AI in Education: Innovating Responsibly in the Sun Prairie Area School District Part 2
6th-12th Grade Educators Professional Development Module
Fall 2024
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Welcome back, 6-12 educators! In today's professional development session, we are diving deeper into the world of Artificial Intelligence and its impact on teaching, learning, and responsible use within the Sun Prairie Area School District. Building on our initial discussions, we will explore advanced strategies to enhance your efficiency, integrate AI across various content areas, and uphold ethical standards. The AI Committee has made significant progress in drafting guidance and a framework for our vision and purpose statement on AI, which is currently under review by district and building leadership. We are excited to introduce you to Brisk Teaching, our district-supported AI tool designed to streamline your workload and elevate your teaching practices. Stay tuned for more updates this year as we continue to shape the future of AI in SPASD. Let's embark on this journey together and discover the transformative potential of AI in education!
Learning Outcomes
Learning Outcomes
Advanced AI Tools for Efficiency: Help teachers use AI tools to make their work easier, like handling admin tasks, personalizing student learning, and analyzing data.
AI in Different Subjects: Show teachers how to use AI in various subjects to make lessons more interesting and relevant for students.
Ethical AI Use: Teach teachers about using AI responsibly and ethically, so they can guide students to do the same.
Improving Teaching with AI: Train teachers to use AI in their teaching methods, focusing on personalized instruction, ongoing assessments, and interactive learning.
Using Brisk Teaching: Provide teachers with basic skills to use the district-supported AI tool, Brisk Teaching.
Reviewing New AI Guidance: Review and discuss our new AI guidance to ensure everyone understands and can implement it effectively.
Must Do!
Must Do!
You should complete this PD in groups designated by your building princpal. When you've completed the course you will come to an Exit Ticket designed to collect questions, feedback, and allow building leaders to ensure completion of this course.
Inclusion Activity
Inclusion Activity
Machine Learning isn't perfect... why would these pictures confuse a computer using Machine Learning?
Let's Review!
Let's Review!
Last May we walked through our initial AI training. Here were some of the take aways and FAQs based off your feedback, with the help of ChatGPT to summarize.
Summary of Key Reasons Educators Should Be Well-Versed in AI
Summary of Key Reasons Educators Should Be Well-Versed in AI
Enhancing Teaching and Learning:
AI improves instruction and learning experiences.
Enables personalized learning tailored to individual needs.
Assists in efficiently generating lesson plans, rubrics, and interactive content.
Efficiency and Productivity:
Automates administrative tasks, saving time on grading and lesson planning.
Reduces educators' mental load, allowing more focus on teaching.
Streamlines tasks, increasing overall work efficiency.
Understanding and Guiding Student Use:
Awareness of both positive and negative uses of AI by students.
Helps teachers guide ethical and responsible use of AI.
Crucial to teach students to use AI as a learning tool, not a shortcut.
Keeping Up with Technological Advancements:
Staying informed about AI ensures educators remain relevant.
Prepares students for a future where AI is integral.
Identifying and Preventing Misuse:
Recognize and address academic dishonesty related to AI.
Establish clear guidelines and consequences for AI misuse.
Equity and Accessibility:
Makes education more accessible, supporting students with disabilities or language barriers.
Address biases in AI to promote equity.
Future Preparedness:
Essential for preparing students for technological advancements.
Crucial for teaching necessary skills for a tech-driven world.
Safety and Privacy:
Ensures safe and ethical use of AI tools.
Educators need to teach students about digital integrity, privacy, and ethical implications.
Summary of FAQs on AI in SPASD with responses
Summary of FAQs on AI in SPASD with responses
Training:
Availability: Ongoing training throughout the school year and during professional development days.
Responsible AI Use: Teachers will be trained on best practices for teaching responsible and ethical AI use.
Guidelines:
Academic Dishonesty: Clear guidelines on AI-related academic dishonesty will be established, including definitions and consequences.
Student Access to AI: AI tools will not be accessible to students on district devices until a suitable product that meets data and privacy guidelines is found.
Citing AI Content: Guidelines for citing AI-generated content will be provided in the training.
