Artificial intelligence is rapidly entering science classrooms, yet many educators are unsure how to begin using it in purposeful and responsible ways. In this introductory session, participants will explore what AI is, what it is not, and how it can support NGSS sensemaking without replacing student thinking. Through live demonstrations and simple classroom examples, educators will learn how AI can help students ask better questions, strengthen reasoning, and engage more deeply with phenomena. The session highlights ethical use of AI as a partner in science learning.

TAKEAWAYS:
Participants will understand how to use AI as a tool for sensemaking that strengthens student questioning and reasoning while supporting phenomenon-based science learning routines.

SPEAKERS:
Chris Lazzaro, Velma Itamura

Artificial intelligence is rapidly entering science classrooms, and education leaders play a key role in shaping how it strengthens student sensemaking. This session explores how AI can help students ask stronger questions, reason with evidence, and engage more deeply with phenomena. Leaders will learn how to communicate a clear, purposeful vision for AI use, one that promotes thoughtful integration and supports high-quality science investigations. The session also highlights ways to partner with parents to build understanding and shared confidence in AI’s role in learning. Participants will leave with tools to assess readiness, articulate guiding principles, and position AI as a productive thinking partner in phenomenon-based science instruction.

TAKEAWAYS:
Participants will learn how to guide AI use to deepen science sensemaking, promote purposeful rather than restrictive practices, and engage parents as partners in supporting students’ phenomenon-based investigations.

SPEAKERS:
Chris Lazzaro, Velma Itamura

As AI becomes a routine part of science learning, educators across roles are looking for ways to lead its purposeful and productive use. This leadership session provides practical guidance for communicating about AI in ways that inspire curiosity, strengthen science sensemaking, and support phenomenon-based investigations. Participants will explore clear, consistent language and implementation strategies that empower teachers, engage families, and encourage thoughtful experimentation with AI as a reasoning partner. The session highlights supportive structures and approaches that help diverse learners and build educator confidence. Attendees will leave with insights and strategies they can adapt to guide AI-enabled science learning in their own classrooms, departments, schools, or districts.

TAKEAWAYS:
Attendees will learn how to communicate and implement AI in ways that inspire curiosity, strengthen sensemaking, and reshape classroom culture through purposeful routines, while partnering with parents and the community.

SPEAKERS:
Chris Lazzaro, Velma Itamura

As AI becomes more accessible, many traditional science assignments no longer reveal what students truly understand. This session helps educators move from policing AI use to designing tasks that encourage reasoning, reflection, and deeper engagement with phenomena. Participants will analyze why certain activities are vulnerable to AI shortcutting and learn practical strategies for redesigning them into AI-resilient tasks that surface student thinking. Through live demonstrations and sample routines, attendees will explore approaches that require students to critique, revise, justify, and apply ideas during phenomenon based investigations. The session include a framework to identify non-AI resilient tasks and reivse them into tasks that promote purposeful, sensemaking focused AI use.

TAKEAWAYS:
Educators will learn strategies for transforming traditional assignments into AI-resilient tasks that reveal student reasoning and strengthen sensemaking during phenomenon based investigations.

SPEAKERS:
Chris Lazzaro, Velma Itamura

AI can deepen science sensemaking when it is woven into a classroom culture that values curiosity, reflection, and evidence-based reasoning. This session introduces practical, tool-agnostic thinking structures that help students clarify ideas, test explanations, and reflect on their reasoning during phenomenon-based investigations. Participants will explore routines that position AI as a questioning partner, one that surfaces gaps in logic, offers alternative explanations, and supports revision of emerging ideas. Through live demonstrations, educators will see how these structures transform classroom norms by encouraging students to engage more purposefully with evidence, compare ideas, and make their thinking visible.

TAKEAWAYS:
Participants will learn AI-supported routines that strengthen student reasoning and help learners make their thinking visible during phenomenon based science investigations.

SPEAKERS:
Chris Lazzaro, Velma Itamura

Planning an investigation involves selecting variables, designing procedures, and ensuring fair tests, which can be challenging for many students. In this session, participants will explore how AI can support planning and carrying out investigations by helping students identify variables, consider controls, analyze procedural flaws, and revise plans during phenomenon-based investigations. Through hands on demonstrations, educators will examine examples of AI generated procedures that vary in quality and learn routines that prompt students to critique, justify, and refine investigation plans. The session emphasizes how AI can strengthen reasoning without replacing the work of designing thoughtful investigations.

