--- name: assessment-design description: | Evidence-based assessment design with rubrics, feedback strategies, and formative checkpoints. Aligns each assessment to learning objectives using Bloom's taxonomy. Applies Nicol's 7 principles of good feedback practice. Reads from /learning-objectives manifest and extends it with assessment specs. (idstack) --- ## Preamble: Interaction Conventions idstack skills are designed to run in multiple CLIs (Claude Code, OpenAI Codex CLI, and others). To stay portable, skill bodies use a few **concept names** that have a CLI-specific implementation: - **AskUserQuestion** — when a skill says "ask via AskUserQuestion" or "using AskUserQuestion", it means: present a single numbered multiple-choice question (e.g., "Which of these best describes X? 1) ..., 2) ..., 3) Other") and stop, waiting for the user's next message before proceeding. Ask **one** question at a time, never batch. In Claude Code this maps to the `AskUserQuestion` tool; in Codex CLI (which has no analog) just emit the numbered question as plain text and wait. - **Agent / Skill (sub-task dispatch)** — when a skill says "if the Agent tool is available, dispatch X as a sub-task," that's an optimization. If your CLI has no equivalent, fall through to the inline written-out steps that follow — every skill that uses `Agent` ships a sequential fallback alongside it. - **Skill (cross-skill invocation)** — used only by `/idstack:pipeline`. In Claude Code this invokes a child skill in-process via the `Skill` tool. In CLIs without that primitive, the pipeline degrades to prompting the user to type the next skill name explicitly. - **Skill invocation syntax in user-facing text** — when a skill prints "run `/idstack:foo`" or links to `/idstack:foo` in a "Next steps" section, that's Claude Code's `/idstack:` invocation. **In Codex CLI, translate to `$foo`** (drop the `/idstack:` prefix, replace the leading `/` with `$`). Apply this same translation when the skill emits handoff instructions in reports, manifests, or AskUserQuestion options. Same body text, two hosts; the model translates per-CLI on output. These are **directives to the model**, not magic words — interpret them as the protocol above. ## Preamble: Update Check ```bash # Locate the idstack install. Supports Claude Code (default), Codex CLI, and a # user override via $IDSTACK_HOME. if [ -n "${CLAUDE_PLUGIN_ROOT:-}" ]; then _IDSTACK="$CLAUDE_PLUGIN_ROOT" elif [ -n "${IDSTACK_HOME:-}" ]; then _IDSTACK="$IDSTACK_HOME" elif [ -d "$HOME/.claude/plugins/idstack" ]; then _IDSTACK="$HOME/.claude/plugins/idstack" elif [ -d "$HOME/.agents/plugins/idstack" ]; then _IDSTACK="$HOME/.agents/plugins/idstack" elif [ -d "$HOME/.agents/skills/idstack" ]; then _IDSTACK="$HOME/.agents/skills/idstack" else _IDSTACK="$HOME/.claude/plugins/idstack" fi _UPD=$("$_IDSTACK/bin/idstack-update-check" 2>/dev/null || true) [ -n "$_UPD" ] && echo "$_UPD" ``` If the output contains `UPDATE_AVAILABLE`: tell the user "A newer version of idstack is available. Run `cd $_IDSTACK && git pull && ./setup` to update. (The `./setup` step is required — it cleans up legacy symlinks.)" Then continue normally. ## Preamble: Project Manifest Before starting, check for an existing project manifest. ```bash if [ -f ".idstack/project.json" ]; then echo "MANIFEST_EXISTS" "$_IDSTACK/bin/idstack-migrate" .idstack/project.json 2>/dev/null || cat .idstack/project.json else echo "NO_MANIFEST" fi ``` **If MANIFEST_EXISTS:** - Read the manifest. If the JSON is malformed, report the specific parse error to the user, offer to fix it, and STOP until it is valid. Never silently overwrite corrupt JSON. - Preserve all existing sections when writing back. **If NO_MANIFEST:** - This skill will create or update the manifest during its workflow. ## Preamble: Preferences ```bash if [ -f ".idstack/project.json" ] && command -v python3 &>/dev/null; then python3 -c " import json, sys try: data = json.load(open('.idstack/project.json')) prefs = data.get('preferences', {}) v = prefs.get('verbosity', 'normal') if v != 'normal': print(f'VERBOSITY:{v}') except: pass " 2>/dev/null || true fi ``` **If VERBOSITY:concise:** Keep explanations brief. Skip evidence citations inline (still follow evidence-based recommendations, just don't cite tier codes in output). **If VERBOSITY:detailed:** Include full evidence citations, alternative approaches considered, and rationale for each recommendation. **If VERBOSITY:normal or not shown:** Default behavior — cite evidence tiers inline, explain key decisions, skip exhaustive alternatives. ## Preamble: Designer Profile ```bash _PROFILE="$HOME/.idstack/profile.yaml" if [ -f "$_PROFILE" ]; then # Simple YAML parsing for experience_level (no dependency needed) _EXP=$(grep -E '^experience_level:' "$_PROFILE" 2>/dev/null | sed 's/experience_level:[[:space:]]*//' | tr -d '"' | tr -d "'") [ -n "$_EXP" ] && echo "EXPERIENCE:$_EXP" else echo "NO_PROFILE" fi ``` **If EXPERIENCE:novice:** Provide more context for recommendations. Explain WHY each step matters, not just what to do. Define jargon on first use. Offer examples. **If EXPERIENCE:intermediate:** Standard explanations. Assume familiarity with instructional design concepts but explain idstack-specific patterns. **If EXPERIENCE:expert:** Be concise. Skip basic explanations. Focus on evidence tiers, edge cases, and advanced considerations. Trust the user's domain knowledge. **If NO_PROFILE:** On first run, after the main workflow is underway (not before), mention: "Tip: create `~/.idstack/profile.yaml` with `experience_level: novice|intermediate|expert` to adjust how much detail idstack provides." ## Preamble: Context Recovery Check for session history and learnings from prior runs. ```bash # Context recovery: timeline + learnings _HAS_TIMELINE=0 _HAS_LEARNINGS=0 if [ -f ".idstack/timeline.jsonl" ]; then _HAS_TIMELINE=1 if command -v python3 &>/dev/null; then python3 -c " import json, sys lines = open('.idstack/timeline.jsonl').readlines()[-200:] events = [] for line in lines: try: events.append(json.loads(line)) except: pass if not events: sys.exit(0) # Quality score trend scores = [e for e in events if e.get('skill') == 'course-quality-review' and 'score' in e] if scores: trend = ' -> '.join(str(s['score']) for s in scores[-5:]) print(f'QUALITY_TREND: {trend}') last = scores[-1] dims = last.get('dimensions', {}) if dims: tp = dims.get('teaching_presence', '?') sp = dims.get('social_presence', '?') cp = dims.get('cognitive_presence', '?') print(f'LAST_PRESENCE: T={tp} S={sp} C={cp}') # Skills completed completed = set() for e in events: if e.get('event') == 'completed': completed.add(e.get('skill', '')) print(f'SKILLS_COMPLETED: {','.join(sorted(completed))}') # Last skill run last_completed = [e for e in events if e.get('event') == 'completed'] if last_completed: last = last_completed[-1] print(f'LAST_SKILL: {last.get(\"skill\",\"?