Generative AI Applications in Education: Transforming Teaching and Learning

Generative AI is rapidly changing the landscape of education, offering innovative tools and approaches that have the potential to transform how we teach, learn, and create. Generative AI refers to artificial intelligence that can generate novel content by utilizing existing text, audio files, or images. These AI models can produce high-quality outputs, supporting various tasks such as writing essays, generating code, creating images and art, composing recipes, producing music, and creating videos. As generative AI reaches a tipping point, it's essential to explore its applications in education to harness its potential effectively and ethically.

Most generative AI tools were not built for educational purposes, and advances in the technology have outpaced research and design of their application to learning contexts. There is an opportunity for research and design solutions to shape future applications of this emerging technology in an ethical, equitable, and safe manner.

The Rise of Generative AI in Education

Artificial intelligence itself is not new. Precursors to generative AI, like predictive AI, function by analyzing data to identify patterns, make predictions, or suggest outcomes. These forms of AI rely on predefined rules and logic, making them more rigid and less adaptive. Generative AI, or GenAI, refers to artificial intelligence models capable of producing new content, such as text, images, and even lesson plans, based on the data they are trained on.

Generative AI has rapidly evolved from a peripheral awareness to a priority focus for many higher education institutions. ChatGPT, a specific implementation of generative AI that creates conversational content, reached over one million users less than one week after it was made available as a research release in November 2022. It quickly became one of the most novel experiences and successful software releases in history, driving significant educational interest, large investments, product development, and generative AI solution evolution. These machine-learning neural network models can now leverage billions of learning parameters and are additionally trained on large datasets. ChatGPT's research release was trained on over 570 GB of data (from books and the internet) and was refined by human feedback. Widespread student use in 2023 inevitably raised questions about academic integrity. By the fall, as it became evident that all major technology vendors and education technology products would soon have some element of generative AI, acceptance of its use became more common.

Core Principles for Generative AI in Education

As educators adapt to these quickly evolving tools and observe how students are using them, many are formulating their own values around what this means for their classes. Cornell’s response to generative AI in teaching and learning is built around seven core principles:

The integrity of the faculty-student relation.
A commitment to experimentation, evidence, and learning from experience.
The centrality of faculty judgment and expertise in the classroom.
Responsiveness to real student needs and uses.
Recognition of both AI ‘goods’ and ‘harms’.
Respect for institutional and disciplinary heterogeneity.
The extension and renewal of core mission and values.

How Generative AI Affects Learning

Early responses to generative AI in teaching and learning were driven by experimentation. Often that experimentation was informed by an understanding of evidence-based teaching practices, but there was not yet any research to assess the impact of generative AI on learning itself. That research is beginning to appear, with more studies published every month. While some studies have demonstrated learning gains associated with student use of GenAI tools, especially in math or computer science courses, often those gains have proved ephemeral. Other studies of GenAI’s impact on writing are more concerning, showing that GenAI can lower the ‘friction’ of writing in concerning ways. Students who used GenAI for writing showed less brain activity, their writing showed more homogeneity, and the students themselves were less able to recall their written work when aided by GenAI. At the same time, research is now beginning to focus on particular ways in which GenAI might improve learning, whether by limiting its use to helping students engage in active engagement and practice, providing students with actionable and supportive feedback, and/or helping students reflect on their learning and metacognition. GenAI tools have also begun to introduce ‘study’ modes specifically designed to help students learn using these approaches.

Generative AI Literacy

While ChatGPT and other LLMs can assist learners in various tasks and activities, they cannot replace human creativity, judgment, ethics, or responsibility, all of which are essential for learning. Thus, the need for AI literacy is essential for students and faculty alike. Ethical generative AI literacies can be understood as the ability to understand, evaluate, and critically engage with generative AI technologies. Generative AI literacy includes skills such as recognizing when and how generative AI is used in various domains; assessing the reliability and validity of AI-generated outputs; identifying the ethical and social implications of AI applications; and creating and communicating with generative AI systems in ways that are appropriate to your course.

