geo-infer-edu

name	geo-infer-edu
description	Educational technology for geospatial learning. Use when creating spatial analysis curricula, interactive GIS exercises, learning progression models, competency assessment for geographic concepts, or step-by-step spatial tutorials.
prerequisites	{"required":[],"recommended":["geo-infer-space","geo-infer-data"]}
difficulty	beginner
estimated_time	30min
examples_dir	../GEO-INFER-EXAMPLES/examples/

GEO-INFER-EDU

Instructions

Core Capabilities

• Curriculum design: Standards-aligned curriculum and module generation (CurriculumDesigner)
• Exercises: Template-based interactive exercises with starter code and test cases (ExerciseGenerator)
• Progress tracking: Competency tracking, gap identification, analytics, and privacy-aware exports (ProgressTracker)
• Personalized learning: Adaptive pathways and resource recommendations (PersonalizedLearning)
• Professional development: Certification pathways and continuing-education tracking (ProfessionalDevelopment)

Key Imports

from geo_infer_edu import (
    CurriculumDesigner,
    ExerciseGenerator,
    ProgressTracker,
    PersonalizedLearning,
    ProfessionalDevelopment,
)
from geo_infer_edu.core.progress import CompetencyLevel

Examples

from geo_infer_edu import ExerciseGenerator, ProgressTracker

# Generate exercises for a set of concepts
generator = ExerciseGenerator()
exercises = generator.create(
    concepts=["spatial_autocorrelation", "buffer_analysis"],
    format="code",           # 'interactive_map', 'code', 'quiz', 'practical'
    difficulty="progressive",
    include_hints=True,
)

# Track learner progress from activity logs and assessment scores
tracker = ProgressTracker(privacy_compliance="ferpa")
progress = tracker.track_progress(
    learner_id="student_042",
    activity_log=[
        {"id": "act_1", "type": "exercise", "topic": "spatial_autocorrelation",
         "score": 0.82, "duration_minutes": 45},
    ],
    assessments=[{"competency": "spatial_analysis", "score": 0.82}],
)
export = tracker.export_progress("student_042")  # JSON string, FERPA-pseudonymized

Guidelines

• Competency levels are ordered (NOT_STARTED < EMERGING < DEVELOPING < PROFICIENT < EXEMPLARY); assessments never silently downgrade an achieved level.
• CurriculumDesigner accepts only supported standards (bok, gistbok, ngss); unknown standards raise ValueError.
• ProgressTracker exports embed record.level.value strings, so exports are always JSON-serializable.

Integrations

• Optional integration with SPACE and DATA for spatial exercise content (not imported at runtime)
• Test: uv run python -m pytest GEO-INFER-EDU/tests/ -v