How Will Gen AI Refine Evaluation & Personalize Learning: 2025
Could AI be a viable option for high school students, or could it also benefit younger learners in elementary school? This question lies at the heart of a growing conversation about the transformative potential of generative AI in education. However, not all students have the same level of one-on-one access to teachers, and it’s not always guaranteed that they receive the proper guidance at the right moment in their problem-solving journey. These challenges highlight the need for innovative solutions, and generative AI is stepping in to fill the gap.
Imagine a classroom where learning is no longer monotonous but personalized to each student’s unique needs, preferences, and pace. That’s the commitment of generative AI in education. This technology adapts to individual learning curves by leveraging its capabilities and enhancing outdated teaching methods into engaging, interactive, and dynamic experiences.
The generative AI in education market is projected to reach approximately USD 7,701.9 million by 2033, up from USD 299.8 million in 2023, with a compound annual growth rate (CAGR) of 39.5% from 2024 to 2033. As generative AI continues penetrating the education sector, it transforms traditional learning methods, making them more fun and personalized. Our article explores the fundamentals of generative AI, its impact on modern education, how it's applied to tailor learning to individual needs, the benefits it brings, and the future of generative AI in classrooms.
Fusion of AI and Education
Integrating artificial intelligence in education changes how students learn and interact with content. AI makes learning more personalized by meeting each student's unique needs and learning styles. Generative AI tools for personalized assessments can analyze student data, identifying strengths and weaknesses to offer individualized recommendations and AI-powered real-time student feedback.
For example, Three Newark schools in New Jersey offered to participate as test subjects in a study designed to differentiate the real-world applications of AI-powered tutoring bots.
Understanding Generative AI
Gen AI is a technology that can create original content, like text, images, videos, or even software code, based on a user’s prompt. It relies on deep learning models, algorithms designed to simulate how the human brain learns and makes decisions. These models understand patterns and relationships by analyzing massive amounts of data and generating relevant and creative content in response to user input.
Artificial intelligence in education has been a hot topic in the past decade. The rise of generative AI, especially with the inception of ChatGPT in 2022, has tossed the technology into the mainstream. Some companies are already using generative AI in at least one part of their workflow, and experts predict that by 2026, over 80% of organizations will have integrated generative AI tools for personalized assessments in their processes.
Workings of Generative AI in EdTech
Gen AI operates in three pivotal phases: training, tuning, and generation. Let’s explore phases and understand what makes them so important.
Phase 1: Training the Foundation Model
The first step in generative AI is training a foundation model. This extensive neural network serves as the base for different types of content generation, such as text, images, quizzes, and even video lecture summaries. To build this model, vast amounts of unstructured, unlabeled data about textbooks, online articles, and educational videos are processed. The AI learns by predicting the next element in a sequence (e.g., the next word in a sentence or pixel in an image). The training process involves complex calculations, requiring powerful GPUs and significant time and financial investment. The result of this step is a model that can generate content autonomously based on prompts given by the user.
Phase 2: Tuning for Specific Tasks
After the foundation model is developed, it must be fine-tuned for particular use cases. This phase refines the model’s general knowledge to perform tasks such as personalized tutoring, adaptive assessments, or content generation more accurately. Fine-tuning involves feeding the model-labeled data, such as question-answer pairs, to teach it the proper responses. Another method is reinforcement learning with human feedback (RLHF), where educators guide the AI by assessing and correcting its output, helping the model improve its accuracy and relevance over time.
Phase 3: Generation, Evaluation, and Retuning
In this phase, the generative AI creates content based on student, teacher, or educational platform input. For instance, personalized learning with generative AI can help in creating customized lesson plans and study materials. After developing content, developers and users evaluate the quality and relevance of the output. This ongoing evaluation process often leads to further model tuning to improve accuracy. Techniques like retrieval augmented generation (RAG) allow the model to access up-to-date information from external sources, ensuring its responses are current and relevant. The model’s performance is continually refined through regular updates. Feedback loops from both students and educators contribute to its ongoing refinement.
How will generative AI impact education?
Generative AI in education can independently create content, such as assignments, quizzes, and lesson plans. Students can receive materials ideally suited to their level of understanding, which makes learning much more engaging and effective. Instead of simply handing out information, generational AI adapts to student's needs and helps them grasp concepts more deeply.
But the impact isn't limited to students alone. Generative AI encourages teachers to rethink their roles. Instead of focusing purely on content delivery, educators can now focus on guiding students through a more dynamic, creative, and AI-enhanced simulation-based learning process. AI helps them create a learning environment where students' learning experience is unique. This shift in the teacher’s role requires them to be more facilitators of learning, coaching students through their own discoveries and helping them develop critical thinking skills.
How does generative AI improve evaluation design?
