How the AI for Teaching & Learning Framework on AWS is transforming the student and teacher experience

The landscape of higher education is undergoing a profound transformation driven by generative AI, creating unprecedented opportunities for enhanced teaching and learning experiences. Through strategic partnerships with HAQM Web Services (AWS), generative AI competent education partners and education institutions are implementing innovative solutions based on the AI for Teaching & Learning Framework on AWS to address their specific educational challenges and opportunities. These innovations—including AI-powered content generation tools, personalized learning assistants, or automated assessment solutions—are designed to improve the learning experience and outcomes for the entire education community.

A partnership-driven approach to educational innovation

Educational institutions today face mounting pressure to deliver personalized, engaging learning experiences while managing faculty workloads and improving operational efficiency. They are focusing on improving efficiency, expanding their reach, and enhancing student success and career readiness. At the same time, educators are seeking ways to enhance their curriculum and engage students more effectively, while balancing their workloads on creating consistent course materials, marking criteria, and actionable feedback—leaving little time for teaching and research.

The entry of Generation Z (born 1995-2009) and Generation Alpha (born 2010-2025) into the education system requires an approach that matches their technological fluency. Schools are implementing adaptive learning technologies and interactive digital classrooms to engage students effectively. Research indicates that today’s students increasingly expect personalized learning experiences and consider digital capabilities when selecting institutions. According to the 2022 Higher Education Digital Experience Report by Great State, 50 percent of students consider a university’s digital experience as a key factor in their choice of where to study (Great State, 2022). Further, research from the UK Department for Education indicates approximately 50 percent of students of higher education are using ChatGPT to support their academic work. These findings suggest that integrating generative AI in education is becoming increasingly important for institutions aiming to meet student expectations and stay competitive.

This widespread adoption of AI tools by students has created both opportunities and challenges for educational institutions. While these tools offer potential for enhanced learning experiences, they also necessitate a fundamental rethinking of traditional teaching methods and assessment approaches. Educational institutions must now consider how to effectively incorporate these tools into their teaching practices while maintaining academic integrity and ensuring equitable access to technology-enhanced learning.

Institutions are navigating a significant cultural shift, balancing traditional academic values with the integration of AI as a legitimate information source in academia. This shift is accompanied by a growing need for clear metrics to evaluate teaching impact, student engagement, and overall teaching and learning effectiveness. These multifaceted challenges present opportunities for innovative solutions that can enhance all aspects of higher education.

Transforming the teaching and learning Journey with the AI for Teaching & Learning Framework

To help institutions navigate this transformation successfully, AWS has been developing the AI for Teaching & Learning Framework on AWS, along with a reference architecture and a series of assets and modules. AWS is collaborating with generative AI-competent and education accredited partners to create comprehensive solutions aligned to that framework. The AI for Teaching & Learning Framework on AWS leverages AWS’s generative AI capabilities to empower educators, engage students, and enable institutions to harness the full potential of AI in education.

The framework’s modular approach allows AWS Partners to create solutions that support the entire teaching and learning lifecycle, ensuring a comprehensive transformation of the educational experience. It is designed around a three-phase cycle for educators that enhances the entire teaching and learning experience.

Lecture preparation:

- For educators: This phase utilizes generative AI for research, content generation, syllabus creation, and customization of content, all with built-in guardrails to ensure quality and relevance. It also includes reference generation and publishing of materials.
- Student benefits: Students receive well-structured, up-to-date, and personalized course materials, enhancing their preparedness and improving overall learning outcomes.

Lecture delivery:

- For educators: This phase utilizes generative AI to provide real-time transcription, translation, summarization, and Q&A creation, making content more accessible and interactive. It also supports asynchronous delivery and ad-hoc material generation.
- Student benefits: Students enjoy more accessible and interactive content, with real-time support for diverse learning needs. This includes language translation for international students, transcriptions for those with hearing impairments, and interactive Q&A sessions for enhanced engagement.

Lecture analysis:

- For educators: Post-lecture, the system collects feedback, analyzes data, and facilitates content review, enabling continuous improvement of teaching materials and methods. This includes assessment marking, feedback analysis, performance review, identifying trends, and implementing lecture improvements.
- Student benefits: Students receive more targeted and effective instruction as the system adapts to their collective and individual learning patterns. They also benefit from faster, more consistent grading and personalized feedback.

Figure 1. AI for Teaching & Learning Framework lifecycle.

Throughout this cycle, students actively engage in a comprehensive learning experience that extends beyond the traditional classroom settings. AI-powered tools enhance both synchronous classroom learning and asynchronous non-classroom learning. In the classroom, real-time features—like transcription, translation, summarization, quiz generation, and content chat— support synchronous learning. For asynchronous learning, AI assists with easily digestible format conversion, providing references, and facilitating Q&A and feedback sessions monitoring and adapting to the progress of the student. These AI-driven tools work in tandem to make content more accessible, interactive, and tailored to individual student needs. This cyclical process puts educators at the center, providing them with AI-powered tools to continuously enhance their teaching methods and materials. Simultaneously, it supports students in their learning journeys, both in and out of the classroom, creating a more engaging, personalized, and effective educational experience.

By integrating seamlessly into existing workflows and addressing both teaching and learning aspects, these AWS-powered solutions aim to address the challenges faced by educators, students, and institutions in today’s rapidly evolving educational landscape.

AI for Teaching & Learning Framework components

At its core, the AI for Teaching & Learning Framework is a modular approach that combines robust infrastructure, partner offerings, and AWS managed services, streamlining the development, operation, and scaling of AI applications tailored specifically for educational environments.