Practical Considerations:
Integration in Subjects: Training will include practical examples of integrating AI into subjects like Math.
Addressing Concerns: Ongoing support and resources will address potential drawbacks, focusing on the responsible and ethical use of AI.
Engaging Families: Resources, listening sessions, and workshops will be offered to help families understand AI and support their children's use.
General Feedback:
Implementation Plan: The plan includes a timeline, guidelines, and ongoing support for integrating AI into classrooms.
Data Privacy and Security: The district will maintain strict data privacy and security measures to protect personal information and ensure ethical AI use.
Review of Definitions
Review of Definitions
Artificial Intelligence (AI):
AI refers to computer programs performing cognitive tasks like thinking and problem-solving. It enhances human information-processing, supports creativity, and speeds up routine tasks.
Machine Learning (ML):
ML is a subset of AI where computer algorithms learn from data and improve over time without being explicitly programmed for every scenario.
Supervised Learning: Uses labeled data to train programs, like using flashcards with questions and answers.
Unsupervised Learning: Uses unlabeled data to find patterns independently, useful for grouping and categorizing.
Reinforcement Learning: Programs learn through feedback, improving decisions with positive reinforcement.
Generative AI (genAI):
Generative AI creates new content (text, images) using a mix of supervised, unsupervised, and reinforcement learning. It's crucial in sectors like drug research, design, and fashion, helping create innovative solutions and personalized products.
Large Language Model (LLM):
LLMs are AI models trained on extensive text data, predicting the next words in a sequence to generate coherent responses in conversational AI tools.
Connection to Instructional Framework
Connection to Instructional Framework
Artificial Intelligence holds the promise of significantly enhancing our Instructional Framework by weaving its capabilities through every element: Experiences, Environment, and Equity. As we explore the integration of AI into our teaching practices, it offers innovative avenues to enrich classroom experiences, creating more interactive and personalized learning opportunities. In terms of environment, AI can streamline administrative tasks and optimize learning spaces in ways that support both teachers and students more effectively. Furthermore, AI's potential to analyze vast amounts of data can lead to more equitable educational outcomes by identifying and addressing individual student needs and disparities in educational access.
**Disclaimer**
**Disclaimer**
As we move through this training you will see the following disclaimer on the bottom of every page. This is an intentional reminder of how important it is to consider data privacy, accuracy, harm and bias when evaluating or utilizing AI tools or outputs.
YOU SHOULD NEVER ENTER PERSONALLY IDENTIFIABLE INFORMATION FOR YOU OR STUDENTS IN ANY AI TOOL.
YOU SHOULD NEVER ENTER PERSONALLY IDENTIFIABLE INFORMATION FOR YOU OR STUDENTS IN ANY AI TOOL.
YOU SHOULD ALWAYS ENSURE THAT THE INFORMATION IS ACCURATE, IS NOT HARMFUL, AND FREE FROM ANY BIAS.
YOU SHOULD ALWAYS ENSURE THAT THE INFORMATION IS ACCURATE, IS NOT HARMFUL, AND FREE FROM ANY BIAS.
Personally Identifiable Information (PII) is defined as any data that could potentially identify a specific individual. In the context of AI in education, this includes information such as students' names, addresses, email addresses, telephone numbers, dates of birth, social security numbers, and any other data that, alone or in combination with other data, can be used to identify, contact, or locate a person.
In the context of using AI in education, we must be vigilant about the outputs generated by these systems. Here's what we need to consider:
Bias: Sometimes, AI can show bias based on its data. This means it might favor or discriminate against certain groups (like different races, genders, economic statuses or other historically marginalized groups). It's important for teachers to notice and address if AI seems biased.
Accuracy: AI's answers or assessments need to be correct and trustworthy. Mistakes can happen if the data is wrong, the AI isn’t well-built, or it misinterprets information. Teachers should check if AI's outcomes make sense and confirm them with additional sources if necessary.
Harm: AI mistakes can be harmful, particularly in areas like student evaluations, counseling, or career advice. Harm can result from biases, inaccuracies, or privacy issues. Teachers should be cautious and ready to step in if AI's advice might harm a student.
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