1) Automates assessments
Generative AI reduces the burden on human graders by automating the evaluation of assignments, essays, and exams. When integrated with Learning Management Systems (LMS), this technology streamlines grading, making it faster, more accurate, and more consistent across diverse student submissions. ML and NLP contribute to this task by analyzing student submissions, understanding context, and assessing quality based on predefined criteria like grammar, coherence, and argument strength. Gen AI grading systems learn from large datasets, such as past assignments and teacher feedback, improving their accuracy over time. While Gen AI in the education industry excels in grading objective assessments like multiple-choice tests, it has also shown the ability to evaluate subjective tasks like essays with accuracy comparable to human graders.
2) Personalizes learning
With generational AI, educators can align their tasks more closely with learning outcomes and professional expectations. They can customize assessments to individual student needs based on their strengths and areas of improvement. For example, allowing students to choose the format of their assessment, such as essays, multimedia presentations, or even case-based evaluations, can enhance engagement and ownership of their learning process. It can play an influential role in low-stakes assessments. With Gen AI, students can be encouraged to evaluate the value and appropriateness of using Gen AI in their future careers.
3) Enhances Learning Analytics
Gen AI can provide deeper insights into learning patterns and student performance. Tools like ChatGPT provide students with AI-powered real-time student feedback on their work, such as suggesting structure, grammar, and citation improvements. Many automated feedback tools use generative AI to enhance academic writing feedback, leaving no room for higher-order expert analysis. Moreover, universities are leveraging AI for more dynamic, data-driven decision-making.
4) Removes Human Bias
Human biases—such as affinity, attribution, and gender bias—can subtly influence grading. However, generational AI can help neutralize these biases by focusing purely on objective data rather than human tendencies. Generative AI tools for personalized assessments can ensure teachers and administrators evaluate students based on merit rather than unconscious biases. For instance, generational AI can analyze and modify admissions processes to assess applicants based on qualifications and skills. A powerful example of this is the use of AI in job placements, where platforms like Textio and Knockri remove biases related to gender, national origin, and appearance from job descriptions and interview processes.
How can schools, universities, and edtech companies use Gen AI?
1) Automating the Creation of Diverse Question Banks
The traditionally tedious process of creating question papers can be automated. Teachers no longer have to spend hours sorting through questions, deciding difficulty levels, and distributing marks. The Gen AI system can generate multiple, unique question papers for secure online exams and minimize the risk of question paper leaks. It enhances the quality of exams by sifting through vast pools of data and selecting the most relevant and high-quality questions.
2) Developing Realistic Simulations Using Synthetic Data
Gen AI can generate synthetic data that mimics real-world scenarios, which is especially valuable when accurate data is either difficult to obtain or too costly to collect. It builds complex models by learning from existing datasets to create AI-enhanced simulation-based learning processes that reflect intricate behaviours and systems. It enhances simulation accuracy by incorporating real-world insights to generate more realistic scenarios.
3) Facilitating Ideation and Course Design Development
With Gen AI, universities can explore diverse teaching methods and course structures that align with student needs. By analyzing current trends and student preferences, Gen AI can accelerate the creation of customized learning materials and refine educational resources, such as textbooks or digital tools. As a result, educators can rapidly innovate and adapt by making the content more accessible and engaging.
4) Creating Interactive Scenario-Based Learning Experiences
Educators can formulate adaptive role-play exercises that align with specific learning objectives. For example, a student in a negotiation class can role-play as a seller and adjust the strategy based on AI-generated prompts tailored to their experience level and background. AI provides a range of scenario options so students can select situations that challenge and help them grow. The AI also adapts the narrative as the role-play progresses, offers guidance, and summarizes critical decisions for further reflection.
5) Providing timely feedback for student improvement
While Gen AI can't replace educators' deep knowledge and understanding of their students, it can offer AI-powered real-time student feedback at scale. This type of feedback is especially beneficial in refining drafts, as it gives students an external perspective they can use to enhance their work. The AI feedback is personalized based on student input about their assignment and learning level. It can guide students to reassess their drafts, clarify their ideas, and address weaknesses before submission.
6) Exploring and Validating Multiple Problem-Solving Approaches
By leveraging its ability to analyze vast amounts of data and recognize patterns, Gen AI can propose multiple approaches to a given question or task, offering diverse perspectives and problem-solving methods. This process cultivates a deeper understanding of STEM concepts by presenting various ways to approach the same problem and ensuring students grasp complex subjects from different angles.
Upgrade Your Teaching methods with our personalized AI/ML Solutions
The integration of Gen AI in the education industry will push us to reimagine and invigorate old teaching styles. By focusing on developing critical skills in students and educators, we can prepare them for a future of generative AI in classrooms where this technology is deeply embedded in personal and professional life. As a leading AI/ML solutions provider for the education sector, Webelight Solutions Pvt. Ltd. recognizes educators' and institutions' pressure to deliver personalized learning with generative AI at scale, manage limited resources, and keep up with technological advancements. Our generative AI services create innovative content and personalized AI/ML solutions by leveraging advanced algorithms to generate new, valuable insights, designs, and responses.
