File size: 1,890 Bytes
25732fb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 | import json
import os
import random
class TutorRuleEngine:
"""
Expert system for tutoring decisions.
Selects hint strategies and templates based on student state.
"""
def __init__(self, knowledge_base_path=None):
if knowledge_base_path is None:
base_dir = os.path.dirname(os.path.dirname(__file__))
knowledge_base_path = os.path.join(base_dir, 'knowledge_bases', 'hint_strategies.json')
self.strategies = []
self.quotes = []
self._load_knowledge_base(knowledge_base_path)
def _load_knowledge_base(self, path):
try:
with open(path, 'r') as f:
data = json.load(f)
self.strategies = data.get('hint_strategies', [])
self.quotes = data.get('motivational_quotes', [])
except Exception as e:
print(f"Error loading tutor knowledge base: {e}")
def select_hint_strategy(self, attempts, frustration_level):
"""
Select best hint strategy.
"""
# Linear progression logic based on attempts
if attempts == 1:
# First attempt: Socratic or subtle
return self._find_strategy("socratic_questioning")
elif attempts == 2:
# Second attempt: Conceptual
return self._find_strategy("conceptual_reminder")
elif attempts >= 3:
# High attempts: Direct help
return self._find_strategy("direct_correction")
# Fallback
return self.strategies[0] if self.strategies else None
def _find_strategy(self, name):
for s in self.strategies:
if s['name'] == name:
return s
return None
def get_motivational_quote(self):
if self.quotes:
return random.choice(self.quotes)
return "Keep trying!"
|