The framework’s strength lies in its collection of reusable design primitives and capabilities. These AI-driven building blocks enable rapid development and deployment of AI applications for common educational use cases, from personalized learning paths to AI learning assistants. By leveraging these generative AI-powered primitives, institutions can quickly implement a wide array of AI-powered educational solutions, including intelligent tutoring assistants and AI grading tools, without having to build each component from scratch.

Figure 2. AI for Teaching & Learning Framework components.

AI for Teaching & Learning Framework reference architecture

This architecture serves as a blueprint for implementing AI-powered educational solutions for teaching and learning, showcasing how various AWS services and partner technologies can work together to create a robust, scalable, and secure platform for enhancing the teaching and learning experience.

Figure 3. AI for Teaching & Learning Framework on AWS reference architecture.

At the core of the reference architecture is AWS’s powerful generative AI ecosystem, anchored by HAQM Bedrock. Bedrock provides access to state-of-the-art foundation models (such as Claude, Nova, and Llama) while providing essential guardrails and governance capabilities critical for educational environments. Through this fully managed service, educational institutions can build and scale generative AI applications without managing complex infrastructure. The architecture leverages HAQM Bedrock Knowledge Bases to connect foundation models with institutional data sources, providing context-aware responses grounded in educational content. Additionally, HAQM Bedrock Agents enables the creation of sophisticated AI teaching assistants that can perform complex tasks—from answering student queries to helping instructors grade assignments—by orchestrating foundation models, tools, and data sources into cohesive educational workflows.

For institutions requiring custom model development, HAQM SageMaker AI offers comprehensive machine learning capabilities for training models tailored to specific educational domains. The architecture implements a serverless approach with services such AWS Lambda and AWS StepFunctions for business logic, delivering responsive performance while maintaining cost efficiency through pay-as-you-go pricing—particularly valuable for educational institutions with fluctuating workloads throughout academic cycles. These services integrate with front-end applications through GraphQL APIs powered by AWS AppSync and REST APIs managed by HAQM API Gateway, providing flexible interfaces for diverse educational tools such Learning Management Systems (LMS).

The framework’s distinctive strength lies in its RAG (Retrieval Augmented Generation) capabilities, offering diverse vector stores in HAQM OpenSearch Serverless for high-performance semantic search, HAQM Neptune for graph-based knowledge representation, or HAQM Aurora for relational data with vector capabilities. These work alongside specialized AI services like HAQM Textract, HAQM Transcribe, HAQM Rekognition, and HAQM Polly to process and understand diverse educational content types—from lecture recordings to course materials.

What sets AWS apart is how these services work together to create a secure, scalable, and cost-effective solution specifically designed for education’s unique needs. The platform’s comprehensive monitoring and analytics capabilities through HAQM CloudWatch and HAQM QuickSight provide institutions with deep insights into usage patterns and learning outcomes. Data management through AWS Glue and HAQM Bedrock Data Automation creates educational data pipelines that automatically generate useful insights from unstructured multimodal content such as documents, images, audio, and video—particularly valuable for processing diverse educational materials. Moreover, AWS approach to AI governance, with built-in guardrails through HAQM Bedrock Guardrails and comprehensive security features, addresses the critical concerns of data privacy and responsible AI use in educational settings—a crucial differentiator for institutions implementing AI solutions. This integrated ecosystem empowers educational institutions to focus on pedagogical innovation rather than infrastructure management, while maintaining complete control over their data and AI implementations.

Success through partner innovation

Our partners are already creating impressive solutions using this framework, demonstrating the power of collaboration in educational innovation. A prime example is EDT&Partners, which has developed Lecture. Lecture enables institutions to implement AI-enhanced teaching and learning experiences. This solution showcases how partners can customize the framework to meet specific institutional needs while maintaining security, compliance, and academic integrity. The success of this implementation demonstrates the framework’s ability to support partners in creating solutions that truly transform the educational experience.

Real-world impact and early success stories

Early adopters working with our partners are experiencing significant positive outcomes in their educational environments. Institutions report substantial reductions in time spent on administrative tasks, allowing educators to focus more on student interaction and engagement. Find out more about how University Luxembourg has been implementing the AI for Teaching & Learning Framework on AWS in this blog.

Furthermore, partners have successfully implemented solutions that improve accessibility for diverse learner populations, ensuring that educational content is available to all students regardless of their learning style or physical location. These implementations demonstrate the framework’s ability to support inclusive education at scale.

Conclusion

The AI for Teaching & Learning Framework on AWS represents an innovative approach to enhancing higher education, offering new ways to support teaching and learning. This framework aims to augment traditional lectures with AI-driven tools that benefit educators, students, and institutions alike.

For educators, it provides assistance in content creation, real-time assessment, and data-driven improvements. Students can access more personalized learning experiences, with on-demand support and adaptive tools. Universities implementing this technology may see improvements in student engagement and educational outcomes. Beyond the classroom, the framework helps familiarize students with AI technologies they’re likely to encounter in future workplaces. This exposure can contribute to developing both technical skills and critical thinking abilities necessary for working alongside AI systems.

As AI continues to evolve, its applications in education will likely expand. AWS and its partners are committed to ongoing innovation in this field, working closely with educational institutions to develop solutions that address their specific needs and challenges. The AI for Teaching & Learning Framework is one step in the ongoing digital transformation of education. By combining AI capabilities with human expertise, it aims to create enhanced learning experiences that can better prepare students for an increasingly technology-driven world.

To discover how the AI for Teaching & Learning Framework can enhance your institution’s educational approach, contact your AWS account team or our education specialists today. Explore with us the potential of AI in education, where technology complements human expertise to create innovative learning experiences.

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Contributing authors: Hannah Brassord, Maryclaire Abowd, Michael Wittel, Chris Mathews, Andrew Proctor

AWS Public Sector Blog