To recommend news articles and motivational content based on a person's educational qualifications and goals, you would need a combination of personal and contextual information.
Here are some types of data that could be valuable for making relevant recommendations:
Personal Information:
Name, age, gender.
Educational qualifications (degrees, certifications).
Professional qualifications and work experience.
Interests and hobbies.
Educational Goals and Objectives:
Specific educational goals (e.g., learning a new programming language, pursuing advanced studies).
Short-term and long-term career objectives.
Preferred learning style (e.g., visual, auditory, kinesthetic).
Learning History:
Courses completed or currently enrolled in.
Subjects of interest and proficiency.
Historical performance in assessments or tests.
Preferred Content Types:
Types of news articles or motivational content the user prefers (e.g., technology, science, career advice).
Preferred content formats (videos, articles, podcasts).
Time Constraints:
Available time for studying or consuming content.
Preferred time of day for learning activities.
Leverage public APIs that provide educational and career-related data. For example, LinkedIn API for professional information or APIs from educational platforms for course history
namita0210
commented
5 months ago
DATA COLLECTION
To recommend news articles and motivational content based on a person's educational qualifications and goals, you would need a combination of personal and contextual information.
Here are some types of data that could be valuable for making relevant recommendations:
Personal Information: Name, age, gender. Educational qualifications (degrees, certifications). Professional qualifications and work experience. Interests and hobbies.
Educational Goals and Objectives: Specific educational goals (e.g., learning a new programming language, pursuing advanced studies). Short-term and long-term career objectives. Preferred learning style (e.g., visual, auditory, kinesthetic).
Learning History: Courses completed or currently enrolled in. Subjects of interest and proficiency. Historical performance in assessments or tests.
Preferred Content Types: Types of news articles or motivational content the user prefers (e.g., technology, science, career advice). Preferred content formats (videos, articles, podcasts).
Time Constraints: Available time for studying or consuming content. Preferred time of day for learning activities.
Leverage public APIs that provide educational and career-related data. For example, LinkedIn API for professional information or APIs from educational platforms for course history