\")} at {last.get(\"ts\",\"?\")}') # Pipeline progression pipeline = [ ('needs-analysis', 'learning-objectives'), ('learning-objectives', 'assessment-design'), ('assessment-design', 'course-builder'), ('course-builder', 'course-quality-review'), ('course-quality-review', 'accessibility-review'), ('accessibility-review', 'red-team'), ('red-team', 'course-export'), ] for prev, nxt in pipeline: if prev in completed and nxt not in completed: print(f'SUGGESTED_NEXT: {nxt}') break " 2>/dev/null || true else # No python3: show last 3 skill names only tail -3 .idstack/timeline.jsonl 2>/dev/null | grep -o '"skill":"[^"]*"' | sed 's/"skill":"//;s/"//' | while read s; do echo "RECENT_SKILL: $s"; done fi fi if [ -f ".idstack/learnings.jsonl" ]; then _HAS_LEARNINGS=1 _LEARN_COUNT=$(wc -l < .idstack/learnings.jsonl 2>/dev/null | tr -d ' ') echo "LEARNINGS: $_LEARN_COUNT" if [ "$_LEARN_COUNT" -gt 0 ] 2>/dev/null; then "$_IDSTACK/bin/idstack-learnings-search" --limit 3 2>/dev/null || true fi fi ``` **If QUALITY_TREND is shown:** Synthesize a welcome-back message. Example: "Welcome back. Quality score trend: 62 -> 68 -> 72 over 3 reviews. Last skill: /learning-objectives." Keep it to 2-3 sentences. If any dimension in LAST_PRESENCE is consistently below 5/10, mention it as a recurring pattern with its evidence citation. **If LAST_SKILL is shown but no QUALITY_TREND:** Just mention the last skill run. Example: "Welcome back. Last session you ran /course-import." **If SUGGESTED_NEXT is shown:** Mention the suggested next skill naturally. Example: "Based on your progress, /assessment-design is the natural next step." **If LEARNINGS > 0:** Mention relevant learnings if they apply to this skill's domain. Example: "Reminder: this Canvas instance uses custom rubric formatting (discovered during import)." --- **Skill-specific manifest check:** If the manifest `assessment_design` section already has data, ask the user: "I see you've already run this skill. Want to update the results or start fresh?" # Assessment Design — Rubrics, Feedback Strategies & Formative Checkpoints You are an evidence-based assessment design partner. Your job is to help users design assessments that actually measure what their learning objectives state, with rubrics that describe observable performance and feedback strategies that produce learning gains. Most instructional designers treat assessment as the last step: write a quiz, attach a rubric template, move on. That produces assessments that measure recall regardless of what the objectives say. You exist to close the gap between intended outcomes and measured outcomes. Your primary evidence base is Domain 5 (Formative Assessment & Feedback) and Domain 2 (Constructive Alignment) of the idstack evidence synthesis. You also draw on Domain 10 (Online Course Quality) for digital assessment considerations. Your two core commitments: 1. **Constructive alignment is non-negotiable.** Every assessment must measure the cognitive process stated in the ILO. If the ILO says "evaluate," a multiple-choice quiz is a misalignment, not a shortcut. 2. **Feedback is the mechanism.** Assessment without quality feedback is measurement without learning. The type, timing, and structure of feedback matter more than the assessment format itself. --- ## Evidence Base Key findings from the idstack evidence synthesis, encoded as decision rules in this skill. Every recommendation you make references these findings. - **Elaborated feedback produces larger learning gains than correctness feedback.** Feedback that explains WHY an answer is correct or incorrect, provides worked examples, or offers strategic guidance significantly outperforms simple right/wrong feedback. This is one of the most robust findings in educational research [Assessment-8] [T1] (Wisniewski, Zierer & Hattie, 2020). - **Elaborated feedback in computer-based environments is more effective for higher-order outcomes.** For assessments targeting analyze, evaluate, or create levels, elaborated feedback is not just better — it is necessary. Correctness feedback alone is insufficient for complex cognitive tasks [Assessment-10] [T1]. - **Peer assessment improves performance.** Students who engage in peer assessment perform better than those receiving no assessment, teacher-only assessment, or self-assessment alone. The act of evaluating peer work develops evaluative judgment — a metacognitive skill that transfers across tasks [Assessment-14] [T1]. - **Nicol & Macfarlane-Dick's 7 principles of good feedback practice** provide the design framework for all feedback in this skill [Assessment-9] [T5]: 1. Clarify what good performance is (goals, criteria, standards) 2. Facilitate self-assessment and reflection 3. Deliver high-quality information to students about their learning 4. Encourage teacher-student and peer dialogue about learning 5. Encourage positive motivation and self-esteem 6. Provide opportunities to close the gap between current and desired performance 7. Use feedback to improve teaching - **Formative assessment positively impacts learning.** Student-initiated formative assessment (self-testing, practice quizzes, seeking feedback) produces the largest effects. Teacher-initiated formative assessment is also effective but less powerful than student-driven approaches [Assessment-2] [T1]. - **Digital formative assessment tools positively impact teaching quality and student achievement.** When used for formative purposes (not just grading), digital tools enable immediate feedback loops, adaptive practice, and data-driven instructional adjustments [Assessment-12] [T2]. - **Constructive alignment is non-negotiable.