradually improved.
Educators and faculty have been exploring and experimenting with AI, discovering plenty of use cases where AI can be utilized. Respondents in a recent Educause QuickPoll highlighted four common areas of work in which generative AI can greatly benefit:
- Dreaming
- Drudgery
- Design
- Development
These use cases also apply to AI in general. AI's potential expands across many other educational segments, such as data analytics, productivity, and more.
AI Can Help Educators Get Creative
AI can be a wonderful assistant in curriculum development by generating:
- Study content
- Examples
- Lesson plans
- Presentations
- Assignments
- Assessment rubrics and more
For example, you can ask ChatGPT to develop a lesson plan based on the learning objectives you provide or create plenty of examples to support explanations of study concepts for students. Several AI tools can help with creating or editing multimedia study content:
- Images
- Videos
- Documents
Leveraging AI for Content Creation and Assessment
Ethan Mollick, Associate Professor at the Wharton School, wrote a practical article on how AI tools can be used differently in content creation. “AI is perfect for idea generation and can be extremely helpful in overcoming thought-blockers.” Educators can use AI to create many new ideas and suggestions on learning activities, quiz questions, assessment criteria, and more. Assessment is another area in which AI has proven to be extremely helpful. Three of several assessment aspects that AI can support:
- Drafting course rubrics
- Creating quiz questions
- Case study scenarios
Having AI generate initial ideas or the first draft of a lesson plan or course syllabus can save educators tremendous time throughout the course design process. At the same time, they explore novel ways of teaching and learning. Overall, using AI tools for content creation and idea generation can effectively improve educators' productivity, efficiency, and creativity.
AI Can Help Educators Promote Inclusivity and Accessibility
The promise of AI-enabled applications is that they might facilitate a transition from one-size-fits-all technology to scalable implementations of personalized learning experiences. Over the past two years, the abrupt online transition has prompted institutions to make many important realizations. Chief among these is the need to build an inclusive and accessible learning environment that addresses students’ diverse needs and mitigates learning barriers.
DEI Challenges in Higher Education
Diversity, equity, and inclusion (DEI) are among the key missions at many institutions to achieve quality education. This means that faculties need to ensure students with different learning backgrounds, needs, and preferences have access to meaningful, equitable learning opportunities and receive timely support and aid. Addressing these action points is undoubtedly challenging. Within a large student cohort and learners attending classes from various geographical locations, instructors face a large workload of time-consuming tasks such as:
- Grading exams
- Giving feedback
- Assigning groups for collaborative projects
Leveraging AI to Enhance DEI
The capacity of AI tools to take over these laborious tasks gives faculties space and time to engage with students and focus on more challenging pedagogical tasks like nurturing real-life skills, analyzing data, and student evaluation. Below are some approaches in which educators can leverage AI to create inclusive, accessible learning experiences. Provide instant, formative automated feedback on technical aspects of students’ writing, such as:
- Grammar
- Spelling
- Citation
- Content structure
This encourages students to actively review their work and improve while allowing instructors to tackle higher-order writing aspects like reasoning or argumentation.
Automated Feedback with FeedbackFruits
FeedbackFruits Automated Feedback is an example of a tool that harnesses AI to generate automatic feedback for writing. Answer lower-order questions from students, such as:
- Providing explanations
- Definitions
- Examples of certain study concepts
Unlike search engines, AI allows interaction with the tools by asking follow-up questions until a satisfactory answer has been reached. Not only do students practice asking questions and autonomy, but they also need to evaluate whether the answers are correct or not critically.
AI Can Help Increase Productivity and Efficiency
Besides teaching and learning tasks, AI can enhance many strategic and operational tasks in higher education. AI chatbots that can answer simple questions from students can be great assistants to IT help desks, which usually face many queries daily.
As these tools become more accurate and helpful, they can be adopted across faculties to help students access basic information and troubleshoot, allowing the IT team to investigate more serious cases. AI technology can gather and process large volumes of institutional data, thus generating holistic insights from these disparate data points.
Using AI to identify and respond to potential dropouts has significantly improved retention rates at Nova Southeastern University in the USA. Similarly, the University of Sydney implemented a comprehensive AI strategy that improved service and learning experiences for current and prospective students and staff members. These examples are just among many successful use cases of AI for data insights.
Existing Challenges
Regardless of the many benefits, AI presents institutions with specific ethical concerns to consider. Since AI is trained on data, the underlying data could carry implicit or explicit biases that result in discrimination against certain groups of people, such as minorities and women. This could reinforce existing societal inequalities and undermine the principles of equal opportunities and fairness in education.