TAKEAWAYS:
Participants will learn how AI can support students in identifying variables, evaluating procedures, and designing fair tests, strengthening reasoning during phenomenon-based investigations while making their reasoning visible.

SPEAKERS:
Chris Lazzaro, Velma Itamura

AI generated explanations can appear polished yet contain scientific inaccuracies, missing evidence, or embedded bias. In this session, participants will learn how to turn these flaws into powerful opportunities for science sensemaking. Educators will explore routines that guide students to critique AI generated explanations, identify errors, compare ideas with evidence, and revise thinking during phenomenon based investigations. Through live demonstrations, attendees will analyze examples of biased or incomplete AI reasoning and practice using frameworks that make student thinking visible.

TAKEAWAYS:
Participants will learn how to critique and revise AI outputs to deepen student reasoning and support sensemaking in phenomenon-based investigations.

SPEAKERS:
Chris Lazzaro, Velma Itamura

Interpreting data is central to science sensemaking, yet students often struggle to describe patterns, identify anomalies, or connect evidence to explanations. In this session, participants will explore how AI can support data analysis by helping students interpret data, compare datasets, generate multiple possible explanations, and revise interpretations during phenomenon-based investigations. Through hands on demonstrations, educators will examine examples of AI generated analyses that vary in accuracy and learn routines that require students to critique, justify, and improve analytical reasoning. Participants will leave with tangible ways to strengthen student science reasoning skills.

TAKEAWAYS:
Educators will explore how AI can support data interpretation by helping students critique AI reasoning and refine explanations tied to real world phenomena.

SPEAKERS:
Chris Lazzaro, Velma Itamura

Constructing explanations and scientific arguments requires students to think like scientists, testing ideas against evidence, uncovering misconceptions, and refining reasoning. This session explores how AI can support those habits of mind by helping students evaluate the strength of their claims, identify gaps in logic, and compare alternative explanations during phenomenon-based investigations. Participants will analyze AI-generated explanations to determine where scientific principles are upheld or misapplied, and practice routines that guide students to question, critique, and revise AI outputs rather than accept them at face value. The session emphasizes how AI can be used to strengthen science processing skills, promote deeper sensemaking, and help learners understand how scientific knowledge is built.

TAKEAWAYS:
Attendees will learn strategies to guide students in critiquing AI-generated explanations so they build scientific arguments grounded in evidence, logic, and sensemaking, while deepening understanding of how scientific explanations are constructed.

SPEAKERS:
Chris Lazzaro, Velma Itamura

Scientific models help students explain phenomena, yet many learners struggle to revise or compare models in meaningful ways. In this session, participants will explore how AI can generate draft models or representations that students can refine, critique, and compare during phenomenon based investigations. Through hands on demonstrations, educators will analyze examples of AI produced models that vary in accuracy or completeness and use structured routines to help students identify misconceptions, improve explanations, and justify revisions with evidence. Attendees will leave with example routines that strengthen student critical thinking through the purposeful use of AI.

TAKEAWAYS:
Educators will learn routines that use AI models for critique and revision, helping students surface misconceptions and strengthen explanations.

SPEAKERS:
Chris Lazzaro, Velma Itamura

Asking strong scientific questions is central to sensemaking, yet many students struggle to move beyond surface level ideas. In this session, participants will explore how AI can support questioning that leads to deeper engagement with phenomena and clearer pathways for phenomenon-based investigations. Through hands on demonstrations, educators will learn routines that use AI to generate, refine, and evaluate questions, as well as produce flawed examples that students can critique to reveal their reasoning. The session emphasizes practices that strengthen student thinking by avoiding AI shortcutting. Attendees will leave with adaptable questioning templates and classroom ready strategies.

TAKEAWAYS:
Participants will learn how AI supported routines can help students generate, refine, and critique scientific questions that lead to stronger reasoning and deeper engagement with phenomenon-based investigations.

SPEAKERS:
Chris Lazzaro, Velma Itamura

Multimodal AI tools can analyze images, graphs, diagrams, and datasets, giving students new entry points into science sensemaking. In this session, participants will explore how multimodal AI can help students describe phenomena, interpret data patterns, compare representations, and refine explanations during phenomenon-based investigations. Through hands on demonstrations, educators will examine strengths and limitations of multimodal outputs and learn routines that prompt students to critique, revise, and build on AI generated interpretations.

TAKEAWAYS:
Participants will learn how multimodal AI can support science sensemaking by helping students interpret images, data, and diagrams and by prompting deeper reasoning during phenomenon-based investigations.

SPEAKERS:
Chris Lazzaro, Velma Itamura