MORE EVENTS
Leadership
Exchange
Solutions
Summit
DigCit
Connect
Change display time — Currently: Mountain Daylight Time (MDT) (Event time)

AI in the Classroom for Educators: A Quantum Leap for Educational Equity

,
Colorado Convention Center, Mile High Ballroom 3A

Explore and create: Exploratory Creation lab
Preregistration Required
Save to My Favorites

Presenters

Photo
Educator
Chantilly High School
ISTE Certified Educator
Courtney Marshall's journey from business leadership to educational advocacy exemplifies transformative thinking. At the University of Florida, her advanced studies apply a quantum lens to AI in education, seeking innovative solutions for dynamic learning. Her leadership in Ohio's Telecommunications Educator Boot Camp underscores her commitment to digital literacy and bridging technological divides. Embracing diverse learners, Marshall advocates for a tech-enriched, human-centered education. Aware of technology's biases, she is pivotal in steering education towards a future where AI empowers rather than excludes. She introduces strategies for dynamic learning through AI literacy and hands-on activities, enabling educators to create cross-disciplinary, project-based curricula.
Photo
Coordinator of Instructional Technology
Robstown ISD
@RachelMedrano14
ISTE Certified Educator
I have the pleasure of being the Coordinator of Instructional Technology for Robstown ISD. I truly love seeing what the power of technology can do for both our teachers and students. I am proud to be a Google Applied Digital Skills Ambassador, Curipod Curiosity Champion, edlio Super User, Google Certified Trainer, GoGuardian Certified Coach, Kami Hero, Pear Deck Certified Coach, Quizizz Ambassador, and Wakelet Ambassador.

Session description

Explore a groundbreaking approach to education through the lens of quantum mechanics and artificial intelligence. Learn how AI can serve as a co-teacher to personalize learning and bridge educational gaps. Engage in hands-on activities to design AI-integrated lesson plans and activities. Walk away with an AI partnership.

Purpose & objective

Purpose:
The session is designed to empower K-12 educators with the knowledge and tools to integrate Artificial Intelligence into their classrooms effectively. We aim to instigate a transformative shift towards educational paradigms that are adaptive, equitable, and interconnected. For example, AI can make education more adaptive by enabling real-time feedback loops and personalized learning paths. It can also make education equitable by providing additional resources and individualized support for students who may otherwise be left behind. Furthermore, AI's data-driven insights can facilitate interconnected learning environments where curriculum, extracurricular activities, and parental engagement are optimally aligned.

Objectives:
1. Understanding AI Literacy: Educators will become familiar with an array of emerging AI tools designed to support different aspects of teaching and learning. We will showcase various AI tools that assist with bell ringers, prompt engineering, AI image generation, lesson planning, differentiated instruction, role-playing scenarios, designing educational materials.

2. Hands-On Experience with Emerging Tools: Participants will undergo a hands-on lab session where they'll actively interact with these cutting-edge AI tools. Some of the tools we will explore include Adobe, Canva, Claude, Diffit.ai, Chat GPT, Gemini, and Magic School AI.

3. Exploring Distributed Cognition: Educators will explore how these AI tools, individually and collectively, can extend the cognitive reach of both teachers and students, thereby enhancing the overall learning environment.

4. Quantum-Thinking in Education: Participants will engage in discussions on applying quantum mechanics metaphors to educational models, allowing for a more holistic and interconnected framework.

5. Collaborative Lesson Planning with AI: Working in content-specific groups, educators will employ these AI tools to collaboratively design a multifaceted lesson plan that leverages the capabilities of each tool for optimal student engagement and learning outcomes.

6. Feedback and Reflection: Educators will share their AI-integrated lesson plans with peers through an AI-facilitated peer review system, providing opportunities for insights and iterative improvement.

By the end of the session, participants will not only have a comprehensive understanding of how to implement these AI tools in their classrooms practically but will also appreciate the theoretical underpinnings that make such integration both effective and transformative.

More [+]

Outline

I. Introduction (10 minutes)
Purpose: To set the context and provide an overview of the session's objectives.
Content: Briefly introduce the transformative potential of AI in K-12 education.
Process: Short lecture using AI to create engaging bell ringers
Engagement Tactics: Quick poll on familiarity with AI tools, and a brief outline of the session's flow.

