Automated Teaching Resource Production Program
Teachers can efficiently create the following instructional materials using Open Deep Research:
- Intelligent Outline GenerationInput curriculum standards such as "Python Programming Fundamentals for High Schools", and the system will automatically break it down into teaching modules such as variables, loops, functions, etc., and match them with examples of the appropriate level of difficulty.
- Multimedia packages: Generate course cover art via `-gen_cover true` and `-gen_podcast true` to create audio summaries of knowledge points to meet different learning needs.
- Differentiated Content Adaptation: Add parameters such as `-audience=beginner` to control the depth of the content, and support the generation of teacher's version of the guidebook and student's version of the study materials.
- Question Bank Extension: The `exercise_generator` plugin available in the Community Edition automatically produces practice questions and reference answers (additional installation required).
Typical workflow:
- Prepare course description file `course_desc.md` describing instructional objectives and audience
- Execute the command: `python main.py -topic "Introduction to machine learning" -mode education -output_dir lesson_plans `
- Generate Chinese teaching content using `-lang=zh-CN` parameter
- Personalization of the generated `activity design' and `extended reading' sections
Efficiency Tips:
- Create a library of personal teaching templates (saved as JSON files for reuse)
- Integration with LMS systems such as Moodle for automated uploads
- Accelerating Similar Course Generation with Historical Report Caching
This answer comes from the articleTogether Open Deep Research: Generating Indexed Deep Research ReportsThe
May not be reproduced without permission:AI productivity tools " How can I quickly generate course instructional materials in an educational scenario?
