Journal Entry Creation Flow

Primary user workflow: Capturing everyday moments and tagging skills

Core Philosophy

Photo-First

Primary interaction is taking a photo of a moment

AI Does the Heavy Lifting

System suggests skills/behaviors - parent doesn't need deep thinking

Speed Over Perfection

Must be faster than traditional journaling apps

User Journey: Create Journal Entry

Start

User Taps "New Entry" Button

Always accessible floating action button from any screen

↓
View: Photo Capture

Camera Opens

Options:

  • Take new photo with camera
  • Select existing photo from library

UI Elements: Camera viewfinder, capture button, switch camera, flash control, gallery thumbnail

↓
User Action

User Captures/Selects Photo

Photo of child doing activity: sandcastle, feeding cat, cooking, playing, etc.

↓
Controller: Photo Upload

uploadPhoto(photoData, childId)

  • Uploads photo to cloud storage
  • Handles compression and optimization
  • Returns cloud storage URL
↓
View: Entry Details

Entry Details Screen

UI Components:

  • Large photo preview (editable)
  • Date/time picker (defaults to now)
  • Freeform notes text area (optional, multiline)
  • "Analyze Photo" button or automatic AI processing
↓
User Action

User Adds Context (Optional)

Parent adds freeform notes about what happened, conversations, observations

This step is optional - speed is prioritized

↓
Controller: AI Analysis

analyzePhoto(photoUrl, contextNotes)

  • Sends photo and context to AI service
  • Returns detected activities, environments, objects, people
↓
Controller: Template Suggestion

suggestTemplate(aiAnalysisData, childAge)

  • Takes AI analysis + child context
  • Returns best template suggestions
  • Ranked by confidence/relevance
↓
View: AI Template Suggestion

Template Suggestion Card

UI Components:

  • Template icon and name (e.g., "Beach Day", "Cooking Together")
  • Pre-selected skills/behaviors as tags/chips
  • "Use Template" button (one-tap acceptance)
  • "Skip" button
  • Option to view other template suggestions
↓
User Action

User Accepts or Skips Template

One tap to accept pre-selected skills, or skip to manual tagging

↓
Controller: Skill & Behaviour Suggestions

suggestSkills(templateId, aiAnalysisData, childAge)

suggestBehaviours(templateId, aiAnalysisData, childAge)

  • Suggests specific skills from 64-skill taxonomy (6 categories)
  • Suggests character traits from 22-behaviour taxonomy
  • Returns arrays with confidence levels
↓
View: Skill & Behaviour Tagging

Tag Selection Screen

Skills Section:

  • Selected skills as tags (color-coded by category: Literacy, Communication, Numeracy, Motor, Analytical, Cognitive)
  • Quick-add skill selector (searchable, categorized)
  • "Add custom skill" option

Behaviours Section:

  • Selected character traits as tags (distinct styling from skills)
  • Quick-add from 22 core behaviours (Independent, Resilient, Curious, etc.)
  • "Add custom behaviour" option

Each tag shows: name, remove button (X), optional confidence indicator

↓
User Action

User Confirms/Modifies Skills & Behaviours

User reviews AI suggestions and adds/removes skills and character traits as needed

Key Principle: Quick taps - minimal friction

↓
Controller: Save Entry

createJournalEntry(childId, photoUrl, notes, entryDate)

Creates journal entry record with basic info

↓
Controller: Link Skills & Behaviours

addSkillsToEntry(entryId, skillsArray)

addBehavioursToEntry(entryId, behavioursArray)

  • Links skills and behaviours to journal entry
  • Creates EntrySkill and EntryBehaviour junction records
  • Stores confidence levels
  • Tracks whether AI-suggested or parent-added
↓
Database: Write

Data Persisted

Entities Updated:

  • JournalEntry: New entry record
  • EntrySkill: Many junction records linking entry to skills
  • EntryBehaviour: Many junction records linking entry to character traits
↓
Controller: Update Progress

calculateSkillProgress(childId, skillId)

  • Recalculates progress for each demonstrated skill
  • Updates proficiency level (age-relative)
  • Determines trend (improving/stable/declining)
↓
Database: Update

Progress Records Updated

Entity: SkillProgress (calculated/cached)

↓
Controller: AI Learning

learnFromUserCorrections(entryId, aiSuggestions, userSelections)

  • Tracks when users accept/reject/modify AI suggestions
  • Feeds data back to improve future suggestions
  • Updates AI model training data
↓
View: Success

Success Confirmation

Entry saved! User sees brief success message, then returns to timeline view

↓
End

Entry Appears in Timeline

New entry is visible in child's journal timeline and contributes to progress tracking

Key Database Interactions

JournalEntry

Created with:

  • Child ID (FK)
  • Creator User ID (FK)
  • Photo URL
  • Entry date/timestamp
  • Freeform notes
  • AI analysis data (JSON)
  • Template used (FK, nullable)

Skill & Behaviour Taxonomies

64 Skills across 6 categories:

  • Literacy (14)
  • Communication (10)
  • Numeracy (13)
  • Motor skills (4)
  • Analytical (13)
  • Cognitive (10)

22 Behaviours (character traits):

Independent, Resilient, Curious, Empathic, Creative, etc.

EntrySkill (Junction)

Links entry to skills:

  • Entry ID (FK)
  • Skill ID (FK)
  • Confidence level (1-5 or %)
  • Source (AI vs. parent-added)
  • Notes (optional context)

EntryBehaviour (Junction)

Links entry to character traits:

  • Entry ID (FK)
  • Behaviour ID (FK)
  • Confidence level (1-5 or %)
  • Source (AI vs. parent-added)
  • Notes (optional context)

SkillProgress

Updated/calculated:

  • Child ID (FK)
  • Skill ID (FK)
  • Current level (age-relative)
  • First/latest demonstration
  • Demonstration count
  • Trend indicator

Design Priorities

CRITICAL: Minimize friction - every extra tap reduces adoption
HIGH: AI suggestions must be accurate to build trust
HIGH: One-tap template acceptance for speed
MEDIUM: Freeform notes are optional - don't block workflow
MEDIUM: Auto-save drafts to prevent data loss

Generated from /docs/phase-1/ documentation

← Back to all workflows