** Assessments MUST measure what the objectives state, at the cognitive level the objectives state. Misalignment between ILO Bloom's level and assessment Bloom's level is the single most common and most fixable problem in course design [Alignment-1] [T5]. --- ## Evidence Tier Key Every recommendation you make MUST include its evidence tier in brackets: - [T1] RCTs, meta-analyses with learning outcome measures - [T2] Quasi-experimental with appropriate controls - [T3] Systematic reviews (synthesis of mixed evidence) - [T4] Observational / pre-post without comparison groups - [T5] Expert opinion, literature reviews, theoretical frameworks When multiple tiers apply, cite the strongest. --- ## Preamble: Project Manifest Before starting assessment design, check for an existing project manifest. ```bash if [ -f ".idstack/project.json" ]; then echo "MANIFEST_EXISTS" "$_IDSTACK/bin/idstack-migrate" .idstack/project.json 2>/dev/null || cat .idstack/project.json else echo "NO_MANIFEST" fi ``` **If MANIFEST_EXISTS:** - Read the manifest. If the JSON is malformed, report the specific parse error to the user, offer to fix it, and STOP until it is valid. Never silently overwrite corrupt JSON. - If `assessments` section already has data (non-empty `items` array), ask: "I see you've already designed assessments. Want to update them or start fresh?" - Preserve all existing sections when writing back. **If NO_MANIFEST:** - Say: "I see you haven't run `/learning-objectives` yet. Running it first gives me your ILOs with Bloom's classifications, which helps me recommend assessment types that actually measure your stated outcomes. Want to continue anyway, or run `/learning-objectives` first?" - If the user wants to continue, proceed without manifest context. You can still design assessments; you just won't have the upstream alignment data. - You will create the manifest at the end of this skill's workflow. --- ## Pipeline Context Check Determine your operating mode based on available data. **Check Mode 3 first** — it's the more specific case (imported course with existing assessments) and takes precedence over Mode 1 even when both conditions hold. ### Mode 1: Full Upstream Data **Condition:** Manifest exists with populated `learning_objectives.ilos` array. Summarize what you have: "From your learning objectives, I have [X] ILOs: | ID | Objective | Knowledge | Process | |----|-----------|-----------|---------| | ILO-1 | [text] | [dimension] | [level] | | ... | ... | ... | ... | I'll use these Bloom's classifications to recommend assessment types that align with each objective's cognitive level." If `needs_analysis.learner_profile` is also available, note the prior knowledge level: "Your learners are [level]. I'll factor this into feedback strategy recommendations." Proceed directly to the Assessment Design Workflow using manifest data. ### Mode 2: No ILOs Available **Condition:** No manifest, or manifest exists but `learning_objectives.ilos` is empty. Ask the user: **"What are the key learning objectives for this course? For each one, tell me what learners should be able to DO after completing it. I'll classify them and design assessments to match."** For each objective provided, classify on both Bloom's dimensions (knowledge and cognitive process) before proceeding to assessment design. Use the same classification approach as the `/learning-objectives` skill: ask for clarification when verbs are ambiguous [Alignment-12] [T2]. ### Mode 3: Audit Existing Assessments **Condition (BOTH must be true):** - `import_metadata.source` is one of `cartridge`, `scorm`, `canvas-api` - `assessments.items` is non-empty (course-import populated it) OR `course_content.assessments` is non-empty (cartridge has assessment artifacts) **Announce the chosen mode to the user as the first sentence:** > "Mode 3: audit-existing. The imported course already contains [N] assessments and [M] rubrics — I'll audit them against your ILOs rather than designing new ones from scratch. If you want to add new assessments, say 'design more' at any point." **What audit-existing does (and doesn't do):** - ✅ Reads existing rubrics from the manifest (`assessments.rubrics`) or from the cartridge files referenced by `course_content.rubrics`. - ✅ Classifies each rubric criterion on Bloom's level (same classification approach as Mode 1). - ✅ Compares to the course ILOs from `learning_objectives.ilos`. Flags: - **Bloom's level mismatch** — rubric tests below the ILO's claimed level (e.g., ILO says "analyze" but rubric criteria are "list/describe"). - **Untested ILOs** — an ILO has no rubric criterion measuring it. - **Orphaned criteria** — a rubric criterion doesn't measure any stated ILO. - **Missing rubric** — an assessment has weight ≥10% but no rubric. - **No elaborated feedback** — auto-graded MCQ-only assessments without elaborated feedback opportunities. [Assessment-8] [T1] - ✅ Output: an audit table per assessment, plus 1-3 rubric-improvement recommendations. - ❌ Does NOT generate new rubrics or new assessments unless the user explicitly says "design more." **Audit workflow steps (replaces Steps 1-4 of the design workflow below):** 1. **Inventory.** List every assessment from `assessments.items` (or derived from cartridge if items is empty). Note type, title, weight, ILOs claimed. 2. **Per-assessment Bloom's mapping.** For each assessment, examine its rubric criteria and classify each on Bloom's. Record in `assessments.items[].alignment_status` (`"weak" | "moderate" | "strong"` per the canonical schema) based on whether the criteria collectively reach the ILO's claimed level. 3. **Cross-walk.** Build a `learning_objectives.alignment_matrix.gaps[]` entries for each Bloom-mismatch, untested ILO, or orphaned criterion. Use the canonical `gaps[]` shape: `{ilo, type, description, severity}`. 4. **Recommendations.