generate-learner-profile

# Generate Learner Profile Command Generate a comprehensive learner profile that informs curriculum differentiation, example selection, and transfer planning. The profile captures five dimensions of the target audience: prior knowledge, motivational drivers, learning preferences and constraints, transfer environment, and resistance points. Each dimension maps directly to concrete curriculum design decisions. ## Why This Matters Designing a course without understanding the audience leads to: - **Mismatched difficulty** — content too basic for experienced learners or too advanced for novices - **Low engagement** — examples and framing that don't connect to participants' real context - **Poor transfer** — skills taught but never applied because the workplace doesn't support them - **Unnecessary resistance** — objections that could have been preemptively addressed in design A learner profile ensures that differentiation tiers, example domains, scaffolding depth, and transfer strategies are calibrated to the actual audience rather than assumed defaults. ## Prerequisites - A course topic or context (can come from existing course-positioning.md or be gathered interactively) - Ideally, a training needs analysis has been completed first (`01-planning/training-needs-analysis.md`) ## Command Behavior When user invokes `/course-curriculum-creator:generate-learner-profile [--from-tna]`: ### Step 1: Load Existing Context 1. **Read `01-planning/course-positioning.md`** (if exists) for audience context — extract course title, target audience description, and any stated prerequisites. Use this to pre-populate questions where possible. 2. **Read `01-planning/training-needs-analysis.md`** (if exists or `--from-tna` flag provided) for gap type and population data — pre-populate answers where TNA already has the data. Specifically extract: - Target population skill range - Prior related training - Gap type classification - Learning context If either file exists and provides relevant data, inform the user: "I found existing data in [file] — I'll pre-populate where I can. You can confirm or override each item." ### Step 2: Gather Five Dimensions Interactively Use AskUserQuestion to gather each dimension. For each dimension, present pre-populated data from Step 1 (if available) and ask the user to confirm, correct, or expand. #### Dimension 1: Prior Knowledge Inventory What participants already know and what they cannot yet do. Ask: "What can participants already do related to this topic? List 3-5 skills or concepts they're comfortable with." Then ask: "What can participants NOT yet do? List 3-5 skills or concepts that represent gaps. For each, indicate whether it's a critical prerequisite, moderate gap, or minor gap." Map responses to prerequisites — what must be true before Day 1 versus what the course will teach. #### Dimension 2: Motivational Drivers Why participants are attending and what drives their engagement. Ask: "Why are participants taking this course? (a) Required by organization — mandatory attendance (b) Self-selected for career growth (c) Mixed — some mandatory, some voluntary (d) Other — please describe" Follow up: "What do participants hope to gain? What would make them say 'this was worth my time'?" #### Dimension 3: Learning Preferences & Constraints Practical constraints that shape design decisions. Ask: "What constraints should we design around? Consider: - Technology access and proficiency level - Language considerations (primary languages, proficiency) - Accessibility needs (known or anticipated) - Schedule constraints (time zones, availability windows) - Expected group size - Attention span expectations (e.g., max session length)" #### Dimension 4: Transfer Environment Whether the workplace will support applying new skills after the course. Ask: "After the workshop, what support will participants have? (a) Manager actively reinforcing — follows up, provides practice opportunities (b) Manager aware but hands-off — knows about the training but won't actively support (c) No manager involvement — manager may not know about the training (d) Unknown — we don't have this information yet" Follow up: "Will participants have access to the tools and resources needed to practice? Are there competing priorities that might prevent application?" #### Dimension 5: Resistance Points Anticipated objections, prior negative experiences, or competing priorities. Ask: "What resistance or skepticism do you anticipate? Consider: - Prior negative training experiences - 'We've tried this before' attitudes - Competing workload pressures - Skepticism about the topic's relevance - Cultural or organizational barriers" ### Step 3: Generate Design Implications Map each finding to a concrete curriculum decision. For each significant finding, create a row in the Design Implications table following this pattern: | Finding | Curriculum Impact | Action | |---|---|---| | High tech anxiety | Add Module 0 tech orientation | Include step-by-step screenshots in all activities | | Mandatory attendance | Extra engagement hooks needed | Add immediate relevance connections in every module opening | | Low manager support | Stronger self-directed transfer plan | Add peer accountability groups, self-directed action items | | Mixed skill levels | Wider differentiation tiers needed | Design floor/extension tiers with larger spread in practice activities | Generate differentiation guidance: - **Floor tier** should assume: [baseline capability derived from prior knowledge inventory] - **Extension tier** should challenge: [stretch capability derived from gaps and motivations] - **Scaffolding emphasis**: [where extra support is needed based on constraints and resistance] ### Step 4: Write Output Write the learner profile to `01-planning/learner-profile.md`. Compute sourceHashes by running: ```bash md5sum 01-planning/course-positioning.md 2>/dev/null | cut -c1-8 ``` ## Settings Integration Plugin settings (configured with `/plugin configure`). If the project has a `.claude/course-curriculum-creator.local.md` file, values in its YAML frontmatter override these. A value still shown as a literal `${user_config.