Example Assignments: Using BoodleBox for Classroom Collaboration

This guide showcases a diverse range of example class-wide assignments that harness the power of AI-assisted learning through BoodleBox. From interactive discussions to peer reviews, these collaborative activities demonstrate how students and teachers can collectively leverage AI tools to foster a rich learning environment, encourage peer-to-peer engagement, and showcase the collective academic growth of the entire class across various disciplines.

Example Assignments

1. Reading Comprehension Analysis:

  • Students submit chats of their interactions with an AI bot after completing a reading assignment to a shared class folder.
  • The professor analyzes these chats against learning objectives to identify common misunderstandings or areas where the class excelled.
  • This analysis helps the instructor tailor future lessons to address specific learning gaps or reinforce successful comprehension strategies.

2. Pre-Lecture Knowledge Check:

  • Before a lecture, students engage with an AI bot to discuss their current understanding of the upcoming topic and submit these chats to a class folder.
  • The instructor reviews the folder to gauge the class’s baseline knowledge and adjust the lecture content accordingly.

3. Post-Lecture Reflection:

  • After a lecture, students interact with an AI bot to summarize key points and ask follow-up questions, then add these chats to a shared folder.
  • The professor analyzes the folder to identify concepts that need further clarification in the next class session.

4. Problem-Solving Strategies in STEM:

  • Students solve a set of problems with AI assistance and submit their process chats to a class folder.
  • The instructor reviews the folder to identify common problem-solving approaches, misconceptions, and areas where students are effectively (or ineffectively) using AI tools.

5. Language Learning Progress Tracking:

  • In a language course, students regularly submit chats of their conversations with an AI language model to a shared folder.
  • The instructor analyzes these chats over time to track class-wide progress in vocabulary, grammar, and conversational skills.

6. Peer Review Compilation:

  • Students conduct peer reviews of each other’s work using AI assistance and submit these review chats to a class folder.
  • The professor examines the folder to assess the quality of peer feedback and identify areas where students need guidance in providing constructive criticism.

7. Research Methodology Assessment:

  • For a research methods course, students submit chats showing their interactions with AI for literature reviews and research design to a shared folder.
  • The instructor analyzes these chats to evaluate the class’s overall research skills and identify areas where additional instruction on research methodology is needed.

8. Ethical Reasoning Development:

  • Students engage with AI to discuss ethical dilemmas related to their field of study and submit these discussions to a class folder.
  • The professor reviews the folder to assess the development of ethical reasoning skills across the class and identify common ethical considerations or misconceptions.

9. Creative Writing Technique Analysis:

  • In a creative writing course, students submit chats where they’ve used AI for brainstorming or style analysis to a shared folder.
  • The instructor examines these chats to identify common creative approaches, areas where students are effectively using AI for inspiration, and aspects of writing craft that need more attention in class.

10. Concept Mapping and Connections:

  • Students use AI to help create concept maps or explore connections between different course topics, then submit these chats to a class folder.
  • The professor analyzes the folder to assess how well the class is integrating different concepts and identify areas where connections are being missed or misunderstood.

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