Considerations in AI Adoption in Higher Education
It is easy for AI to create hallucinations or plausible facts, which are entirely false content that looks convincing. In other words, AI-generated content can be unreliable, and faculty and students need to establish the ability to evaluate these responses critically. There is also a growing concern over data protection and privacy. AI in higher education may require collecting and analyzing sensitive personal data, such as student academic performance and behavioral patterns.
Shifting Assessment Practices in the Age of AI
The institutions implementing AI systems must ensure that the data collected is used for its intended purpose and is not misused or shared with third parties without consent. The rise of AI has prompted institutions to depart from traditional assessment practices and switch to holistic evaluation practices that promote authenticity and lifelong learning. Such a transition indeed enhances the quality of assessment, yet it entails:
- Increased workload for faculties regarding communication with staff and students
- Implementation of different assessment methods
- Documentation of assessment results and such
Ethical Concerns in AI Integration
Integrating AI in higher education could result in job displacement for institutions, leading to ethical concerns regarding the impacts on the academic workforce. Addressing these ethical concerns while adopting AI in higher education is crucial to ensuring its responsible and equitable use.
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What are the Challenges of Using AI in a Classroom?
Generative AI can help students learn faster and more efficiently. But how much is too much? One of the main concerns about the adoption of generative AI is the risk of becoming too dependent on this technology. In essence, it’s the same debate as whether or to what extent calculators, computers, or smartphones should be allowed in the classroom.
Technology makes our lives easier. It can perform tasks in seconds that would take minutes, hours, or even days. In the case of generative AI, the number of use cases in educational settings is potentially unlimited, from writing essays and preparing presentations to summarizing readings and completing assignments.
Yet, let technology do everything for students. In that case, we risk losing the endeavor, frustration, and fulfillment that are an intrinsic part of any learning process and replacing them with:
- Lack of decision-making
- Laziness
- Frustration
Misinformation & Bias: Can We Trust AI?
Despite their impressive capabilities, generative AI models don’t understand the meaning of the language they process. They are just making complex calculations to create accurate content based on the data they have been trained with.
As a result, these models are prone to producing responses that are either factually incorrect, nonsensical, or even harmful, commonly known as LLM hallucinations. In other cases, generative AI models can be biased, resulting in:
- Unfair
- Discriminatory
- Stereotypically generated
If students (or even instructors) cannot identify inaccurate content, this could spark misinformation and discriminatory beliefs in the classroom.
Loss of Human Interaction: Will AI Change the Way We Relate to Each Other?
Education is the process of learning new knowledge and skills. Rather than individual, this is a collective process, especially in early childhood.
The classroom is the preferred setting for education because it fosters interaction among students, who spend considerable time learning and working together, getting to know each other, gossiping, and making friendships. The same applies to the student-teacher relationship, a bond based on trust and respect that is crucial for learning.
Generative AI promises a more effective, personalized education. This could also result in a more solitary, isolated education, as students would spend part of their time interacting with a virtual assistant instead of their educators and peers, which could jeopardize their social skills.
Academic Integrity: How Can We Maintain Trust in AI?
Academic integrity means being honest, fair, respectful, and responsible in your studies and academic work. Following the rise of generative AI, ensuring academic integrity has become challenging.
As already mentioned, generative AI is a new technology. There are still many uncertainties about how to regulate it, including in educational settings. As a result, academic institutions and education hardly ever have clear guidelines on the limitations and expectations for the use of generative AI.
Generative AI increases the risk that students may use it to submit work that is not their own. Addressing these risks is particularly difficult, as current technologies that detect AI-generated content are not accurate and reliable enough, which could result in unfair accusations of improper use of AI.
High Cost of Implementation: What Are the Financial Implications of AI?
Maintenance of technological devices can be costly. Integrating AI into the educational system will raise the school/school district's education budget. Those who cannot adapt to innovation will end up lagging.
Data Privacy Concerns: Can We Protect Sensitive Student Information?
Then, there are concerns surrounding data privacy and security in AI-driven education systems. As these systems collect and analyze vast amounts of student data, there is a risk of breaches or misuse of sensitive information, raising ethical and legal implications. The use of AI in grading and evaluation may raise questions about the fairness and validity of assessments, as AI algorithms may only accurately capture the nuances of student performance or learning outcomes.
AI has the potential to perpetuate biases present in the data used to train these systems, leading to unintended discrimination or reinforcement of existing inequalities within education systems.
Practical Tips for Using AI in the Classroom
Generative AI can be a potent tool for teachers and students. But before you bring it into the classroom, you must identify how it can help meet your goals.