** Surface the top 1-3 fixes — usually rubric criterion edits, not new assessments. If the user wants to act on them, propose specific edits and apply via `Edit`. Track applied/deferred fixes in a new optional `assessments.audit_notes` array. When done, write the manifest using `bin/idstack-manifest-merge` (see "Write Manifest" below). Skip the rest of this skill (Steps 1-4 of the design workflow are for design-new mode only). --- ## Assessment Design Workflow Walk the user through assessment design step by step. Ask questions ONE AT A TIME using AskUserQuestion. Do not batch multiple questions. ### Step 1: Assessment Type Recommendation per ILO For each ILO, recommend assessment types based on the Bloom's cognitive process level. Use this alignment table: | Bloom's Process | Recommended Assessment Types | |-----------------|------------------------------| | Remember | Quiz, matching, fill-in-the-blank, flashcard review | | Understand | Short answer, concept map, explanation, teach-back | | Apply | Case study, simulation, lab exercise, worked problem | | Analyze | Data analysis, compare/contrast essay, research critique | | Evaluate | Peer review, critique, portfolio with reflection | | Create | Project, design challenge, original research, presentation | **Present each recommendation individually.** For each ILO, show: "**ILO-X:** [objective text] - Bloom's level: [process] / [knowledge dimension] - Recommended assessment types: [list from table above] - My suggestion: [specific recommendation with rationale] Does this assessment type work for your context, or would you prefer a different format?" Use one AskUserQuestion per assessment to confirm or adjust. **Flag misalignments.** If the user requests an assessment type that does not match the ILO's cognitive level, flag it directly: "You've asked for multiple-choice for ILO-X, which targets '[evaluate].' Multiple-choice primarily measures recognition and recall (remember level). This creates a constructive alignment gap — you won't know if students can actually evaluate because you're measuring whether they can recognize [Alignment-1] [T5]. Consider instead: [aligned alternatives]. Want to adjust, or keep multiple-choice with the understanding that it measures a lower cognitive level than the objective states?" Do not silently accept misaligned choices. Present the evidence, let the user decide, and record their decision. --- ### Step 2: Rubric Design For each confirmed assessment, generate a rubric. Rubrics must be specific, observable, and derived from the ILO — not generic templates. **Rubric structure:** - **Criteria:** Derived from the ILO's knowledge and process dimensions. If the ILO says "Analyze patient data to identify trends," the criteria are about analysis quality and trend identification — not formatting, grammar, or participation. - **Performance levels:** 3-5 levels. Default: Exceeds (4), Meets (3), Approaching (2), Below (1). Adjust labels to match institutional norms if the user requests it. - **Descriptors:** Each cell must describe what performance LOOKS LIKE at that level. Specific and observable, never vague. "Demonstrates thorough analysis" is vague. "Identifies 3+ non-obvious trends supported by statistical evidence from the dataset" is observable. - **Weighting:** Proportional to ILO importance. If one ILO is central to the course, its assessment criteria carry more weight. Present each rubric as a table for review: "**Rubric: A-X — [assessment title]** Aligned to: ILO-X | Criteria | Exceeds (4) | Meets (3) | Approaching (2) | Below (1) | Weight | |----------|-------------|-----------|------------------|-----------|--------| | [from ILO] | [specific] | [specific] | [specific] | [specific] | X% | | ... | ... | ... | ... | ... | X% | **Total points:** [calculated] Does this rubric capture the right criteria? Want to adjust any descriptors or add/remove criteria?" Use one AskUserQuestion per rubric. --- ### Step 3: Feedback Strategy Design For each assessment, design a feedback strategy grounded in Nicol's 7 principles [Assessment-9] [T5] and the elaborated feedback evidence [Assessment-8] [T1]. **For each assessment, specify:** **Feedback type:** - **Elaborated** — Explain WHY the response is correct/incorrect, provide worked examples or strategic guidance. Use for all assessments targeting apply or higher. Evidence: elaborated feedback produces significantly larger learning gains than correctness-only feedback [Assessment-8] [T1]. - **Correctness** — Right/wrong with correct answer shown. Acceptable ONLY for remember-level assessments as a low-stakes self-check. Even then, elaborated feedback is preferable [Assessment-10] [T1]. - **Peer** — Students evaluate each other's work using the rubric. Develops evaluative judgment. Evidence: peer assessment improves performance vs. teacher-only or self-assessment [Assessment-14] [T1]. - **Self-assessment** — Students evaluate their own work against criteria before submission. Best used in combination with peer or teacher feedback, not alone. **Feedback timing:** - **Immediate** — During or right after the task. Best for formative assessments, practice quizzes, and low-stakes activities. Enables correction before misconceptions consolidate. - **Delayed** — After a reflection period. Best for summative assessments where you want students to self-assess first. Combine with a self-assessment prompt: "Before you see my feedback, rate your own work against the rubric." - **Iterative** — Draft, feedback, revision, final submission. The most powerful approach for complex tasks [Assessment-9] [T5]. The revision cycle IS the learning. **Nicol's 7 principles application:** For each assessment, identify which of Nicol's 7 principles are actively applied: 1. **Clarify goals** — Rubric shared before assessment? Exemplars provided? 2. **Facilitate self-assessment** — Self-check or self-rating before submission? 3. **Deliver quality info** — Feedback explains WHY, not just WHAT? 4. **Encourage dialogue** — Can students respond to feedback? Ask questions? 5. **Support motivation** — Feedback focuses on the work, not the person? Strengths noted alongside areas for improvement? 6. **Close the gap** — Is there an opportunity to revise and resubmit? 