II. Understanding AI Literacy (5 minutes)
Objective: Introduction to emerging AI tools
Content: Brief overviews of tools including but not limited to Adobe, Canva, ChatGPT, Claude, Diffit.ai, Gemini, and MagicSchool AI.
Process: Slides and discussion
Engagement Tactics: Interactive Q&A

III. Exploring Distributed Cognition & Quantum-Thinking (10 minutes)
-Objectives 3 & 4: Theoretical underpinnings.
-Content: Discussion on extending the cognitive reach and applying quantum mechanics metaphors in education about being linear regardless of technology.
Process: Group discussion
Engagement Tactics: Small-group brainstorming and sharing.

IV. Guided Introduction/Practice (20 minutes)
Objective: Practical experience with AI tools.
Content & Activities
- Design an AI-assisted material (4 mins)
- Create bell ringers (4 mins)
- Draft lesson outlines (4 mins)
- Simulate a Q&A session (4 mins)
- Differentiate a lesson (4 mins)

V: Hands on Lab - Attendee Led
Free exploration based on educators' needs (10 mins)
Engagement Tactics: Choose a few tools to focus their attention on and explore

VI. Feedback and Reflection/Wrap-Up (5 minutes)
Objective: Share out the biggest takeaway from hands-on activity
Content: Attendees' feedback
Process: Reflection.
Engagement Tactics: Q&A

More [+]

Supporting research

My AI Lit review sources that helped identify the PD teachers needed.

Antonenko, P., & Abramowitz, B. (2023). In-service teachers’ (mis)conceptions of artificial intelligence in K-12 science education. Journal of Research on Technology in Education, 55(1), 64–78. https://doi.org/10.1080/15391523.2022.2119450

Bransford, J. D., Brown, A. L., & Cocking, R. R. (2000). How people learn: Brain, mind, experience, and school. National Academy Press.
du Boulay, J. B. (2016). Artificial Intelligence as an Effective Classroom Assistant. IEEE Intelligent Systems, 31, 76-81.

Casal-Otero, L., Catala, A., Fernández-Morante, C., Taboada, M., Cebreiro, B., & Barro, S. (2023). AI literacy in K-12: A systematic literature review. International Journal of STEM Education, 10(1), 29. https://doi.org/10.1186/s40594-023-00418-7

Celik, I., Link to external site, this link will open in a new window, Dindar, M., Muukkonen, H., & Järvelä, S. (2022). The Promises and Challenges of Artificial Intelligence for Teachers: A Systematic Review of Research. TechTrends, 66(4), 616–630. https://doi.org/10.1007/s11528- 022-00715-y

Chen, L., Chen, P., & Lin, Z. (2020). Artificial Intelligence in Education: A Review. IEEE Access, 8, 75264–75278. https://doi.org/10.1109/ACCESS.2020.2988510

Cope, B., Kalantzis, M., & Searsmith, D. (2021). Artificial intelligence for education: Knowledge and its assessment in AI-enabled learning ecologies. Educational Philosophy and Theory, 53(12), 1229–1245. https://doi.org/10.1080/00131857.2020.1728732

Eguchi, A. (2021). Contextualizing AI Education for K-12 Students to Enhance Their Learning of AI Literacy Through Culturally Responsive Approaches. Künstliche Intelligenz.
What does the literature say about AI in K-12 education: The implementations and outcomes?

Fredricks, J. A., Blumenfeld, P. C., & Paris, A. H. (2004). School Engagement: Potential of the Concept, State of the Evidence. Review of Educational Research, 74(1), 59–109.