…}` placeholder has not been set, so use its default: - `instructor_name` = `${user_config.instructor_name}` (default: not set): Use as analyst name in the output document - `organization` = `${user_config.organization}` (default: not set): Use as organization in the output document If a value is empty and not overridden, omit these fields from frontmatter rather than prompting (they are optional for this document). ## Output Format Generate the learner profile with the following structure: ```markdown --- title: Learner Profile - [Course Title] date: YYYY-MM-DD version: 0.1.0 status: draft lastUpdated: YYYY-MM-DD sourceFiles: course-positioning: "01-planning/course-positioning.md" sourceHashes: course-positioning: "[md5-first-8]" --- # Learner Profile ## [Course Title] **Purpose:** Inform curriculum differentiation, example selection, and transfer planning based on audience analysis. --- ## 1. Prior Knowledge Inventory ### What Participants Can Already Do | Skill/Concept | Confidence Level | Evidence | |---|---|---| | [Skill 1] | [High/Medium/Low] | [How we know] | ### What Participants Cannot Yet Do | Skill/Concept | Gap Severity | Implication | |---|---|---| | [Skill 1] | [Critical/Moderate/Minor] | [Prerequisite? Pre-work? Module focus?] | ### Prerequisite Mapping [Map prior knowledge to course prerequisites — what must be true before Day 1] --- ## 2. Motivational Drivers | Factor | Finding | Design Response | |---|---|---| | Attendance type | [Voluntary/Mandatory/Mixed] | [Engagement strategy] | | Primary motivation | [Career/Compliance/Curiosity/Other] | [Relevance framing] | | Expected ROI | [What participants hope to gain] | [Value prop emphasis] | --- ## 3. Learning Preferences & Constraints | Constraint | Details | Accommodation | |---|---|---| | Technology proficiency | [Level] | [Tech orientation needed?] | | Language considerations | [Primary languages] | [Glossary, pacing, visual aids] | | Accessibility needs | [Known or anticipated] | [Specific UDL measures] | | Schedule constraints | [Time zones, availability] | [Session timing] | | Group size | [Expected N] | [Activity format implications] | --- ## 4. Transfer Environment | Factor | Assessment | Risk Level | |---|---|---| | Manager support | [Active/Aware/None/Unknown] | [High/Medium/Low] | | Tool/resource access | [Available/Partial/None] | [High/Medium/Low] | | Competing priorities | [Description] | [High/Medium/Low] | | Organizational culture | [Supports learning?] | [High/Medium/Low] | **Transfer risk summary:** [Overall assessment of how likely participants are to apply learning post-workshop] --- ## 5. Resistance Points | Anticipated Resistance | Source | Mitigation Strategy | |---|---|---| | [Resistance 1] | [Why they feel this way] | [How to address in curriculum] | --- ## 6. Design Implications **Priority adjustments based on this profile:** | Finding | Curriculum Impact | Action | |---|---|---| | [Finding 1] | [What to change] | [Specific file/command affected] | | [Finding 2] | [What to change] | [Specific file/command affected] | **Differentiation guidance:** - Floor tier should assume: [baseline capability] - Extension tier should challenge: [stretch capability] - Scaffolding emphasis: [where extra support is needed] ``` If `sourceFiles` entries don't exist (files were not found), omit those entries from the frontmatter rather than including empty values. ## Integration Points - `generate-lesson-plans` reads learner profile for differentiation tier calibration and example domain selection - `generate-transfer-plan` reads transfer environment section to calibrate manager briefing depth and self-directed vs. supported action plans - `generate-pre-work` reads prior knowledge inventory to determine pre-work depth - `quality-reviewer` agent checks learner profile exists and flags if differentiation tiers don't match profile findings - `curriculum-architect` agent adds learner profile generation as Phase 3.5 (after course initialization, before objectives) ## Error Handling **No course directory:** - Save as `learner-profile-YYYY-MM-DD.md` in current directory (same pattern as standalone TNA) - This supports running the profile before a course directory has been created **Course positioning missing:** - Proceed without pre-population, gather all data interactively - Inform the user: "No course-positioning.md found — I'll gather all information interactively." **User skips sections:** - Mark skipped sections as "[Not assessed — skipped by user]" - Still generate the document with available information - Note in the document which sections were skipped **Settings file not found:** - Omit optional settings-derived fields from output - Do not block or prompt for these values ## Implementation Notes **Date retrieval:** Always use bash to get current date: ```bash TZ='America/New_York' date '+%Y-%m-%d' ``` **Path handling:** - Check for `01-planning/` directory in current working directory to determine output mode - Use absolute paths in success messages - Expand ~ to full path if applicable **YAML frontmatter:** - All dates in YYYY-MM-DD format - Version starts at 0.1.0 (semantic versioning) - Status starts as "draft" - sourceHashes use first 8 characters of md5sum **DO NOT:** - Skip interactive questioning and fabricate learner data - Assume all participants are the same — always probe for skill range and diversity - Use relative dates ("today", "current") — always get actual date via bash - Generate a profile without user input on at least the prior knowledge dimension - Ignore resistance points — even if the user says "none", probe gently for hidden concerns - Copy TNA population data verbatim without confirming it's still current and complete --- Ensure every curriculum decision traces back to evidence gathered in this learner profile.