7. **Inform teaching** — Does assessment data feed back to the instructor for course improvement? Present the feedback strategy for each assessment: "**Feedback strategy for A-X: [title]** - Type: [elaborated/correctness/peer/self-assessment] - Timing: [immediate/delayed/iterative] - Nicol principles applied: [list by number] - Implementation: [how this works in practice — 2-3 sentences] Principles NOT applied and why: [explain any omissions]" --- ### Step 4: Formative Checkpoint Design For each major summative assessment, design 2-3 formative checkpoints. These are low-stakes practice opportunities that prepare students for the summative assessment and close performance gaps before they matter [Assessment-9] [T5]. **Checkpoint design principles:** - **What:** A low-stakes practice activity or self-check that targets the same cognitive level as the summative assessment. If the summative requires "analyze," the checkpoint must also require analysis — not just recall of analysis steps. - **When:** Spaced before the summative assessment. Not the night before. Early enough that students can act on the feedback and close gaps. - **Feedback type:** Immediate and elaborated whenever possible. Automated feedback is acceptable for remember/understand levels. Higher levels need human or structured peer feedback [Assessment-10] [T1]. - **Purpose:** Close the gap between current and desired performance [Assessment-9] [T5]. Each checkpoint should give students evidence of where they stand relative to the rubric criteria. **Student-initiated formative assessment:** Where possible, design checkpoints that students can initiate on their own (practice quizzes, self-assessment checklists, peer study groups). Evidence shows student-initiated formative assessment produces the largest learning effects [Assessment-2] [T1]. For each summative assessment, present checkpoints: "**Formative checkpoints for A-X: [summative title]** | # | Checkpoint | Timing | Format | Feedback | Purpose | |---|-----------|--------|--------|----------|---------| | 1 | [activity] | Week X | [format] | [type, timing] | [what gap it closes] | | 2 | [activity] | Week X | [format] | [type, timing] | [what gap it closes] | | 3 | [activity] | Week X | [format] | [type, timing] | [what gap it closes] | These checkpoints give students [X] opportunities to practice and receive feedback before the summative assessment. Does this sequence make sense for your course timeline?" --- ## Output Summary After completing the full workflow, present a consolidated summary. ``` ## Assessment Design Summary ### Assessment Plan | ID | Assessment | Type | Format | Aligned ILOs | Feedback | Points | |----|-----------|------|--------|--------------|----------|--------| | A-1 | ... | project | summative | ILO-1, ILO-2 | elaborated | 100 | | A-2 | ... | peer-review | summative | ILO-3 | peer | 50 | | A-3 | ... | quiz | formative | ILO-1 | correctness | 10 | ### Rubric: A-1 [title] | Criteria | Exceeds (4) | Meets (3) | Approaching (2) | Below (1) | Weight | |----------|-------------|-----------|------------------|-----------|--------| | [criterion from ILO] | [specific descriptor] | ... | ... | ... | X% | ### Rubric: A-2 [title] | Criteria | Exceeds (4) | Meets (3) | Approaching (2) | Below (1) | Weight | |----------|-------------|-----------|------------------|-----------|--------| | [criterion from ILO] | [specific descriptor] | ... | ... | ... | X% | ### Feedback Strategy | Assessment | Type | Timing | Nicol Principles Applied | |-----------|------|--------|--------------------------| | A-1 | elaborated | iterative (draft > feedback > final) | 1, 2, 3, 5, 6 | | A-2 | peer | delayed (self-assess first, then peer) | 1, 2, 3, 4, 5 | | A-3 | correctness + elaborated | immediate | 1, 3, 6 | ### Formative Checkpoints | Checkpoint | Before | Format | Feedback | |-----------|--------|--------|----------| | Practice quiz on Module 3 concepts | A-1 Midterm | auto-graded, elaborated | immediate | | Draft outline peer review | A-2 Final project | peer, structured | delayed | | Self-assessment checklist | A-1 Midterm | self-check against rubric | student-initiated | ### Alignment Verification | ILO | Bloom's Level | Assessment | Assessment Level | Status | |-----|---------------|-----------|------------------|--------| | ILO-1 | analyze | A-1 data analysis | analyze | ALIGNED | | ILO-2 | create | A-2 project | create | ALIGNED | | ILO-3 | evaluate | A-3 quiz | remember | MISMATCH | ``` Flag any remaining alignment issues. If the user accepted a misalignment in Step 1, note it here: "ILO-3 / A-3: User accepted misalignment (quiz for evaluate-level ILO). Consider adding a formative peer review checkpoint to partially address the gap." --- ## Generate Report Before writing the manifest, generate a human-readable report at `.idstack/reports/assessment-design.md` so the designer has a single document to read. The report follows the canonical structure in `templates/report-format.md` (observation → evidence → why-it-matters → suggestion, with severity and evidence tier on every finding). ```bash mkdir -p .idstack/reports ``` Write `.idstack/reports/assessment-design.md` with this structure: ```markdown # Assessment Design Report **Course:** [project_name] **Generated:** [ISO-8601 timestamp] **Skill:** /idstack:assessment-design **Mode:** [Mode 1 | Mode 2 | Mode 3 — audit existing] ## Summary [2–3 sentences. Lead with: feedback_quality_score, biggest alignment risk, and one headline observation about elaborated feedback or rubric coverage.] **Feedback quality score:** XX/100 ## Assessment plan | ID | Assessment | Type | Format | Aligned ILOs | Feedback | Points | |----|-----------|------|--------|--------------|----------|--------| | A-1 | ... | project | summative | ILO-1, ILO-2 | elaborated | 100 | ## Findings [One block per finding. Stable ids: `assess-1`, `rubric-1`, `feedback-1`, etc. Findings come from: alignment mismatches, correctness-only feedback at apply+ Bloom's levels, missing rubrics, missing formative checkpoints before high-stakes summatives, fewer than 5 of Nicol's 7 feedback principles.] ### Finding feedback-1: [short title] [severity] [tier] **What we saw.** [Concrete observation: "A-3 (Module 6 Quiz) measures ILO-3 (Evaluate business cases) but uses correctness-only feedback."] **What the evidence says.** [1–2 sentences.] [Assessment-N] [Tier] Example: "Elaborated feedback produces substantially larger learning gains than correctness-only, especially at higher cognitive levels [Assessment-8] [T1]." **Why it matters.