Heffernan, N. T., & Heffernan, C. L. (2014). The ASSISTments Ecosystem: Building a Platform that Brings Scientists and Teachers Together for Minimally Invasive Research on Human Learning and Teaching. International Journal of Artificial Intelligence in Education, 24(4), 470–497. https://doi.org/10.1007/s40593-014-0024-x

Heintz, F. (2021). Three interviews about k-12 AI education in America, Europe, and Singapore. KI Kunstliche Intelligenz, 35(2), 233–237. https://doi.org/10.1007/s13218-021-00730-w

Holmes, W., Bialik, M., & Fadel, C. (2019). Artificial intelligence in education: Promises and Implications for Teaching and Learning. Center for Curriculum Redesign.
Hutchins, E. (1995). How a cockpit remembers its speeds. Cognitive Science, 19(3), 265–288. Ji, H., Han, I., & Ko, Y. (2023). A systematic review of conversational AI in language education: Focusing on the collaboration with human teachers. Journal of Research on Technology in Education, 55(1), 48–63. https://doi.org/10.1080/15391523.2022.2142873

Johnson, S. M., Kraft, M. A., & Papay, J. P. (2012). How Context Matters in High-Need Schools: The Effects of Teachers’ Working Conditions on Their Professional Satisfaction and Their Students’ Achievement. Teachers College Record: The Voice of Scholarship in Education, 114(10), 1–39. https://doi.org/10.1177/016146811211401004

Kandlhofer, M., Steinbauer, G., Hirschmugl-Gaisch, S., & Huber, P. (2016). Artificial intelligence and computer science in education: From kindergarten to university. 2016 IEEE Frontiers in Education Conference (FIE), 1–9. https://doi.org/10.1109/FIE.2016.7757570

Kim, J., Lee, H., Cho, Y. H., & Link to external site, this link will open in a new window. (2022). Learning design to support student-AI collaboration: Perspectives of leading teachers for AI in
What does the literature say about AI in K-12 education: The implementations and outcomes?
education. Education and Information Technologies, 27(5), 6069–6104.
https://doi.org/10.1007/s10639-021-10831-6

Knezek, G., & Christensen, R. (2016). Extending the Will, Skill, Tool Model of Technology Integration: Adding Pedagogy as a New Model Construct. Journal of Computing in Higher Education, 28(3), 307–325. https://doi.org/10.1007/s12528-016-9120-2

Kong, S.-C., Cheung, W.M.-Y., & Zhang, G. (2021). Evaluation of an artificial intelligence literacy course for university students with diverse study backgrounds. Computers in Human Behavior, 115, 106552. https://doi.org/10.1016/j.chb.2020.106552

Kong, S.-C., Cheung, W. M.-Y., & Tsang, O. (2023). Evaluating an artificial intelligence literacy programme for empowering and developing concepts, literacy and ethical awareness in senior secondary students. Education and Information Technologies, 28(4), 4703–4724.

Kuleto, V., Ilic, M., Bucea-Manea-Țoniş, R., Živanović, Z., & Păun, D. (2022). K-12 MODERN SCHOOLS IN SERBIA: EXPLORATORY RESEARCH REGARDING TEACHERS GENUINE KNOWLEDGE AND PERCEPTION OF AI-BASED OPPORTUNITIES AND CHALLENGES IN EDUCATION. Journal of Economic Development, Environment and People, 11(2), Article 2. https://doi.org/10.26458/jedep.v11i2.762

Lee, S., Noh, H., Lee, J., Lee, K., Lee, G. G., Sagong, S., & Kim, M. (2011). On the effectiveness of Robot-Assisted Language Learning. ReCALL, 23(1), 25–58.
https://doi.org/10.1017/S0958344010000273

Long, D., & Magerko, B. (2020). What is AI Literacy? Competencies and Design Considerations. Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems, 1–16. https://doi.org/10.1145/3313831.3376727
What does the literature say about AI in K-12 education: The implementations and outcomes?

Luckin, R., & Cukurova, M. (2019). Designing educational technologies in the age of AI: A learning sciences-driven approach. British Journal of Educational Technology, 50(6), 2824–2838. https://doi.org/10.1111/bjet.12861

Luckin, R., Holmes, W., & Forcier, L. B. (2016). An argument for AI in Education. Mayer, R. E. (2001). Multimedia learning. Cambridge University Press.
doi:10.1017/CBO9780511811678

Miao, F., Holmes, W., Huang, R., & Zhang, H. (2021). AI and education: A guidance for policymakers. UNESCO Publishing.

