Assessing Readability Levels

Requirements Clarification & Assessment

1. Audience and Language Scope:

   • Clarifying Question: Is the application intended for a single language pair (e.g., French speakers learning English) or does it support multiple languages?
   • Target User: Is the application designed for a specific age group or proficiency level? For example, children vs adults, or beginner vs advanced learners.

2. Business Model and Objectives:

   • Monetization: Is the application subscription-based or ad-supported?
   • Engagement Metrics: Is the primary metric of success the time spent on the platform, the number of texts read, or user satisfaction?

3. Personalization:

   • User-Specific Features: Should the algorithm consider individual user characteristics, such as age, native language, or learning speed?

4. Data Availability and Constraints:

   • Historical Data: Is there existing data on user interactions, such as quiz scores or time taken to read texts?
   • Dataset Diversity: What is the size and diversity of the available dataset? Does it include a variety of sentence structures and difficulty levels?

5. Output Requirements:

   • Readability Scale: How should the algorithm categorize readability (e.g., 1/10 for easy to 9/10 for challenging)?

6. Regulatory and Ethical Considerations:

   • Data Privacy: Are there any data privacy laws or regulations that must be adhered to, especially when handling user data?