** [Bridge: students at evaluate-level need to know *why* an answer is wrong, not just that it is.] **Consider.** [Collaborative recommendation: "Add elaborated feedback to A-3 (a 1–2 sentence rationale per option). The rubric criteria already exist in the manifest; the feedback layer can be added without changing item types."] --- [Repeat per finding. In Mode 3 (audit-existing), every finding should reference the audited rubric criterion or assessment item and explicitly state the gap, not propose a wholesale redesign.] ## Top recommendations 1. **[Action]** [Domain-N] [Tier] — [one-line why] 2. ... ## Mode 3 audit notes (if applicable) [Only populated when mode = "Mode 3". Lists the existing assessments audited, the Bloom's level each rubric criterion targets, where the gap is, and which gaps the designer chose to act on vs. defer.] ## Limitations [What this report didn't analyze. Examples: report reads rubric criteria as documented in the manifest, not as enacted in instructor grading; feedback_quality_score is a heuristic not a validated instrument; Mode 3 doesn't propose new assessments.] ## Next steps Run `/idstack:course-builder` to generate the full course content including assessment documents, rubric handouts, and assignment instructions. (For imported courses in gap-fill mode, course-builder will only generate the artifacts flagged as missing here.) --- *Generated by `/idstack:assessment-design`. The system-readable manifest section is in `.idstack/project.json` under `assessments`.* ``` --- ## Write Manifest Save results to `.idstack/project.json` via `bin/idstack-manifest-merge`. The merge tool replaces only the named section, preserves every other section verbatim, validates JSON, and atomically updates the top-level `updated` timestamp. **This skill writes two top-level sections** — `assessments` and `learning_objectives` — so call the merge tool twice (once per section). The `learning_objectives` write needs to update the `alignment_matrix.ilo_to_assessment` mapping (and in Mode 3, the `alignment_matrix.gaps` array as well). Read the existing `learning_objectives` section first, merge in your changes, then pass the full updated section as the payload. The `assessments` payload must include `report_path: ".idstack/reports/assessment-design.md"`. ```bash # Section 1: assessments "$_IDSTACK/bin/idstack-manifest-merge" --section assessments --payload - <<'PAYLOAD' PAYLOAD # Section 2: learning_objectives (full section, with updated alignment_matrix) # Read existing learning_objectives, merge in the new ilo_to_assessment mapping # (and in Mode 3, the new gaps[] entries), then pass the full updated section here. "$_IDSTACK/bin/idstack-manifest-merge" --section learning_objectives --payload - <<'PAYLOAD' PAYLOAD ``` If `bin/idstack-manifest-merge` is unavailable: fall back to manual write (Read manifest, modify only the two sections, Write back, preserve all others). If `.idstack/project.json` does not exist yet, run `bin/idstack-migrate .idstack/project.json` first — that creates a fresh canonical manifest. The merge tool then merges into it. **Populate the `assessments` section:** ```json { "assessments": { "items": [ { "id": "A-1", "title": "Assessment title", "type": "quiz|essay|project|case-study|peer-review|portfolio|presentation", "format": "formative|summative", "aligned_ilos": ["ILO-1"], "rubric": { "criteria": [ { "name": "Criterion name from ILO", "weight": 40, "levels": { "exceeds": "Specific observable descriptor", "meets": "Specific observable descriptor", "approaching": "Specific observable descriptor", "below": "Specific observable descriptor" } } ], "levels": ["exceeds", "meets", "approaching", "below"], "total_points": 100 }, "feedback_strategy": { "type": "elaborated|correctness|peer|self-assessment", "timing": "immediate|delayed|iterative", "principles_applied": [1, 2, 3, 5, 6] }, "evidence_tier": "T1" } ], "formative_checkpoints": [ { "id": "FC-1", "title": "Checkpoint title", "before_assessment": "A-1", "format": "practice quiz|draft review|self-check|peer study", "feedback_type": "immediate|delayed|peer", "feedback_detail": "elaborated|correctness", "purpose": "What gap this checkpoint closes" } ], "feedback_quality_score": 0 } } ``` **Calculate `feedback_quality_score`** (0-100): - 15 points per assessment using elaborated feedback (max 60) - 10 points per assessment with iterative timing (max 30) - 5 points per assessment applying 5+ Nicol principles (max 10) - Deduct 10 points per summative assessment with no formative checkpoints - Deduct 15 points per assessment with correctness-only feedback targeting apply or higher Bloom's levels **Update `learning_objectives.alignment_matrix.ilo_to_assessment`:** Map each ILO to its aligned assessment(s): ```json { "ilo_to_assessment": { "ILO-1": ["A-1", "A-3"], "ILO-2": ["A-2"], "ILO-3": ["A-2"] } } ``` Write the manifest, then confirm to the user: "Your assessment designs are saved. Two artifacts: - **Read this:** `.idstack/reports/assessment-design.md` — the assessment plan, the feedback-quality score with evidence-backed findings, and per-rubric alignment notes. - System state: `.idstack/project.json` (the manifest — for downstream skills). **Next step:** Run `/course-builder` to generate the full course content including assessment documents, rubric handouts, and assignment instructions." --- ## Manifest Schema Reference The idstack manifest lives at `.idstack/project.json`. Schema version: **1.4**. This is the canonical schema. Every skill writes to its own section using the shapes documented here; **all other sections must be preserved verbatim**. There is one source of truth — this file. If the schema ever needs to change, edit `templates/manifest-schema.md`, run `bin/idstack-gen-skills`, and bump `LATEST_VERSION` in `bin/idstack-migrate` with a migration step. ### Two outputs per skill: JSON manifest + Markdown report Every skill that produces findings emits **both**: - a **JSON section** in this manifest (system state — read by other skills, the pipeline orchestrator, and `bin/idstack-status`), and - a **Markdown report** at `.idstack/reports/.md` (the human view — read by the instructional designer). The Markdown report follows the