""" EdTech Extensions - Content Adaptation This module provides functionality for adapting educational content based on student profiles and learning objectives. """ from typing import Dict, List, Optional, Any, Union import os import json from datetime import datetime from ..mcp_core.protocol import StudentProfile, LearningObjective, EducationalLevel, ContentFormat class ContentAdapter: """ Adapts educational content based on student profiles and learning objectives. This class provides functionality for personalizing educational content to match a student's learning style, educational level, and interests. """ def __init__(self): """Initialize a new ContentAdapter.""" pass async def adapt_content( self, content: Dict[str, Any], student_profile: StudentProfile, learning_objectives: List[LearningObjective], content_format: ContentFormat = ContentFormat.TEXT ) -> Dict[str, Any]: """ Adapt educational content for a specific student. Args: content: Original content to adapt. student_profile: Student profile to adapt content for. learning_objectives: Learning objectives for this content. content_format: Format of the content. Returns: Dictionary containing adapted content and metadata. """ # In a real implementation, this would use AI models to adapt content # based on the student profile and learning objectives. # For this demo, we'll implement a simplified version. original_text = content.get("text", "") # Apply adaptations based on educational level adapted_text = self._adapt_for_educational_level( original_text, student_profile.educational_level ) # Apply adaptations based on learning style adapted_text = self._adapt_for_learning_style( adapted_text, student_profile.learning_style ) # Apply adaptations based on interests adapted_text = self._adapt_for_interests( adapted_text, student_profile.interests ) # Generate recommended activities recommended_activities = self._generate_recommended_activities( student_profile, learning_objectives ) # List adaptations applied adaptations_applied = [] if student_profile.educational_level: adaptations_applied.append(f"Adapted for {student_profile.educational_level} educational level") if student_profile.learning_style: adaptations_applied.append(f"Adapted for {student_profile.learning_style} learning style") if student_profile.interests: adaptations_applied.append("Incorporated student interests") return { "text": adapted_text, "original_text": original_text, "adaptations_applied": adaptations_applied, "recommended_activities": recommended_activities, "format": content_format, "adapted_at": datetime.utcnow().isoformat() } def _adapt_for_educational_level( self, text: str, educational_level: EducationalLevel ) -> str: """ Adapt content for a specific educational level. Args: text: Original text content. educational_level: Target educational level. Returns: Adapted text content. """ # In a real implementation, this would use more sophisticated techniques # such as vocabulary adjustment, complexity reduction, etc. if educational_level == EducationalLevel.ELEMENTARY: # Simplify language for elementary level return f"{text}\n\n[Note: This content has been simplified for elementary level students.]" elif educational_level == EducationalLevel.MIDDLE_SCHOOL: # Moderate complexity for middle school return f"{text}\n\n[Note: This content has been adapted for middle school students.]" elif educational_level == EducationalLevel.HIGH_SCHOOL: # Standard complexity for high school return f"{text}\n\n[Note: This content has been adapted for high school students.]" elif educational_level == EducationalLevel.UNDERGRADUATE: # Higher complexity for undergraduate return f"{text}\n\n[Note: This content has been adapted for undergraduate students.]" elif educational_level == EducationalLevel.GRADUATE: # Advanced complexity for graduate return f"{text}\n\n[Note: This content has been adapted for graduate students with advanced terminology.]" elif educational_level == EducationalLevel.PROFESSIONAL: # Professional terminology return f"{text}\n\n[Note: This content has been adapted with professional terminology.]" return text def _adapt_for_learning_style(self, text: str, learning_style: str) -> str: """ Adapt content for a specific learning style. Args: text: Original text content. learning_style: Target learning style. Returns: Adapted text content. """ # In a real implementation, this would use more sophisticated techniques if not learning_style: return text if learning_style.lower() == "visual": # Add visual cues return f"{text}\n\n[Note: Visual diagrams and charts would be included here to support visual learners.]" elif learning_style.lower() == "auditory": # Add auditory cues return f"{text}\n\n[Note: Audio explanations would be available for auditory learners.]" elif learning_style.lower() == "reading": # Add reading cues return f"{text}\n\n[Note: Additional reading materials and references are provided for reading-oriented learners.]" elif learning_style.lower() == "kinesthetic": # Add kinesthetic cues return f"{text}\n\n[Note: Interactive exercises would be included here for kinesthetic learners.]" return text def _adapt_for_interests(self, text: str, interests: List[str]) -> str: """ Adapt content to incorporate student interests. Args: text: Original text content. interests: List of student interests. Returns: Adapted text content. """ # In a real implementation, this would use more sophisticated techniques if not interests: return text interest_note = f"\n\n[Note: This content would include examples related to your interests in {', '.join(interests)}.]" return text + interest_note def _generate_recommended_activities( self, student_profile: StudentProfile, learning_objectives: List[LearningObjective] ) -> List[Dict[str, Any]]: """ Generate recommended activities based on student profile and learning objectives. Args: student_profile: Student profile. learning_objectives: Learning objectives. Returns: List of recommended activities. """ # In a real implementation, this would generate personalized activities # based on the student's profile and learning objectives. activities = [] # Add activities based on learning style if student_profile.learning_style: if student_profile.learning_style.lower() == "visual": activities.append({ "type": "visualization", "title": "Create a visual diagram", "description": "Create a diagram that visualizes the key concepts." }) elif student_profile.learning_style.lower() == "auditory": activities.append({ "type": "discussion", "title": "Verbal explanation", "description": "Record yourself explaining the concept to someone else." }) elif student_profile.learning_style.lower() == "reading": activities.append({ "type": "research", "title": "Research and summarize", "description": "Find additional resources on this topic and write a summary." }) elif student_profile.learning_style.lower() == "kinesthetic": activities.append({ "type": "hands-on", "title": "Practical application", "description": "Complete a hands-on project applying these concepts." }) # Add activities based on learning objectives for objective in learning_objectives: if "remember" in objective.taxonomy_level.lower(): activities.append({ "type": "quiz", "title": f"Quiz on {objective.subject_area}", "description": f"Test your recall of key facts about {objective.description}" }) elif "understand" in objective.taxonomy_level.lower(): activities.append({ "type": "explanation", "title": f"Explain {objective.subject_area} concepts", "description": f"Write an explanation of {objective.description} in your own words." }) elif "apply" in objective.taxonomy_level.lower(): activities.append({ "type": "problem", "title": f"Apply {objective.subject_area} knowledge", "description": f"Solve problems that require applying {objective.description}." }) elif "analyze" in objective.taxonomy_level.lower(): activities.append({ "type": "analysis", "title": f"Analyze {objective.subject_area}", "description": f"Analyze a case study related to {objective.description}." }) # Limit to 3 activities return activities[:3]