Applications of Generative AI in Education

Generative AI offers a wide array of applications in education, catering to the needs of students, teachers, and administrators alike.

For Students

Personalized Learning: AI can tailor content to individual student needs and learning styles, based on AI-driven analytics that give you insight into student performance and learning trends, helping students be more engaged and motivated. Generative AI excels at creating customized educational materials that match individual student needs, learning styles, and proficiency levels. The technology analyzes student performance data to generate appropriate content variations automatically. Speechify is a generative AI in education tool that helps students with learning disabilities such as dyslexia or ADHD by generating texts into speech notes.
Immediate Feedback: AI offers students instantaneous and detailed feedback on their work, helping them to see their strengths and weaknesses, enhancing understanding and learning outcomes.
Virtual Tutoring: Generative AI can be used to create virtual tutoring environments, where students can interact with a virtual tutor and receive real-time feedback and support. This can be especially helpful for students who may not have access to in-person tutoring. For example, TutorAI is trying to implement this kind of use of generative AI in education. Another application of generative AI in education for teaching purposes is the implementation of chatbots for tutoring.
Enhanced Problem-Solving: Generative AI in education can create engaging scenarios for problem-solving tasks or generate stories for writing exercises, helping students develop critical thinking skills.
Language Learning: Generative AI bridges language gaps by offering real-time translation, grammar correction, and pronunciation guidance, making education more inclusive for non-native speakers.
Gamified Learning Experiences: To enhance engagement, generative AI is used to gamify education by creating interactive quizzes and simulations, fostering interest and helping students retain knowledge through playful yet informative activities.

For Teachers

Content Creation: Through AI-powered platforms, teachers can create lessons, activities, assessments, discussion prompts, and presentations simply by providing a short prompt with keywords. Generative AI can assist in creating new teaching materials, such as questions for quizzes and exercises, or explanations and summaries of concepts. Image generation is another crucial capability of generative AI in education. Teachers may want to generate images with specific modifications that respond to particular course needs. NOLEJ offers an e-learning capsule that is AI-generated in only 3 minutes.
Personalized Lesson Plans: AI applications like ChatGPT have tremendous potential to help teachers perform their jobs more effectively by drastically reducing the time teachers spend creating lesson materials. By leveraging AI, teachers will be able to rapidly edit and refine lesson materials with natural language prompts. The system will also make suggestions for how to incorporate evidence-informed pedagogical strategies into the lesson materials.
Inclusive Lessons: AI has powerful tools that make previously inaccessible material available to students with special needs. Tools that offer text-to-speech, visual recognition, speech recognition, and more can help teachers adapt resources so that all students have an equal learning opportunity. Microsoft’s Immersive Reader, integrated into Office 365 Education, uses AI to provide reading support for students with learning differences, serving over 23 million students globally with features like syllable breakdown and picture dictionaries.
Time-Saving Tools: Generative AI can streamline administrative tasks such as grading, scheduling, communicating with parents, and managing student records, freeing teachers to do what they do best: teach.
AI-Assisted Collaborative Learning: Explore various approaches to AI-assisted collaborative learning and develop and evaluate sample uses.
Simulations Adaptive Learning Tool (SALT): Leverage generative AI capabilities to allow educators to create or adapt interactive content to meet learners’ needs.
Medical Conversational Virtual Agent (MAI-TA): Supplement in-person teaching for personalized exploratory learning.

For Administrators

Data-Driven Decision-Making: Generative AI offers powerful tools to help administrators make informed decisions to address challenges proactively, empowering schools to allocate resources, like staff and budget, where they are needed most.
Curriculum Design and Course Material Development: Educators spend considerable time creating course materials, lesson plans, and supporting resources. NOLEJ’s platform generates complete interactive learning modules within minutes, including video content, practice exercises, glossaries, and assessments. Teachers using Canva’s AI writing tools create lesson materials faster than traditional methods, with consistent formatting and age-appropriate language automatically applied.