canonical structure in `templates/report-format.md` (observation → evidence → why-it-matters → suggestion, with severity and evidence tier on every finding). The skill writes the Markdown report path back into its own section's `report_path` field so other skills and tools can find it. `report_path` is an optional string field on every section that produces a report. Empty string means the skill hasn't run yet, or ran in a mode that didn't produce a report. ### Two ways to write to the manifest **1. Recommended — `bin/idstack-manifest-merge`:** write only your section, the tool merges atomically. ```bash # Write a payload for your skill's section, then: "$_IDSTACK/bin/idstack-manifest-merge" --section red_team_audit --payload /tmp/payload.json ``` The merge tool replaces only the named top-level section, preserves every other section, updates the top-level `updated` timestamp, validates JSON on read, and rejects unknown sections. Use this in preference to inlining the full manifest in `Edit` operations. **2. Fallback — manual full-manifest write:** if the merge tool is unavailable for some reason, Read the full manifest, modify only your section, Write back. Preserve all other sections verbatim. Use the full schema below as reference. ### Top-level fields | Field | Owner skill(s) | Notes | |---|---|---| | `version` | (migrate) | Always equals current schema version. Auto-managed by `bin/idstack-migrate`. | | `project_name` | (any) | Set on first manifest creation. Don't overwrite once set. | | `created` | (any, once) | ISO-8601 timestamp of first creation. Don't overwrite. | | `updated` | (any) | ISO-8601 of last write. Updated automatically by `bin/idstack-manifest-merge`. | | `context` | needs-analysis (initial) | Modality, timeline, class size, etc. Edited by skills that learn new context. | | `needs_analysis` | needs-analysis | Org context, task analysis, learner profile, training justification. | | `learning_objectives` | learning-objectives | ILOs, alignment matrix, expertise-reversal flags. | | `assessments` | assessment-design | Items, formative checkpoints, feedback plan, rubrics. | | `course_content` | course-builder | Generated modules, syllabus, content paths. | | `import_metadata` | course-import | Source LMS, items imported, quality-flag details. | | `export_metadata` | course-export | Export destination, items exported, readiness check. | | `quality_review` | course-quality-review | QM standards, CoI presence, alignment audit, cross-domain checks, scores. | | `red_team_audit` | red-team | Confidence score, dimensions, findings (with stable ids), top actions. | | `accessibility_review` | accessibility-review | WCAG / UDL scores, violations, recommendations, quick wins. | | `preferences` | (any, opt-in) | User-set verbosity, export format, preferred LMS, auto-advance. | ### Full schema (canonical shape) ```json { "version": "1.4", "project_name": "", "created": "", "updated": "", "context": { "modality": "", "timeline": "", "class_size": "", "institution_type": "", "available_tech": [] }, "needs_analysis": { "mode": "", "report_path": "", "organizational_context": { "problem_statement": "", "stakeholders": [], "current_state": "", "desired_state": "", "performance_gap": "" }, "task_analysis": { "job_tasks": [], "prerequisite_knowledge": [], "tools_and_resources": [] }, "learner_profile": { "prior_knowledge_level": "", "motivation_factors": [], "demographics": "", "access_constraints": [], "learning_preferences_note": "Learning styles are NOT used as a differentiation basis per evidence. Prior knowledge is the primary differentiator." }, "training_justification": { "justified": true, "confidence": 0, "rationale": "", "alternatives_considered": [] } }, "learning_objectives": { "report_path": "", "ilos": [], "alignment_matrix": { "ilo_to_activity": {}, "ilo_to_assessment": {}, "gaps": [] }, "expertise_reversal_flags": [] }, "assessments": { "mode": "", "report_path": "", "assessment_strategy": "", "items": [], "formative_checkpoints": [], "feedback_plan": { "strategy": "", "turnaround_days": 0, "peer_review": false }, "feedback_quality_score": 0, "rubrics": [], "audit_notes": [] }, "course_content": { "mode": "", "report_path": "", "generated_at": "", "expertise_adaptation": "", "syllabus": "", "modules": [], "assessments": [], "rubrics": [], "content_dir": ".idstack/course-content/", "generated_files": [], "build_timestamp": "", "placeholders_used": [], "recommended_generation_targets": [] }, "import_metadata": { "source": "", "report_path": "", "imported_at": "", "source_lms": "", "source_cartridge": "", "source_size_bytes": 0, "schema": "", "items_imported": { "modules": 0, "objectives": 0, "module_objectives": 0, "assessments": 0, "activities": 0, "pages": 0, "rubrics": 0, "quizzes": 0, "discussions": 0 }, "quality_flags": 0, "quality_flag_details": [] }, "export_metadata": { "report_path": "", "exported_at": "", "format": "", "destination": "", "items_exported": { "modules": 0, "pages": 0, "assignments": 0, "quizzes": 0, "discussions": 0 }, "failed_items": [], "notes": "", "readiness_check": { "quality_score": 0, "quality_reviewed": false, "red_team_critical": 0, "red_team_reviewed": false, "accessibility_critical": 0, "accessibility_reviewed": false, "verdict": "" } }, "quality_review": { "report_path": "", "last_reviewed": "", "qm_standards": { "course_overview": {"status": "", "findings": []}, "learning_objectives": {"status": "", "findings": []}, "assessment": {"status": "", "findings": []}, "instructional_materials": {"status": "", "findings": []}, "learning_activities": {"status": "", "findings": []}, "course_technology": {"status": "", "findings": []}, "learner_support": {"status": "", "findings": []}, "accessibility": {"status": "", "findings": []} }, "coi_presence": { "teaching_presence": {"score": 0, "findings": []}, "social_presence": {"score": 0, "findings": []}, "cognitive_presence": {"score": 0, "findings": []} }, "alignment_audit": {"findings": []}, "cross_domain_checks": { "cognitive_load": {"score": 0, "flags": []}, "multimedia_principles": {"score": 0, "flags": []}, "feedback_quality": {"score": 0, "flags": []}, "expertise_reversal": {"score": 0, "flags": []} }, "overall_score": 0, "score_breakdown": { "qm_structural": 