With the powerful capabilities of generative AI, the number of use cases is potentially unlimited. While innovation in the classroom is always welcome, you should always be mindful of the challenges and limitations of using generative AI in your course. Fortunately, the research on the impact of generative AI in education is rapidly evolving. Conducting preliminary research is key to identifying successful use cases and anticipating potential pitfalls.
Just to give you a glimpse of the possibilities of generative AI in education, here is a list with some promising use cases:
- Developing critical thinking
- Creative writing and visualization
- Comparative analysis
- Language learning
- Historical role-play
Set Clear Guidelines for Using AI Tools in the Classroom
Before introducing generative AI in the classroom, you should fully know its capabilities and limitations. In this research phase, you should also check whether the technology aligns with your educational institution’s values, missions, and rules and how it can create added value in your course.
Transparency is important here to ensure everyone is on the same page. State the course’s generative AI policies, identifying situations where the use of generative AI is prohibited. When generative AI is allowed, you should explain how to document and credit content, providing recommendations and examples. These rules regarding documentation and attribution should also apply to you if you use generative AI while preparing my materials.
Monitor AI Tools in the Classroom
Generative AI is a powerful technology, but it needs to be bulletproof. It can be subject to hallucinations, or it may not work as you expected. Ideally, you should control what my students see on their screens. This may only be technologically feasible in some scenarios, and it could raise concerns about students' privacy.
Given the current state of generative AI, the most effective strategy to ensure correct use is to establish trusting relationships with students and design clear guidelines and policies.
Focus on Digital Literacy for Students and Teachers Alike
“Students will think and use this chatbot (Chat GPT) as if it is a know-all. That’s because it's a technology that is creating these things that sound really legitimate, they are going to assume that it is and take it at face value.” said Austin Ambrose, a middle school teacher in Idaho.
Every second, a new digital tool or technology is introduced, opening up new ways to access information and complete time-consuming tasks. The ability to appropriately evaluate, assess, and utilize technology and incoming information has emerged as a critical skill set for students. Accordingly, the curriculum must be adapted to help students develop this essential skill.
“Information literacy is the single most important skill to develop if we are to counter the misinformation that convincing AI-generated text can produce.” Nancy Gleeson.
Generative AI Ethical Considerations and Best Practices
As always occurs with emerging technologies, with power comes responsibility. Despite generative AI's unique capabilities, it’s important to consider its potential risks and ethical considerations.
Accommodate AI technology in the curriculum (teaching and learning). Instead of seeing AI technology as a threat, many educators view this intervention as a great opportunity to enhance and scale effective teaching. Nancy Gleeson, Associate Professor at New York University Abu Dhabi, reflected on the need for an AI-integrated curriculum:
“We need to embrace these tools and integrate them into policies. Lockdown browsers, strict dismissal policies, and forbidding the use of these platforms is not a sustainable way forward.”
When we held a webinar on learner-centered course design last month with Marine Roestel, Associate Director of Learning Systems Support at Central Michigan University, an attendee asked about the role of proctoring in ensuring the integrity of online courses. Marnie responded: “There are a lot of great tools and technology out there that serve as cheating deterrents. There is no foolproof system, unfortunately. If students are determined to find a way to cheat, they will find a way to cheat, unfortunately. Incorporating a variety of strategies into your assessments to deter cheating is probably the best method and setup.”
So how can institutions respond to the rise of AI technology? Marnie again gave an excellent remark: Rely on not just one tool but rely on several things:
- Creating tasks that are open-ended questions or essays is probably a great strategy
- Randomizing questions and randomizing answers so that no two students are getting presented with the same set of questions or in the same order that's another way.
- It just depends on the goals and achievements of a particular assessment.
- Consider maybe changing the activity entirely where students work together, collaborate, and learn from each other.
- Discuss a particular question, and arrive at the answer together.
Address Privacy and Data Security Concerns
Generative AI models are trained with vast amounts of data extracted indiscriminately from the Internet, often containing personal data. This can lead to issues and risks related to data privacy and security, especially if sensitive personal data are disclosed.
Transparency and Attribution
GenAI systems are black boxes, which implies that it is difficult to understand how they arrived at a particular response or what factors led to their decision-making. This can lead to serious attribution problems in education, as instructors won’t know the author of a given work, whether the student or generative AI.
Address Bias and Accuracy Issues
Biased GenAI tools can result in harmful outputs that often exacerbate discrimination and stereotypes, particularly against minority groups. AI researchers are working hard to address bias and improve the accuracy of generative AI models. To learn more about the subject, check out Understanding and Mitigating Bias in Large Language Models.
