Campfire Session — Science

Discover how AI transforms science education with practical Flint features, real classroom examples, and step-by-step activity creation guidance from science educators.

Lulu Gao, Head of Teacher Experience at Flint | LinkedIn

In this session, we explored how Flint's AI capabilities can revolutionize science education, showcasing specific features designed for science teachers and walking through real examples of engaging science activities. Our team demonstrated the step-by-step process of creating effective science activities on the platform and heard directly from science educators who shared their experiences and successes using Flint in their classrooms. This session provides practical insights you can immediately apply to enhance student engagement and learning outcomes in your science courses.

Content covered in this session included:

• Science features in Flint
• Science activity examples
• Step-by-step science activity creation
• Educator share-outs and feedback

Slides from the presentation can be found here.

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Introduction • 00:00

• Lulu introduces the session and agenda for covering Flint use cases for various science courses.

Ice-breaking news • 01:44

• Lulu shows the new Anthropic Economic Index that shows which professions and use cases for Claude are more popular.

Science features in Flint • 05:15

• The session dives into science features and tools within Flint. A series of demonstrations shows uploading content, built-in math accuracy, and equation generation in documents.

• Graphs and visualizations are showcased, including capabilities to read student work, generate data, and visualize lab results. The discussion highlights practical examples like population data, camouflage effects, and custom data input.

• The team discusses Flint features for research and resource accuracy, warning that AI can hallucinate links and advising double-checking sources. They explain how Flint will cite resources and how users can navigate to linked content.

• The group highlights the whiteboard feature, allowing students to paste images, draw on diagrams, and create new drawings for collaborative work, noting its usefulness in learning activities.

• Attention is given to a new “Needs attention” feature that highlights students who might need teacher intervention based on their conversations, to simplify in-person facilitation and targeting of support.

Science activity examples • 11:29

• Lulu shares a list of use cases for Flint for science education, including data visualization, reflection on labs/hypotheses/projects, problem solving practice, role plays with SMEs or concepts, quick knowledge checks, research, tutoring and test prep and projects.

• Many science activity templates created by other educators are highlighted.

• A feature discussion highlights public and school libraries for activities. It is suggested that teachers can upvote and comment on activities to build reviews. The team notes how to access and navigate public library, with links and filters to improve discovery.

Creating a science activity • 19:48

• A hands-on walkthrough of creating an activity shows Flint generating prompts, incorporating uploaded images, and setting up role-play style scenarios. The process includes uploading materials, specifying student context, and Flint producing a detailed rubric and scoring guidance.

• Lulu explains how to preview and test Flint manually, emphasizing the importance of experiencing the student perspective and using a step-by-step rubric for consistency. It is suggested to simulate a session, reset, and then review the feedback and guidance provided by Flint to ensure reliability.

• The discussion shifts to enhancing student interaction, including using the whiteboard and prompts within Flint messages. Teachers are advised to enable access to the whiteboard, integrate prompts and visuals, and consider first activities that introduce these tools.

• Flint users discuss configuring formative assessments with auto-marking and analytics. A plan is described to create quizzes, track class results, and adjust grading scales for different classrooms.

• Lulu Gao confirms feature capabilities for quizzes, auto-marking, and analytics, shares caveats about possible mis-marking, and demonstrates locating examples within the session page.

Educator share-outs and feedback • 42:53

• The group discusses practical uses and experiences with Flint, highlighting tutoring-like activities, problem-solving guidance, and Socratic prompting. Examples include feeding problems and rubrics, and the tutor guiding a student through substitutions, with growing effectiveness over time.

• Lara Cross shares demonstrations of Flint features, including graph-reading tutor support and photo-realistic image generation to analyze student work and explain concepts. Several specific activities are described, including habitats, species adaptation, and a solar-system role-play activity, with positive student reactions.

• The discussion highlights practical uses of a learning assistant in science and personal projects, including vetting ideas, guiding labs, and preparing for exams. It notes that the tool helps with logistics and framing student thinking, while acknowledging the need for teacher oversight.

• Participants discuss strategies to address students’ reliance on direct answers, comparing Flint to a muscle gym versus ChatGPT. They emphasize building critical thinking and treating the tool as a conversational partner to extract deeper understanding.

• A request for a lab simulation feature is discussed and considered. The team notes that Flint could eventually support more interactive simulations, potentially via storytelling and images, though not yet a full hands-on experience.

• Izzie and Lulu discuss engaging, interactive computer science use cases to make practice activities more interesting, including escape rooms, role-play, and a personality-driven tutor. The idea of an instructor-created persona named Bruce is referenced to boost student engagement.

• The team discusses using AI to assess collaboration skills from recorded group work, proposing transcription from devices and automatic speaker identification. Feedback would be delivered based on a preset rubric, with a goal of systematic, automated evaluation.

• Lulu Gao suggests Descript as a tool for multi-speaker transcription, enables later import into Flint for rubric-based evaluation, and mentions context setup for activities. The idea is framed as a practical path to enable group analytics.

Conclusion • 01:03:47

• Lulu concludes the session and highlights the plan for upcoming campfires.

• Lulu also shares QR codes for people to check out the Campfire Calendar, Flint's Instagram (which has a bunch of teacher-facing content), and the Flint Community.