Themes Tecnologias

O CONNECT apoia as escolas na implementação do Ciência-Ação em cenários orientados para o futuro relacionados com TECNOLOGIAS, aplicando o modelo CARE-KNOW-DO (Cuidar-Saber-Fazer).

we-CARE (nós cuidamos): A primeira fase é principalmente a aprendizagem informal com profissionais e familiares, projetada para apresentar o desafio em torno de uma questão voltada para o futuro, estimular perguntas e criar uma “necessidade de saber” que os professores podem aproveitar na próxima etapa.

we-Know (nós sabemos): O segundo estágio é o aprendizado formal focado em alunos que adquirem a compreensão científica e as habilidades de que precisam para tomar decisões e agir no estágio final.

we-DO (nós fazemos): No terceiro estágio, os alunos aplicam as habilidades e conhecimentos adquiridos na ciência-participativa, definindo formas de abordar o desafio proposto e de minimizar seu impacto. Essa etapa também inclui uma avaliação.

we-CARE: This first stage focuses on informal learning with professionals and family, introducing a future-oriented challenge, stimulating questions, and creating a ‘need to know’ that teachers can build upon.

Technologies used: AI-generated tools such as OpenAI ChatGPT, Bing AI, Claude, and Contextminds help explore issues and provide insights, enabling students to identify and discuss questions that are relevant to them and their communities.

we-KNOW: The second stage involves formal learning, where students acquire scientific understanding and the skills needed to make decisions and take action. Students use AI-powered tools to map knowledge and discuss their maps with experts.

Technologies used: AI-based knowledge mapping tools such as MindMeister and Ayoa help students brainstorm current knowledge. They can connect new concepts with MyMap.Ai, develop arguments with Rationale.jina.ai, and link data with Tableau, building a robust foundation to enhance understanding and foster responsible critical, creative, and scientific thinking.

we-DO: In the third stage, students apply their acquired skills and knowledge in participatory science, defining approaches to tackle the given challenge and reduce its impact. This stage includes an evaluation of their solutions.

Technologies used: Tools and platforms for creating AI-based solutions, such as Machine Learning for Kids, Scratch, App Inventor, and Python, are utilized.

 

Examples of  technologies used in the AI Open Schooling Activities by schools:

Machine Learning for Kids is an educational platform designed to help children grasp machine learning concepts through hands-on projects.

• Integration: The platform enables students to train a classifier using photos uploaded from the internet or taken with a computer camera. Once trained, the model can be incorporated into various applications.
• Examples: Students can develop projects where their models classify images, recognize objects, or analyze text sentiment. The platform offers project templates to help students get started.

Scratch is a visual programming language that enables children to create games, stories, and animations through a block-based interface.

• Integration: Machine Learning for Kids can be integrated with Scratch, allowing trained machine learning models to enhance Scratch projects. This enables students to make their projects more interactive and intelligent.
• Examples: A Scratch project might use an image classifier to alter the story or gameplay based on objects detected in a webcam feed.

App Inventor is a visual programming environment for creating Android applications using a block-based approach, similar to Scratch.

• Integration: Machine Learning for Kids integrates with App Inventor, allowing students to embed machine learning models into their mobile apps.
• Examples: A mobile app could use a machine learning model to recognize handwritten digits, classify photos, or analyze text sentiment.

Python is a powerful programming language widely used in web development, data analysis, AI, and scientific computing.

• Integration: Machine Learning for Kids allows students to export trained models for use in Python applications. This is more advanced than Scratch and App Inventor, suitable for older students or those with programming experience.
• Examples: Python applications can use machine learning models for real-time image classification, sentiment analysis, natural language processing, or building intelligent agents.

AI Mapping Tools Popular in Schools

1. Mindmeister
   A widely used mind-mapping tool that integrates AI to help with the organization of ideas, collaboration, and visual brainstorming, popular in classrooms and collaborative projects.
2. Ayoa
   A mind mapping tool that incorporates AI to facilitate creative thinking and task management, commonly used in educational settings for brainstorming and planning.
3. Contextminds
   A knowledge mapping tool that integrates AI to suggest related concepts and ideas, making it easier to organize thoughts and create educational diagrams.
4. Mymap.ai
   This AI-driven tool aids users in creating dynamic mind maps by suggesting links and topics based on input. It simplifies idea generation and project planning.
5. Rationale.jina.ai
   This AI-powered tool assists with creating logical argument maps by helping users structure reasoning and critical thinking processes visually.
6. Tableau Public
   A widely used data tool, student-friendly and free, that integrates AI to help students map and understand complex datasets. With its integration of machine learning (via the Tableau Prep tool), students can upload Excel or CSV files and map data for easy visualization and insights.

These resources aim to enable teachers, students, STEM professionals, and families to successfully implement a Science Action.

CONNECT Resources can be a structured scenario material linked to the science curriculum in school (formal learning) and an open scenario with participatory science tools outside school (informal learning).

Open Schooling with AI developed in Schools

The Resources consist of stimulus materials that will:

• engage students to interact with STEM professionals,
• facilitate awareness-raising activities for families (CARE),
• guide teachers on how to integrate the teaching of a science concept (KNOW),
• instruct students on conducting specific activities and to produce an output,
• guide STEM professionals on evaluating student work (DO).

Access our resources to embed AI activities in you ropen schooling lessons on our platform.