Plan for the Digital Divide
If wrongly implemented, generative AI threatens to widen the digital divide. If generative AI is set to become ubiquitous, every student should have equal access to this technology, meaning that all of them should have a digital device and internet connection. However, this is not the case.
A possible solution would be to entrust educational institutions to provide equal access, but this would require considerable resources that many centers, especially in poor areas, don’t have. This is a critical concern that should be addressed carefully. Otherwise, we risk widening the distance between the poor and the rich.
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Do We Need to Rethink Education in the Era of AI?
AI has already started to reshape the classroom. As with any new technology, there are challenges to address before teachers and students can fully benefit from its capabilities. To that end, an evolving education model is necessary to reflect the advancements AI can bring. This model must emphasize personalized learning, moving away from the traditional one-size-fits-all approach.
AI-Powered Personalized Learning
One key area AI can improve is understanding individual students’ strengths and weaknesses so teachers can better tailor their lessons to address knowledge gaps. The role of the teacher will change significantly in this new paradigm. Instead of being the sole source of information for students, teachers will act as facilitators who guide students through AI-assisted learning environments.
Priya Lakhani, CEO of CENTURY Tech, noted, “AI in education is capable of aiding personalized learning, providing intelligent tutoring, automating grading and translating languages in real-time. In other words, its impact is already being felt. … harness AI’s capacity to target specific students’ knowledge gaps. The platform is already developing tools to help tailor learning and allow teachers to move away from traditional one-size-fits-all methods.”
Preparing Future Generations for a World with AI
As generative AI and other technologies continue to evolve, it will be essential to prepare future generations for the workforce they will encounter as adults. This means teaching skills that AI cannot replicate so students can thrive as they pursue their careers. “Students should not be encouraged to cut their teeth on routine activities,” says King’s College London economics professor Dr. Daniel Susskind. “Instead, they should focus on tasks that foster communication, creativity, and interpersonal skills.”
As Susskind notes, these efforts will help future generations address the challenges of an economy transformed by artificial intelligence. Building on this notion, Ikhlaq Sidhu, dean of the IE School of Science & Technology, emphasizes that “educators can teach math or logic, but are often unable to teach behaviors or mindsets. … It’s clear that a shift in the education system is required if we are going to address this profound societal challenge.”
AI and the Transformation of Education
Experts agree that AI will transform education for the better. “When anything new is introduced into the education system, the number-one reaction is fear,” said American educator Esther Wojcicki during enlightED 2023. “School districts banned calculators when they were first introduced.” Despite scientific consensus that lecturing is the least effective teaching method, it is still the predominant approach utilized worldwide.
Both Wojcicki and fellow panelist Edo Segal, an AI proponent and founder of TouchCast, agreed that artificial intelligence is on the cusp of revolutionizing education for the better. “The medium of conversation is a hundred times more potent than just saying, ‘Here’s a book.’ Now, we can offer one-on-one tutoring to curious minds around any content base,” noted Segal.
Bringing Humanity to the Age of AI
The world’s first professor of AI & Work, Carl Benedikt Fray, stressed this is not the first time technology has profoundly impacted society. “There are still three key bottlenecks to automation: creativity, complex social interactions and navigating unstructured environments,” he said. Indeed, a common theme throughout the two-day event was the need to champion the use of AI through the lens of the humanities. It is the only way to ensure our transition to a more digital, tech-based world is empathetic and ethical. Consequently, focusing on human interaction and creativity rather than formulaic, routine tasks, much as Susskind proposed in his opening speech, will be vital to teaching moving forward.
Save Time While Grading Schoolwork with EssayGrader's Grading Software for Teachers
EssayGrader is an AI grading tool that helps teachers save time and get accurate and specific feedback to students. The tool is trusted by over 60,000 educators globally, and it’s easy to see why. With EssayGrader, what typically takes ten minutes for a teacher to do can be done in less than 30 seconds. The software even provides specific feedback on writing and can detect AI-written essays.
Boost Engagement with AI Grading Tools Like EssayGrader
EssayGrader can help boost engagement in class. No student likes to get back an essay with a grade but no feedback. This is especially true if the paper was written on a topic they didn’t care for and their interest had waned by the time they completed the assignment. Feedback from AI tools like EssayGrader can help get students engaged again.
Why? Because the specific writing feedback they receive will help them improve their writing for the next assignment. The next paper they write might just be on a topic they enjoy. Then, when they get their grade back, they will also get feedback from the AI tool that can help them improve their writing skills before turning in the next paper.
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