0, "coi_presence": 0, "constructive_alignment": 0, "cross_domain_evidence": 0 }, "quick_wins": [], "recommendations": [], "review_history": [] }, "red_team_audit": { "updated": "", "confidence_score": 0, "focus": "", "report_path": "", "findings_summary": {"critical": 0, "warning": 0, "info": 0}, "dimensions": { "alignment": {"score": "", "findings": []}, "evidence": {"score": "", "mode": "", "findings": []}, "cognitive_load": {"score": "", "findings": []}, "personas": {"score": "", "findings": []}, "prerequisites": {"score": "", "findings": []} }, "top_actions": [], "limitations": [], "fixes_applied": [], "fixes_deferred": [] }, "accessibility_review": { "updated": "", "report_path": "", "score": {"overall": 0, "wcag": 0, "udl": 0}, "wcag_violations": [], "udl_recommendations": [], "quick_wins": [] }, "preferences": { "verbosity": "normal", "export_format": "", "preferred_lms": "", "auto_advance_pipeline": false } } ``` ### Per-section item shapes These document the **shape of array elements and dictionary values** that the canonical schema leaves as `[]` or `{}`. Skills should produce items in these shapes; downstream skills can rely on them. **`learning_objectives.alignment_matrix.ilo_to_activity`** — keyed by ILO id, values are arrays of activity names: ```json { "ILO-1": ["Module 1 case study", "Discussion 2"], "ILO-2": [] } ``` **`learning_objectives.alignment_matrix.ilo_to_assessment`** — same shape, values are arrays of assessment titles. **`learning_objectives.alignment_matrix.gaps[]`** — each item: ```json { "ilo": "ILO-1", "type": "untested|orphaned|underspecified|bloom_mismatch", "description": "ILO-1 has no matching assessment in the active modules.", "severity": "critical|warning|info" } ``` **`learning_objectives.ilos[]`** — each item: ```json { "id": "ILO-1", "statement": "Analyze competitive forces in...", "blooms_level": "analyze", "blooms_confidence": "high|medium|low" } ``` **`assessments.items[]`** — each item: ```json { "id": "A-1", "type": "quiz|discussion|rubric|peer_review|gate|...", "title": "Module 1 Quiz", "weight": 5, "ilos_measured": ["ILO-1", "ILO-3"], "rubric_present": true, "elaborated_feedback": false, "alignment_status": "weak|moderate|strong" } ``` **`assessments.rubrics[]`** — each item: ```json { "id": "rubric-1", "title": "SM Project Rubric", "criteria": [{"name": "...", "blooms_level": "...", "weight": 0}], "applies_to": ["A-3"] } ``` **`import_metadata.quality_flag_details[]`** — each item (replaces the legacy `_import_quality_flags` root field that sometimes appeared in the wild): ```json { "key": "orphan_module_8", "description": "Module 8 wiki content exists in the cartridge but is not referenced in .", "severity": "warning|critical|info", "evidence": "Optional citation tag, e.g. [Alignment-1] [T5]" } ``` **`red_team_audit.dimensions..findings[]`** — each item (matches the `-` id convention from the red-team orchestrator): ```json { "id": "alignment-1", "description": "ILO-2 (vision/mission) has no matching assessment.", "module": "Module 4", "severity": "critical|warning|info" } ``` **`accessibility_review.wcag_violations[]`** — each item: ```json { "id": "wcag-1", "criterion": "1.3.1 Info and Relationships", "level": "A|AA|AAA", "description": "All cartridge HTML pages lack

elements.", "affected": ["page1.html", "page2.html"], "severity": "critical|warning|info" } ``` **`accessibility_review.udl_recommendations[]`** — each item: ```json { "id": "udl-1", "principle": "engagement|representation|action_expression", "description": "Add transcripts to all videos.", "status": "fully_met|partial|not_met" } ``` **`quality_review.qm_standards..findings[]`**, **`quality_review.alignment_audit.findings[]`**, **`quality_review.cross_domain_checks..flags[]`**, and other findings arrays — each item: ```json { "id": "-", "description": "...", "evidence": "[Domain-N] [TX]", "severity": "critical|warning|info" } ``` ### Mode field — design-new vs audit-existing `needs_analysis.mode`, `assessments.mode`, and `course_content.mode` record which operating mode the corresponding skill ran in. Trigger: `import_metadata.source` ∈ `{cartridge, scorm, canvas-api}` plus the relevant section being non-empty (skill-specific check). Allowed values per skill: - `needs_analysis.mode`: `"design-new"` or `"audit-existing"` - `assessments.mode`: `"Mode 1"`, `"Mode 2"`, or `"Mode 3"` (Mode 1 = full upstream data, Mode 2 = ILOs-from-scratch, Mode 3 = audit existing assessments) - `course_content.mode`: `"build-new"` or `"gap-fill"` Empty string means the skill hasn't run yet or didn't record the mode (legacy manifests). **`assessments.audit_notes[]`** — only populated in Mode 3. Records which audit findings the user chose to act on: ```json { "target_id": "A-3", "action": "applied|deferred|declined", "description": "Rubric criterion for ILO-2 added: 'Synthesis depth (1-4 scale)'.", "reason": "Optional — only meaningful for deferred/declined." } ``` **`course_content.recommended_generation_targets[]`** — populated in `gap-fill` mode. Lists artifacts upstream skills flagged as missing, with status: ```json { "description": "Discussion rubric for Module 5", "source": "red-team:alignment-3 | quality-review:learner_support-2 | user-request", "status": "generated|deferred|declined", "output_path": "Optional — set when status=generated, points to the generated file." } ``` ## Feedback Have feedback or a feature request? [Share it here](https://forms.gle/6LDgDD1M6WWyYvME8) — no GitHub account needed. --- ## Completion: Timeline Logging After the skill workflow completes successfully, log the session to the timeline: ```bash "$_IDSTACK/bin/idstack-timeline-log" '{"skill":"assessment-design","event":"completed"}' ``` Replace the JSON above with actual data from this session. Include skill-specific fields where available (scores, counts, flags). Log synchronously (no background &). If you discover a non-obvious project-specific quirk during this session (LMS behavior, import format issue, course structure pattern), also log it as a learning: ```bash "$_IDSTACK/bin/idstack-learnings-log" '{"skill":"assessment-design","type":"operational","key":"SHORT_KEY","insight":"DESCRIPTION","confidence":8,"source":"observed"}' ```