Objective
SayPro leverages GPT technology to generate topic lists relevant to student skills, employer needs, and industry trends, and then analyzes the efficiency of prompts used to create these lists. This enhances the quality and relevance of internship and job placement matches.
๐ Details
1. ๐ค GPT-Generated Topic Lists
- What: Curated lists of topics such as skills, job roles, industry trends, and emerging technologies.
- Purpose: Help in aligning student profiles with employer requirements and current market demands.
- Usage:
- Inform curriculum and skill development initiatives.
- Enhance placement matching algorithms.
- Guide communication and content creation.
- Volume: Typically generated in batches (e.g., 100 topics per prompt) for comprehensive coverage.
2. ๐ Prompt Efficiency Reports
- What: Analytical reports measuring how well GPT prompts perform in generating useful, accurate, and relevant topic lists.
- Metrics Include:
- Relevance and specificity of generated topics.
- Diversity and coverage across industries and skills.
- Redundancy or overlap in topics.
- Time and computational resources used.
- Purpose:
- Optimize prompt wording and parameters.
- Ensure high-quality outputs that support SayProโs goals.
- Track improvements over time.
3. ๐ ๏ธ Implementation Workflow
- Design and test GPT prompts based on program needs.
- Generate topic lists and review them for relevance.
- Collect data on prompt performance and efficiency.
- Adjust prompts based on feedback and reports.
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Benefits
- Data-driven insights into labor market trends and skill demands.
- Enhanced matching of students to internships/jobs.
- Efficient use of AI tools for program improvement.
- Continuous refinement of content generation processes.
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