Examples of Generative AI Tools in Education

Several generative AI tools are making their mark in education:

Khanmigo (Khan Academy): Built on GPT-4, Khanmigo acts as a tutor and teaching assistant, helping students solve problems step by step, encouraging critical thinking, and assisting teachers by drafting lesson plans.
Duolingo Max: This premium version of Duolingo integrates GPT-4 to create conversational practice scenarios and explain learners’ mistakes in natural language.
Quizlet Q-Chat: Quizlet has integrated GPT-4 into its platform to create an AI tutor that interacts with students conversationally, generating adaptive quizzes, explanations, and feedback in real-time.
Canva Magic Write: Teachers increasingly use Canva’s generative AI tools to create presentation slides, lesson outlines, and visual learning aids quickly.
Turnitin Draft Coach: Turnitin has developed AI tools to provide formative writing feedback, including grammar checks and structure suggestions.
Gradescope (by Turnitin): Uses AI to speed up grading workflows, especially for large classes, by identifying common errors and allowing teachers to apply feedback consistently.
Panorama Solara: Educators can access a secure chat interface with education best practices and district-specific customizations.

Addressing Challenges and Limitations

While generative AI offers numerous benefits, it also presents challenges and limitations that need to be addressed:

Privacy and Security Concerns: Data uploaded into most AI tools is used to train and refine the broader model, meaning that private information like student data is not actually private. It's crucial to partner with trusted AI providers that comply with data security and governance standards like SOC 2 and the Family Educational Rights and Privacy Act (FERPA).
Bias in AI Algorithms: Generative AI is trained on information created by fallible humans, so it too can make mistakes. Studies have shown significant bias in GPT against non-native English speakers. When assessing the use of non-native English speakers, it might be best not to use GPT detectors as assessment tools until the detectors have gone through a more comprehensive evaluation.
Reduced Human Interaction: Relying more and more on AI may reduce the teacher-to-student interactions and relationships and take away from the social-emotional aspects of learning.
High Implementation Costs: The cost of AI in education can vary greatly, depending on how schools want to use it, and implementing larger systems is likewise very expensive and is beyond the budgets of many schools, including those in underserved communities.
Academic Misconduct: Cheating and plagiarism are chief among the AI concerns raised by educators. Measures need to be in place to ensure that AI is not being used unethically.
Unpredictability and Inaccurate Information: AI is only as good as the algorithms it is based on. If the data it draws from is inaccurate or biased, then the information it creates will be inaccurate or biased. Students need to learn how to evaluate and think critically about the information they come across and not just accept it at face value.
"Hallucinations": False answers are sometimes generated as a result of models using "statistics" to pick the next word with no actual "understanding" of content.
Subpar training data: Data could be insufficient, obsolete, or contain sensitive information and biases, leading to biased, prohibited, or incorrect responses.
Copyright violations: Some models have been accused of using copyrighted data for training purposes, which is then reused without appropriate permission.
Deepfakes: Outputs generated by ChatGPT could appear realistic but may actually be fake content.

Strategies for Effective Integration

To effectively integrate generative AI into education, consider the following strategies:

Develop AI Literacy: Equip students and educators with the skills to understand, evaluate, and critically engage with generative AI technologies.
Establish Clear Policies: Discuss course policies and expectations around the use of AI tools, and clearly communicate when and in what ways use of generative AI tools are permitted - or not.
Promote Ethical Use: Implement measures to prevent academic misconduct and ensure that AI is used ethically.
Prioritize Human Interaction: Be aware of the potential for reduced human interaction and take care to identify and respond to the social and emotional needs of students.
Provide Training and Support: Ensure that educators receive adequate training on AI tools and their effective integration into classrooms.
Monitor and Evaluate: Implement a comprehensive system for monitoring and evaluating the effects of AI tools in your district.
Continually Gather Feedback: Implement a comprehensive system for monitoring and evaluating the effects of AI tools in your district.

Read also: AI's Impact on Learning

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