Innovation Island Playground

K-12 Playground

Enrollment Prediction

Higley Unified School District serves approximately 13,500 students across 16 schools. Predicting school enrollment is crucial.

According to local school administrators, simply getting static predictions can cost as much as $20,000, an amount that can be a significant burden for the school districts and does not have the flexibility to accommodate changing circumstances.

The ASU Cloud Innovation Center created an open-source prototype to predict future enrollment and integrate real time data, such as attendance data to assess enrollment predictions. This solution uses a wide pool of data from various sources and provides analytics with an easy to use dashboard. 

Open-source code: Download

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Generative Business Intelligence

For data analysis and visualization, many schools today still rely on pre-defined data models and dashboards that can be time-consuming to create and update and difficult for users to navigate and use. Using generative AI, both dashboard authors and consumers can streamline access to insights and visualizations with self-service, natural language queries.

Leveraging Amazon Q in QuickSight, users can pose questions using natural language, and the service will interpret the query, retrieve the relevant data, perform necessary calculations, and generate visualizations to provide insights. This approach eliminates the need for users to navigate through predefined dashboards or write complex SQL queries, making data exploration more accessible and efficient. Additionally, Amazon QuickSight can help users quickly generate executive summaries, narrative data stories, forecasts, and what-if scenarios.

In this demo, see how users can leverage Amazon Q in QuickSight to ask their own natural language questions of K-12 education data.

Intelligent Document Processing

Despite operating in a digital-first world, most K-12 institutions still struggle with manual processes that rely on paper forms and documents. Leveraging AI-powered Intelligent Document Processing (IDP), schools can significantly reduce the time and effort required for manual data entry and processing, streamlining tasks such as student registration, student cumulative folders, health records management, and more.

Services like Amazon Bedrock and Amazon Textract can accurately extract text, handwriting, and information from scanned documents and forms. Once extracted, this data can be processed in a variety of ways, including classification, analysis, summarization, redaction, human review, or integration with other systems and applications.

In this demo, see how Intelligent Document Processing can be used with documents required for school enrollment.

Student Assistant

Generative AI can provide personalized assistance and tailored feedback to students, enhancing the student learning experience and fostering independent problem-solving skills. Leveraging the power of artificial intelligence, generative AI can adapt to individual student needs and interests, providing customized explanations, examples, and exercises based on learning style and level of understanding.

With services like Amazon Bedrock, developers can easily create and deploy generative AI applications tailored to specific subjects and topics. These models can be augmented with existing data like educational content, textbooks, lecture notes, and student information, enabling them to provide more accurate and relevant assistance to students. With Amazon Bedrock, you have full control over the security and privacy of your data, and can implement guardrails to ensure safe and responsible AI use.

In this demo, see how some of the core features of Amazon Bedrock, like Agents, Knowledge Bases, and Guardrails, can be used for a student assistant.

District Chatbot

Schools are often flooded with requests for information from parents, employees, and community members. Generative AI chatbots can enhance the user experience and reduce burden on school staff by addressing frequently asked questions and automating common requests or workflows. These chatbots can provide a seamless and intuitive interface in multiple languages that lets district staff focus their efforts on more complex tasks that require human intervention.

Services and solutions like Amazon Bedrock, Amazon Lex, and QnABot on AWS can be used to implement conversational chatbots that are capable of interpreting and understanding user intent to provide relevant and accurate responses based on your unique organizational data and information. Combined with Amazon Connect, these chatbots can be embedded in various communication channels enabling users to interact through both voice- and text-based interfaces.

In this demo, see a sample FAQ chatbot embedded on a district website.

IT & Developer Productivity

K-12 technology teams have to manage overwhelming workloads with countless day-to-day tasks. Generative AI can play a crucial role in improving IT productivity and efficiency, assisting staff and developers write and test code, operate applications, review security issues, and optimize solutions.

Amazon Q Developer is an AI-powered coding companion that can integrate with popular IDEs and understand your unique codebase to help developers write, analyze, and improve code inside or outside of AWS. Amazon Q Developer can also help you understand, build, extend, and operate applications on AWS; you can ask questions about your own AWS resources, best practices, documentation, and more.

In this demo, see how Amazon Q Developer can be used to generate unit tests, review code, and remediate issues.

Employee Assistant

In today’s fast-paced education environment, teachers and staff can struggle to find the information they need quickly, hindering their ability to focus on providing quality education for students. Generative AI can help by providing faster access to organizational information, policies, and knowledge.

Utilizing services like Amazon Q and Amazon Bedrock, staff can engage in natural language interactions to ask questions and receive relevant information from the organization’s own knowledge bases. Amazon Q and Bedrock can be trained or augmented with organizational documents, policies, and procedures, allowing it to understand unique context and provide accurate and tailored responses. This ensures employees have access to the most up-to-date and compliant information and saves time that is better spent with students and colleagues.

In this demo, see how Amazon Q for Business can answer questions based on unique organizational knowledge like a parent student handbook, school calendar, and acceptable use policy.

IEP Assistant

Individualized Education Programs (IEPs) are crucial for ensuring that students with special needs receive the appropriate support and accommodations to thrive in their educational journey. However, creating and iterating on these IEPs can be a time-consuming and complex process, often requiring extensive collaboration among special education teams, parents, and other stakeholders. Generative AI can help streamline and enhance the IEP development process.

Services like Amazon Q and Amazon Bedrock can leverage historical IEP plans, pedagogical best practices, student information, and other relevant data sources. Using this knowledge, generative AI can assist special education teams analyze student needs and strengths, generate initial drafts of IEPs, evaluate existing IEPs, and recommend personalized goals, accommodations, and instructional strategies. This helps special education teams create, review, and refine high-quality IEPs more quickly and efficiently, freeing up more time for face-to-face student interaction.

In this demo, see how Amazon Q for Business can answer questions and provide recommendations based on past IEPs.

PDF Accessibility

Many organizations have document collections containing hundreds of thousands of PDF documents, many of which do not meet the Web Content Accessibility Guidelines (WCAG) 2.1 Level AA standards, making it difficult or impossible for individuals relying on assistive technologies to access those documents. To address this issue, the ASU Cloud Innovation Center developed an innovative, artificial intelligence-driven solution designed to remediate documents. Some readily available remediation solutions cost $3-$15 dollars per page, but with this solution, expenses for AWS services are less than a penny per page.

AWS services used:

  • Amazon S3: Used to securely store and manage the documents being remediated
  • AWS Lambda: Automates the file processing workflows
  • ECS (Fargate): Handles document processing efficiently
  • AWS Step Functions: Coordinates the various processes involved in splitting, processing, and merging documents
  • Amazon Bedrock: Generates alt text for images and charts using advanced LLM capabilities

This solution also integrates Adobe Auto-Tag APIs which are designed to automatically clean metadata, apply appropriate tags, and further enable document remediation. 

More information:

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My eCISO

The My eCISO project revolutionizes cybersecurity assessments by leveraging generative AI to assist organizations in strengthening their cyber resilience. Addressing the challenges posed by evolving cyber threats and the complexities of evaluating cybersecurity infrastructure, the Cal Poly Digital Transformation Hub (DxHub), powered by Amazon Web Services (AWS), developed an innovative AI-driven application. My eCISO automates the assessment process by conducting natural language interviews based on the NIST 1.1 framework, enabling organizations to accurately gauge their security posture and implement necessary safeguards. This tool significantly enhances operational efficiency and provides a robust, user-friendly approach to maintaining cybersecurity compliance.

Learn more:

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