Ng, D. T. K., Leung, J. K. L., Su, J., Ng, R. C. W., & Chu, S. K. W. (2023). Teachers’ AI digital competencies and twenty-first-century skills in the post-pandemic world. Educational Technology Research and Development, 71(1), 137–161. https://doi.org/10.1007/s11423-023- 10203-6

Polak, S., Schiavo, G., & Zancanaro, M. (2022). Teachers’ Perspective on Artificial Intelligence Education: An Initial Investigation. CHI Conference on Human Factors in Computing Systems Extended Abstracts, 1–7. https://doi.org/10.1145/3491101.3519866

Seufert, S., Guggemos, J., & Sailer, M. (2020). Technology-related knowledge, skills, and attitudes of pre-and in-service teachers: The current situation and emerging trends. Computers in Human Behavior, 115, 106552. https://doi.org/10.1016/j.chb.2020.106552

Tedre, M., Toivonen, T., Kahila, J., Vartiainen, H., & Valtonen, T. (2021). Teaching machine learning in K–12 classrooms: Pedagogical and technological trajectories for artificial intelligence education. IEEE Access, 9, 110558–110572. https://doi.org/10.1109/ACCESS.2021.3097962

Tierney, P., & Farmer, S. M. (2011). Creative self-efficacy development and creative achievement. High Ability Studies, 22(2), 123–141.
What does the literature say about AI in K-12 education: The implementations and outcomes?

Timms, M. J. (2016). Letting Artificial Intelligence in Education Out of the Box: Educational Cobots and Smart Classrooms. International Journal of Artificial Intelligence in Education, 26(2), 701– 712. https://doi.org/10.1007/s40593-016-0095-y

Touretzky, D. S., Gardner-McCune, C., Martin, F., Deborah W. Seehorn, Deborah W. Seehorn, & Seehorn, D. (2019). Envisioning AI for K-12: What Should Every Child Know about AI? 33(1), 9795–9799. https://doi.org/10.1609/aaai.v33i01.33019795

van Deursen, A. J., & van Dijk, J. A. (2014). The digital divide shifts to differences in usage. New Media & Society, 16(3), 507–526. https://doi.org/10.1177/1461444813487959

Vij, S., Tayal, D., & Jain, A. (2020). A machine learning approach for automated evaluation of short answers using text similarity based on WordNet graphs. Wireless Personal Communications, 111(2), 1271–1282. https://doi.org/10.1007/s11277-019-06913-x

Zawacki-Richter, O., Marín, V. I., Bond, M., Melissa Bond, & Gouverneur, F. (2019). Systematic review of research on artificial intelligence applications in higher education – where are the educators? International Journal of Educational Technology in Higher Education, 16(1), 1–27. https://doi.org/10.1186/s41239-019-0171-0

Zhang, K., & Aslan, A. B. (2021). AI technologies for education: Recent research & future directions. Computers and Education: Artificial Intelligence, 2, 100025.
https://doi.org/10.1016/j.caeai.2021.100025

Zhang, W., He, E., Mao, Y., Pang, S., & Tian, J. (2023). How Teacher Social-Emotional Competence Affects Job Burnout: The Chain Mediation Role of Teacher-Student Relationship and Well Being. Sustainability, 15(3), 2061. https://doi.org/10.3390/su15032061

More [+]

Session specifications

Topic:
Artificial Intelligence
Grade level:
PK-12
Skill level:
Beginner
Audience:
Coaches, Curriculum/district specialists, Teachers
Attendee devices:
Devices required
Attendee device specification:
Smartphone: Android, iOS, Windows
Laptop: Chromebook, Mac, PC
Tablet: Android, iOS, Windows
Participant accounts, software and other materials:
google
Subject area:
ELL, STEM/STEAM
ISTE Standards:
For Educators:
Designer
  • Use technology to create, adapt and personalize learning experiences that foster independent learning and accommodate learner differences and needs.
  • Design authentic learning activities that align with content area standards and use digital tools and resources to maximize active, deep learning.
  • Explore and apply instructional design principles to create innovative digital learning environments that engage and support learning.